Unlocking the genetic diversity of bush hyacinth bean (Lablab purpureus var. typicus L.) landraces under South Indian agro-ecologies

Unlocking the genetic diversity of bush hyacinth bean (Lablab purpureus var. typicus L.) landraces under South Indian agro-ecologies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Unlocking the genetic diversity of bush hyacinth bean (Lablab purpureus var. typicus L.) landraces under South Indian agro-ecologies M. Harini, P. Sudheer Kumar Reddy, K. Vignesh, K. Hari, P. Syam Sundar Reddy This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6181502/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Hyacinth bean is an underutilized leguminous vegetable crop with tremendous potential to contribute enormously to sustainable agriculture and nutritional security. Conserving and utilising hyacinth bean landrace diversity is key to adapting the crop to challenges and identifying desirable traits such as yield and nutritional characteristics, benefiting both farmers and consumers. The current study was focused on the diversity of hyacinth beans based on the eighteen traits evaluated during two consecutive summer seasons of 2021 and 2022. Descriptive analysis of the traits revealed that the highest heritability and genetic advance were shown for yield/plot and yield/plant, respectively. Correlation is employed to arrange and examine the relationships between the eighteen yield and its attributing traits. The number of branches/plant, racemes/plant, seeds/pod, pod length, pod width, pods/plant and pod weight traits showed a significantly positive correlation with pod yield/plant. Dendrogram based clustering divided 26 genotypes into five groups, with cluster IV containing the most genotypes. The PCA analysis reveals the five principal components had eigenvalues of more than one and accounted for 82.62% of the total variation. PC1 alone contributed 47.52% of the total variance, followed by PC2 about 13.60%. Four superior genotypes including PKM LP 26 (Arka Vijay), PKM LP 35, PKM LP 27 (Arka Jay) and PKM LP 13 were identified as superior using the multi-trait genotype ideotype distance index (MGIDI). Two uncovered landraces such as PKM LP 35 and PKM LP 13 showed superior performance than the checks which can be used as vital assets for creating recombinant populations with effective crop enhancement strategies. Horticulture Hyacinth bean. Descriptive analysis. Dendrogram. Principal components. MGIDI Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Introduction Plant genetic resources (PGR’s) are the major genetic materials in any crop improvement programme especially for nutritional security (Singh et al. 2020 ). The PGR’s include wild relatives, advanced breeding lines, modern cultivars, landraces and induced mutants (Salgotra and Chauhan 2023 ). Landraces are traditional specific crop resources that play a vital role in maintaining the sustainability of traditional agroecosystems, food and nutritional security (Puneeth et al. 2024 ). These local ecotypes have varied morphological and less productive, but are generally extremely nutritious. Due to the adoptive evolution, landraces comprised a pool of genes for nutritive value and resistance to biotic and abiotic stresses (Palni et al. 1998 ). Insufficient documentation, inadequate transmission of ethnobotanical significance, lack of interest among younger generations and ineffective policy intervention have resulted in poor conservation and use of landraces in plant breeding. Plant breeders have been endeavouring to document the on-farm conserving activities across the global level (Conversa et al. 2020 ; Thant et al. 2020 ). Hyacinth bean ( Lablab purpureus var. typicus ) is a versatile and ancient vegetable crop with 2n = 22 chromosomes (She and Jiang, 2015 ), belonging to the Fabaceae family. It originated in India and distributed to South Asia, Southeast Asia, Africa and other tropical nations (Raghu et al. 2018 ). Fresh pods of hyacinth beans are highly nutritious and comprise 86.1% moisture, 3.8% protein, 6.7% carbohydrates 0.7% fat, 0.9% minerals and 312 I.U. of vitamin A/100g of edible amount (Tindall 1983 ). The seeds are used as vegetables in India, particularly in tribal areas (Dwivedi et al. 2023 ). Seeds contain 15–25% more protein than the pods (Gopalan et al. 2014 ). Consuming common beans regularly can lower the risk of coronary heart disease, type II diabetes, and cancer (Kutos et al. 2003; Krupa 2008 ). Despite its many uses and benefits, it is only grown in a small area and crops are underutilized due to photosensitivity, insufficient yields, erratic flowering, long growth habit and consumer preferences for pod size, shape, colour and aroma (Vaijayanthi et al. 2018 ). Hyacinth bean is a predominantly self-pollinated vegetable crop with limited genetic diversity for the most significant economic attributes (Gangadhara et al. 2024 ). Collection and study of genetic diversity for morphological and yield traits across landraces is crucial for successful breeding and selection of certain traits (Parmar et al. 2013 ). It's difficult to determine if observed variability is hereditary or caused by environmental factors alone. Understanding heritability is crucial for selection-based development since it determines how a character will be handed down to future generations (Singh et al. 2019 ). D 2 statistical analysis is a useful method for assessing the degree of divergence across genotypes and biological populations at the genotypic level to choose better genotypes effectively. Studying the connections between attributes, especially yield and other tangible characteristics is crucial as yield is a complex character resulting from plant interactions (Singh et al. 2018 ). Olivoto and Nardino ( 2021 ) developed the multi-trait genotype-ideotype distance index (MGIDI). This unique multivariate selection index has been carefully built to solve the drawbacks of multiple traits. Unlike conventional techniques, the MGIDI takes into account the underlying connection between features and effectively picks all factors in the assessment process. The hyacinth bean is a commercial vegetable crop in south India but there are no studies available on the cultivation and assessment of hyacinth beans in the south Indian agroclimatic conditions. However, little research on this crop in the southern region of India has hindered advances in genetic improvement. As a result, the current study was done to assess genetic factors such as descriptive traits, correlation studies, clustering, PCA analysis and MGIDI for yield-attributing and three biochemical variables among extant hyacinth bean landraces and germplasm. The study aimed to characterise and identify the permitted lines and resources for further genetic improvement of the hyacinth bean. Materials and methods Experimental location The current investigation was carried out by conducting field experiments for two consecutive years during the summer season of 2021 and 2022, at the research farm of the Department of Vegetable Science, Horticultural College and Research Institute, Periyakulam, Tamil Nadu, India. Geographically, the experimental site was located between 10.13 0 N latitude and 77.59 0 E longitude and at 356 m above the mean sea level. Genetic materials The experimental material for this study comprised 19 landraces of hyacinth beans obtained from various local regions of South Indian states including Andhra Pradesh, Tamil Nadu, Karnataka and Kerala. The details of landraces, along with seed, flower, pod colour variations and source of collection were illustrated in Table 1 and Fig. 1 . Additionally, five commercial cultivars Arka Amogh, Arka Jay, Arka Vijay, Arka Sowmya and Arka Sambhram were collected from the Indian Institute of Horticultural Research (IIHR), Bengaluru, Karnataka, India. One variety, Co (Gb) 14, was obtained from Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu and another variety, IC636214 was obtained from the NBPGR Regional Research Station, Kerala. These seven cultivars are commercially cultivated by farmers under South Indian agroecological conditions and were used as checks in this study. Table 1 Sources and DUS characteristics of hyacinth bean germplasm used for the study S. No. Code of genotypes Source Longitude Latitude Flower colour Pod shape Pod colour Seed colour 1 PKM LP 01 Theni local 77°42ʹ22ʺE 9°86ʹ92ʺN White Intermediate Light green Brown 2 PKM LP 02 Appipatti local 77°37ʹ90ʺE 9°83ʹ47ʺN White Intermediate Light green Brown 3 PKM LP 03 Chinnamanur local 77°38ʹ49ʺE 9°84ʹ15ʺN White Intermediate Dark green Brown 4 PKM LP 04 Bodinayakanur local 77°35ʹ04ʺE 10°03ʹ24ʺN White Intermediate Light green Brown 5 PKM LP 05 Uthamapalayam local 77°32ʹ99ʺE 9°76ʹ62ʺN White Intermediate Light green Brown 6 PKM LP 06 Mayiladumparai local 77°50ʹ67ʺE 9°78ʹ80ʺN White Intermediate Light green Brown 7 PKM LP 07 Cumbum local 77°28ʹ53ʺE 9°73ʹ94ʺN White Intermediate Light green Brown 8 PKM LP 08 Kamatchipuram local 77°54ʹ67ʺE 10°11ʹ98ʺN Purple Curved Dark green Brown 9 PKM LP 11 Co (Gb) 14 TNAU 76°96ʹ28ʺE 11°00ʹ18ʺN White Intermediate Light green Brown 10 PKM LP 12 Pollachi local 77°00ʹ87ʺE 10°65ʹ88ʺN White Intermediate Dark green Brown 11 PKM LP 13 Erode local 77°35ʹ05ʺE 11°49ʹ05ʺN White Intermediate Light green Brown 12 PKM LP 15 Karur local 78°38ʹ28ʺE 10°82ʹ17ʺN White Intermediate Dark green Brown 13 PKM LP 16 Namakkal local 78°11ʹ86ʺE 11°30ʹ33ʺN White Intermediate Light green Brown 14 PKM LP 19 Walajapet local 79°36ʹ37ʺE 12°92ʹ54ʺN White Intermediate Dark green Brown 15 PKM LP 23 Kadapa local II 78°82ʹ35ʺE 14°47ʹ75ʺN White Intermediate Light green Brown 16 PKM LP 24 Chittoor local II 79°10ʹ75ʺE 13°21ʹ57ʺN White Intermediate Light green Cream 17 PKM LP 25 (Arka Amogh) IIHR, Bangalore 77°60ʹ41ʺE 12°93ʹ16ʺN White Intermediate Light green Cream 18 PKM LP 26 (Arka Vijay) IIHR, Bangalore 77°60ʹ41ʺE 12°93ʹ16ʺN White Intermediate Light green Brown 19 PKM LP 27 (Arka Jay) IIHR, Bangalore 77°60ʹ41ʺE 12°93ʹ16ʺN Pink Curved Light green Cream 20 PKM LP 28 (Arka Sowmya) IIHR, Bangalore 77°60ʹ41ʺE 12°93ʹ16ʺN White Intermediate Light green Cream 21 PKM LP 29 (Arka Sambhram) IIHR, Bangalore 77°60ʹ41ʺE 12°93ʹ16ʺN White Curved Dark green Brown 22 PKM LP 30 Madurai local 78°11ʹ40ʺE 9°92ʹ61ʺN White Intermediate Light green Brown 23 PKM LP 31 Kandamanur local 77°53ʹ57ʺE 9°94ʹ96ʺN White Intermediate Light green Brown 24 PKM LP 32 Kanavilaku local 77°60ʹ36ʺE 9°99ʹ62ʺN White Intermediate Light green Brown 25 PKM LP 34 IC 636214 NBPGR Regional station, Kerala 76°21ʹ46ʺE 10°52ʹ70ʺN White Intermediate Light green Cream 26 PKM LP 35 Kadamalaikundu local 77°42ʹ22ʺE 9°86ʹ92ʺN White Intermediate Dark green Brown Allocation of genotypes and data collection A randomized complete block design (RCBD) was used to study the genotypes of hyacinth beans during the summer seasons of 2021 and 2022. The experiment was conducted in 78 plots, each measuring about 2.5 × 2.5 meters. In each plot, twenty-five plants were allocated from each genotype in three replications. Before sowing, half of the nitrogen and the full doses of phosphate and potash were applied as a basal dosage. The remaining nitrogen was applied as a top dressing 30 days after sowing. Five plants from every plot were randomly labelled to monitor growth, yield and biochemical traits such as days to germination, germination percentage, plant height (cm), number of primary branches, days to first flowering, days to 50% flowering, number of racemes/plant, days to pod formation, number of seeds/pod, pod length (cm), pod width (cm), number of pods/plant, pod weight (g), protein content (%), fibre content (%), phenol content (mg/100 g), yield/plant (g) and yield/plot (kg) and their mean value of each genotype in every replication was determined. Biochemical assays Total proteins The protein content of pods were estimated by multiplying the amount of nitrogen (%) value. The kjeldahl method was used to assess the nitrogen content in the pods (AOAC 1960 ). Total phenols Total phenol content was estimated by using the method described by Sadasivam and Manickam ( 1992 ). One gram of sample was separated using 80% ethanol. The resulting mixture was centrifuged at 10,000 rpm for 20 min. The supernatant was evaporated until dry. The leftover substance was dissolved in 5 ml of distilled water. An aliquot (0.5 ml) was transferred in a test tube and filled to a volume of 3 ml with distilled water, followed by the addition of 0.5 ml Folin-Ciocalteau reagent and 20% Na 2 CO 3 (2 ml) after 3 minutes and thoroughly mixed. The test tubes were immersed in warm water for one minute and then cooled. Absorbance at 765 nm was recorded against a reagent blank. A standard curve was generated using various amounts of gallic acid and the phenol content of the test sample was calculated as mg/100 g of sample. Crude fibre The crude fibre content was determined using a methodology summarised by Sadasivam and Manickam ( 1992 ). One gram of sample was added to 100 ml of 1.25% H 2 SO 4 and heated for 30 minutes on a magnetic hot plate with continual stirring. The sample was then filtered through muslin cloth and rinsed with hot water to remove the acid. The residue was treated similarly with 1.25% NaOH and filtered before being rinsed with hot water. The resulting residue was rewashed with boiling 1.25% H 2 SO 4 , 50 ml water and 25 ml alcohol. After washing, the residue was placed in a crucible and baked in an oven at 130 ± 2 0 C for 2 hours. The sample was ultimately cooled in a desiccator before being weighed. The sample was then transferred to a muffle furnace at 600 0 C for 30 minutes to be ignited. Thereafter, the sample was cooled and weighed to determine the crude fibre content using the expression (Sadasivam and Manikam, 1992) $$\:\text{C}\text{r}\text{u}\text{d}\text{e}\:\text{f}\text{i}\text{b}\text{r}\text{e}\:\left(\text{%}\right)=\frac{\text{W}\text{e}\text{i}\text{g}\text{h}\text{t}\:\text{l}\text{o}\text{s}\text{s}\:\text{d}\text{u}\text{r}\text{i}\text{n}\text{g}\:\text{i}\text{g}\text{n}\text{i}\text{t}\text{i}\text{o}\text{n}}{\text{I}\text{n}\text{i}\text{t}\text{i}\text{a}\text{l}\:\text{w}\text{e}\text{i}\text{g}\text{h}\text{t}\:\text{o}\text{f}\:\text{t}\text{h}\text{e}\:\text{s}\text{a}\text{m}\text{p}\text{l}\text{e}}\times\:100$$ Assessment the prevalence of diseases and pests under epiphytic conditions Pod borer incidence (%): The total number of healthy and infested pods was recorded during each harvest. After the last harvest, the average number of pods in each replication was estimated by summarising all healthy and infected pods of each genotype (Mallikarjuna 2012). $$\:\text{P}\text{o}\text{d}\:\text{b}\text{o}\text{r}\text{e}\text{r}\:\text{i}\text{n}\text{c}\text{i}\text{d}\text{e}\text{n}\text{c}\text{e}\:\left(\text{%}\right)=\frac{\text{N}\text{u}\text{m}\text{b}\text{e}\text{r}\:\text{o}\text{f}\:\text{p}\text{o}\text{d}\text{s}\:\text{i}\text{n}\text{f}\text{e}\text{s}\text{t}\text{e}\text{d}\:\text{w}\text{i}\text{t}\text{h}\:\text{p}\text{o}\text{d}\:\text{b}\text{o}\text{r}\text{e}\text{r}}{\text{T}\text{o}\text{t}\text{a}\text{l}\:\text{n}\text{u}\text{m}\text{b}\text{e}\text{r}\:\text{o}\text{f}\:\text{p}\text{o}\text{d}\text{s}\:\text{h}\text{a}\text{r}\text{v}\text{e}\text{s}\text{t}\text{e}\text{d}\:\:}\:\times\:100$$ Bean mosaic virus incidence (%): In each genotype, bean mosaic virus incidence was visually assessed by observation of 25 randomly selected plants from each replication and plants were scored as either infected with mosaic or not under natural epiphytic conditions (Singh et al. 1992 ). The incidence of mosaic disease infestation was then computed as the percentage of plants exhibiting symptoms as follows, $$\:\text{B}\text{e}\text{a}\text{n}\:\text{m}\text{o}\text{s}\text{a}\text{i}\text{c}\:\text{v}\text{i}\text{r}\text{u}\text{s}\:\text{i}\text{n}\text{c}\text{i}\text{d}\text{e}\text{n}\text{c}\text{e}\:\left(\text{%}\right)=\frac{\text{N}\text{u}\text{m}\text{b}\text{e}\text{r}\:\text{o}\text{f}\:\text{p}\text{o}\text{d}\text{s}\:\text{i}\text{n}\text{f}\text{e}\text{s}\text{t}\text{e}\text{d}\:\text{w}\text{i}\text{t}\text{h}\:\text{m}\text{o}\text{s}\text{a}\text{i}\text{c}\:\text{s}\text{y}\text{m}\text{p}\text{t}\text{o}\text{m}\text{s}}{\text{T}\text{o}\text{t}\text{a}\text{l}\:\text{n}\text{u}\text{m}\text{b}\text{e}\text{r}\:\text{o}\text{f}\:\text{p}\text{l}\text{a}\text{n}\text{t}\text{s}\:\text{o}\text{b}\text{s}\text{e}\text{r}\text{v}\text{e}\text{d}}\:\times\:100$$ Statistical analysis The data recorded on different parameters were subjected to statistical analysis for estimation of various genetic parameters and to find out the degree of association among different characters and their contribution to the pod yield. Principal component analysis and cluster analysis were performed in XLStat 2020 software. The descriptive statistical analysis and Pearson correlation were analysed by using GRAPES software. The MGIDI analysis was computed by using the RStudio 4.4.1 version. Result and Discussion Mean performance of morphological and biochemical traits The pooled data analysis of two years (2021 and 2022) morphological, quality and yield components of the bush type of hyacinth bean germplasms revealed substantial genetic and morphological variations (Fig. 2 ), which is a pre-requisite for the selection of landraces for hyacinth bean improvement programme. The minimum days (4.00) to germination in PKM LP 01, PKM LP 06 and PKM LP 16, whereas the maximum days taken in PKM LP 30 (7.50). Concerning plant height, the highest value was noticed in PKM LP 02 (76.75 cm) genotype, followed by PKM LP 27 (75.95 cm), whereas the lowest plant height was reported in PKM LP 07 (44.90 cm). The differences in plant growth may be due to genetic variability within the genotypes or it may be due to the environmental effects (Reddy et al. 2023 ). Among the genotypes, the maximum (6.76) number of branches was obtained in PKM LP 26 (Arka Vijay), followed by PKM LP 11 (5.20). In contrast, the lowest number of primary branches was notified in PKM LP 06 (4.16). 26 hyacinth bean genotypes showed the maximum variations in branching patterns, plant stature and flower colour (Fig. 3 ). Considering the days to first flowering, early flowering was observed in PKM LP 06 (38.40 days) followed by PKM LP 03 (39.20 days), whereas the maximum number of days to first flowering in PKM LP 35 (53.43 days) and this genotype considered as late flowering type. It concerned days to 50% flowering, minimum days taken in PKMLP 03 (45.20 days), followed by PKM LP 01 ((46.23 days) and maximum days taken in PKM LP 35 (58.83 days). The maximum number of racemes with a value of 6.93 was reported in PKM LP 08, followed by PKM LP 02 (6.53). PKM LP 11 genotype took fewer days (44.50 days) for pod formation, followed by PKM LP 08 (44.61 days), whereas the maximum duration was observed for the formation of pods in the PKM LP 35 genotype (57.23 days) (Table 2 ). Table 2 Morphological characterization of hyacinth bean genotypes S. No. Code of genotypes Days to germination Germination percentage (%) Plant height (cm) Number of primary branches Days to first flowering Days to 50% flowering Number of racemes/plant Days to pod formation Number of seeds/pod 1 PKM LP 01 4.00 g 89.20 a-c 64.00 cd 4.26 k-m 40.13 l-n 46.23 hi 4.63 m 47.51 e-g 3.20 h 2 PKM LP 02 4.50 f 83.30 e-j 76.75 a 4.90 cd 43.40 g-i 57.30 ab 6.53 b 48.43 c-f 4.26 c 3 PKM LP 03 6.00 c 81.20 h-l 50.25 ij 4.63 cd 39.20 mn 45.20 i 5.13 kl 44.76 h 4.33 bc 4 PKM LP 04 5.00 e 79.10 j-n 62.30 de 4.23 lm 42.30 i-k 54.16 c-e 4.50 m 48.53 c-f 3.23 gh 5 PKM LP 05 5.50 d 81.60 g-l 55.50 gh 4.60 e-h 41.23 j-i 51.43 g 5.90 de 45.50 gh 4.36 bc 6 PKM LP 06 4.00 g 75.50 n 65.40 cd 4.16 m 38.40 n 48.32 h 4.13 n 48.70 c-f 3.21 h 7 PKM LP 07 5.50 d 85.70 c-g 44.90 k 4.46 g-k 44.33 e-h 54.26 c-e 4.40 m 49.20 c-f 4.46 a-c 8 PKM LP 08 4.50 f 87.30 b-e 70.55 b 4.96 c 41.56 i-l 51.50 g 6.93 a 44.61 h 4.56 a 9 PKM LP 11 (Co (Gb) 14) 6.50 b 90.40 ab 73.80 a 5.20 b 41.30 j-l 46.26 hi 6.33 bc 44.50 h 4.51 ab 10 PKM LP 12 5.00 e 83.90 d-i 69.35 b 4.60 e-h 46.40 cd 58.80 a 5.26 i-k 50.23 cd 4.46 a-c 11 PKM LP 13 5.86 c 79.98 i-m 48.88 j 4.66 e-g 45.63 c-f 51.53 fg 5.60 fg 49.73 c-e 4.30 c 12 PKM LP 15 6.50 b 84.09 d-i 66.00 c 4.30 j-m 45.69 c-f 52.33 e-g 4.43 m 50.90 c 3.33 e-h 13 PKM LP 16 4.00 g 82.29 f-k 55.75 gh 4.70 ef 46.16 c-e 54.46 c-e 5.76 ef 50.50 cd 3.43 d-g 14 PKM LP 19 5.50 d 86.50 b-f 65.25 cd 4.33 i-m 42.83 h-j 53.63 d-g 3.80 o 47.23 e-g 3.21 h 15 PKM LP 23 6.00 c 77.70 l-n 57.00 g 4.53 f-i 44.23 f-h 55.20 b-d 5.16 j-l 49.21 c-f 3.40 d-h 16 PKM LP 24 6.50 b 76.60 mn 60.75 ef 4.33 i-m 50.30 b 52.10 e-g 4.93 l 54.53 b 3.46 d-f 17 PKM LP 25 (Arka Amogh) 5.50 d 78.50 k-n 58.75 fg 4.50 f-j 46.60 k-m 54.33 c-e 5.53 f-h 50.30 cd 3.30 f-h 18 PKM LP 26 (Arka Vijay) 4.50 f 91.98 a 70.07 b 6.76 a 42.52 h-j 56.50 a-c 6.13 cd 47.20 e-g 4.53 ab 19 PKM LP 27 (Arka Jay) 6.50 b 85.50 c-h 75.95 a 4.90 cd 43.33 g-i 53.10 d-g 6.40 b 48.71 c-f 4.30 c 20 PKM LP 28 (Arka Sowmya 5.50 d 79.30 j-n 67.45 bc 4.40 h-l 40.60 k-m 52.26 e-g 6.06 d 56.23 ab 3.42 d-g 21 PKM LP 29 (Arka Sambhram) 6.00 c 84.20 d-i 64.30 cd 4.76 de 44.86 d-g 54.13 c-f 5.33 h-k 48.13 d-f 3.60 d 22 PKM LP 30 7.50 a 79.40 j-n 53.25 hi 4.33 i-m 42.43 h-k 53.33 c-e 5.43 g-i 47.10 fg 3.23 gh 23 PKM LP 31 5.00 e 86.70 b-e 65.30 cd 4.53 f-i 47.33 c 56.36 a-c 5.36 g-k 51.00 c 3.46 d-f 24 PKM LP 32 6.00 c 84.30 d-i 48.25 j 4.60 e-h 46.20 c-e 54.40 c-e 5.40 g-j 50.53 cd 3.53 de 25 PKM LP 34 (IC 636214) 6.50 b 87.80 b-d 56.75 g 4.50 f-j 43.13 g-j 53.53 d-g 5.60 fg 48.51 c-f 3.43 d-g 26 PKM LP 35 5.00 e 89.40 a-c 67.30 bc 4.56 e-h 53.43 a 58.83 a 4.63 m 57.23 a 3.46 d-f SED (±) 0.12 1.27 1.80 0.06 0.70 0.91 0.09 0.71 0.06 CD at 5% 0.33 3.62 5.12 0.17 2.00 2.57 0.25 2.02 0.17 Note: Means with the different superscript letters are statistically different at p > 0.05 based on Tukey’s test All 26 hyacinth bean genotypes had maximum variations concerning pod shape, seed coat and pod colour (Figs. 4 and 5 ). PKM LP 08 elite genotype had more seeds/pod (4.56) and also similar results were obtained in PKM LP 26 (4.53) and PKM LP 11 (4.51). Pod length differed considerably among all genotypes which was highest in PKM LP 11 (8.56 cm), followed by Arka Jay (8.40 cm) and short pod length was noticed in PKM LP 06 (5.80 cm). The maximum pod width was obtained in PKM LP 06 (1.80 cm) and the minimum pod length was noticed in PKM LP 19 with the value of 1.06 cm. PKM LP 26 genotype had more pods/plant with a value of 39.66, followed by PKM LP 11 (38.45) and less number pods were observed in PKM LP 15 (24.19). The maximum yield/plant (1.32 g) yield/plot (7.32 kg) was exhibited in PKM LP 11 followed by PKM LP 26 (1.30 g). The maximum protein content (21.78%), fibre content (1.32%) and maximum phenols (7.32 mg/100 g) content were reported in the PKM LP 11 genotype (Table 3 ). The current findings are the results of Kushwah et al. ( 2021 ) for phenological traits, Srungarapu et al. ( 2022 ) for the agronomic, yield traits in chickpeas, Mohan et al. ( 2014 ), Gangadhara et al. ( 2024 ) in dolichos bean and Reddy et al. ( 2022 ), Reddy and Dhathri ( 2023 ) in cucumber for the quality traits. Table 3 Mean performance of hyacinth bean genotypes for yield-related and biochemical traits S. No. Code of genotypes Pod length (cm) Pod width (cm) Number of pods/plant Pod weight (g) Protein content (%) Fibre content (%) Phenol content (mg/100 g) Yield/plant (g) Yield/plot (kg) 1 PKM LP 01 6.36 lm 1.18 r 26.13 lm 3.07 jk 81.25 no 2.14 m 17.31 i-k 1.12 k-n 5.25 jk 2 PKM LP 02 7.83 bc 1.56 d 36.00 cd 3.48 c-f 126.29 d 3.37 e 19.59 b-d 1.25 b-d 7.25 a 3 PKM LP 03 6.85 f-i 1.31 i-o 26.00 lm 3.43 c-g 90.28 lm 2.43 kl 17.76 hi 1.24 c-e 5.29 jk 4 PKM LP 04 6.13 mn 1.23 p-r 27.00 j-l 2.73 l 75.60 p 2.05 m 17.25 i-k 1.09 mn 5.15 jk 5 PKM LP 05 7.35 de 1.30 l-o 27.56 jk 3.49 b-e 98.20 jk 2.55 k 18.67 e-g 1.14 i-m 5.32 i-k 6 PKM LP 06 5.80 o 1.80 a 26.85 kl 3.03 k 85.33 mn 2.13 m 16.76 j-l 1.10 l-n 5.03 kl 7 PKM LP 07 6.80 g-i 1.36 i-l 26.38 k-m 3.49 b-e 93.67 kl 2.45 kl 19.54 b-e 1.26 bc 6.08 c-e 8 PKM LP 08 8.05 b 1.68 b 37.15 c 3.47 c-f 129.58 cd 3.67 bc 16.97 i-k 1.28 a-c 6.50 b 9 PKM LP 11 Co (Gb) 14 8.56 a 1.53 de 38.45 b 3.55 bc 138.94 b 3.7 b 21.78 a 1.32 a 7.32 a 10 PKM LP 12 7.05 e-h 1.24 o-q 30.51 fg 3.36 e-i 105.45 gh 2.86 hi 19.23 c-f 1.23 c-f 6.43 b 11 PKM LP 13 7.15 ef 1.29 m-p 35.40 d 3.54 b-d 128.31 cd 3.01 fg 17.65 h-j 1.25 b-d 5.59 g-i 12 PKM LP 15 5.86 no 1.10 s 24.19 n 3.24 hi 79.47 op 2.08 m 16.09 l 1.03 o 4.32 m 13 PKM LP 16 6.56 i-l 1.20 qr 30.18 fg 3.36 e-i 104.28 g-i 3.05 f 18.26 gh 1.18 f-j 5.89 ef 14 PKM LP 19 6.15 mn 1.06 s 25.44 m 3.21 ij 83.15 no 2.09 m 16.43 kl 1.07 no 4.76 l 15 PKM LP 23 7.10 e-g 1.45 fg 32.85 e 3.33 e-i 113.48 f 2.91 gh 19.87 bc 1.22 c-g 5.63 f-h 16 PKM LP 24 6.68 i-l 1.43 f-h 27.37 j-l 3.45 c-f 130.97 cd 3.46 de 19.36 c-f 1.19 e-i 6.03 de 17 PKM LP 25 (Arka Amogh) 6.39 k-m 1.48 ef 34.83 d 3.42 c-g 120.11 e 3.13 f 19.41 b-f 1.23 c-f 6.28 b-d 18 PKM LP 26 (Arka Vijay) 8.03 b 1.58 cd 39.66 a 4.08 a 163.56 a 3.92 a 19.39 c-f 1.30 ab 7.35 a 19 PKM LP 27 (Arka Jay) 8.40 a 1.63 bc 35.60 d 3.64 b 132.90 c 3.56 cd 19.78 b-d 1.28 a-c 6.53 b 20 PKM LP 28 (Arka Sowmya 7.65 h-j 1.32 k-n 30.95 fg 3.27 g-i 103.43 g-j 2.75 ij 19.89 bc 1.26 bc 6.37 bc 21 PKM LP 29 (Arka Sambhram) 7.03 e-h 1.42 f-i 28.85 hi 3.40 c-h 101.87 h-j 2.78 h-j 20.32 b 1.27 a-c 6.43 b 22 PKM LP 30 6.71 i-k 1.38 h-k 29.76 gh 3.32 f-i 99.94 ij 2.68 j 19.35 c-f 1.17 g-k 5.37 h-j 23 PKM LP 31 6.78 g-j 1.35 j-m 27.31 j-l 3.38 d-h 94.38 kl 2.34 l 19.72 b-d 1.15 h-l 6.30 b-d 24 PKM LP 32 6.45 j-m 1.39 g-j 31.21 f 3.41 c-g 107.21 g 2.79 h-j 18.60 fg 1.13 j-m 6.01 de 25 PKM LP 34 (IC 636214) 6.58 i-l 1.27 n-p 28.32 ij 3.39 c-h 100.23 h-j 2.75 ij 18.89 bc 1.20 d-h 5.83 e-g 26 PKM LP 35 6.75 h-j 1.38 h-k 32.89 e 3.41 c-g 115.21 ef 3.02 fg 17.65 h-j 1.16 h-k 5.13 jk SED (±) 0.09 0.02 0.46 0.05 0.29 0.02 0.11 1.52 0.09 CD at 5% 0.26 0.05 1.32 0.15 0.81 0.06 0.30 4.33 0.27 Note: Means with the different superscript letters are statistically different at p > 0.05 based on Tukey’s test Descriptive parameters of hyacinth bean genotypes The assessment of variability parameters revealed a tremendous amount of variation among the genotypes for different characters. The GCV and PCV values provide insight into the magnitude of genetic variation. The heritability assessed in conjunction with estimates of genetic advance indicates genetic gains in the following generation or the change in average values between generations. The estimates of GCV, PCV, heritability and genetic advance of pooled data analysis are presented in Table 4 . Table 4 Descriptive parameters for 18 characters in 26 hyacinth bean genotypes Traits Genotypic variance Phenotypic variance Environmental variance PCV (%) GCV (%) Heritability (%) Genetic advance as % mean Days to germination 0.83 0.85 0.02 16.78 16.56 97.4 33.66 Germination percentage 18.14 23.27 5.12 5.78 5.10 78.0 9.28 Plant height (cm) 73.83 77.18 3.35 14.15 13.84 95.7 27.90 Number of primary branches 0.24 0.26 0.01 10.88 10.62 95.3 21.36 Days to flowering 10.88 11.90 1.03 7.85 7.50 91.4 14.77 Days to 50% flowering 11.71 13.56 1.85 6.94 6.45 86.3 12.34 Number of racemes/plant 0.61 0.63 0.02 14.78 14.56 97.0 29.53 Days to pod formation 9.39 11.15 1.76 6.79 6.23 84.2 11.77 Number of seeds/pod 0.28 0.29 0.01 14.23 13.93 95.8 28.08 Pod length (cm) 0.54 0.58 0.03 10.90 10.58 94.1 21.13 Pod width (cm) 0.03 0.03 0.01 12.95 12.74 96.9 25.84 Number of pods/plant 19.26 19.80 0.54 14.52 14.32 97.3 29.10 Pod weight (g) 0.05 0.06 0.01 7.22 6.78 88.3 13.13 Protein content (%) 1.79 2.03 0.23 7.63 7.17 88.5 13.89 Fibre content (%) 0.01 0.01 0.01 6.82 6.29 85.0 11.95 Phenol content (mg/100g) 0.60 0.62 0.03 13.39 13.09 95.5 26.34 Yield/plant (g) 450.53 460.78 10.25 19.91 19.69 97.8 40.10 Yield/plot (kg) 0.30 0.30 0.01 19.36 19.17 98.0 39.09 The PCV ranged from 5.78–19.91% and the maximum was reported in yield/plant (19.91%) and the lowest PCV was observed in the case of germination percentage (5.78%). The genotypes show a wide range of GCV for growth, yield and biochemical traits and it ranges from 5.1–19.69%. Days to germination, plant height, number of primary branches, number of racemes/plant, number of seeds/pod, pod length, pod width, pods/plant, phenol content, yield/plant and yield/plot exhibit moderate PCV and GCV indicates a moderate amount of variation. The moderate estimates of PCV and GCV have been reported previously by Patel et al. ( 2022 ) for pod length, pod weight and number of pods/plant, indicating low response to selection for these traits. Likewise, moderate to high estimates of GCV were reported in another study by Kumar et al. ( 2021 ) and Gamit et al. ( 2020 ). The lowest GCV and PCV values were noted for the traits viz. , days to first flowering, days to 50% flowering, days to pod formation, pod weight, protein content and fibre content. GCV and PCV are not much different in the majority of traits, revealing that the environment has less influence. The slight variations between PCV and GCV suggested that the heritable component is necessary for their expression and also the selection of genotypes. In the present study heritability ranges from 78% in germination percentage to 98% in yield/plot. High heritability estimates were recorded for yield/plot (98%) followed by yield/plant (97.8%), days to germination (97.4%), pods/plant (97.3%), number of racemes/lant (97%), pod width (96.9%) shows less impact environment on these characters. High heritability was observed in all the characters and a strong influence of genetic constitution on character expression; from a breeding perspective, such traits are considered for selection. These findings suggest the implication of selection procedures for the improvement of dolichos bean (Lahari et al. 2022 ; Thasneem et al. 2022 ). GA as per cent of the mean ranged from 9.28 in germination percentage to 40.10 in yield/plant. In this study high values of GA as a per cent of the mean were observed viz. , yield/plant (40.10), yield/plot (39.09), and days to germination (33.66). During the present investigation moderate values of GA as a per cent of the mean were noticed in days for first flowering (14.77), days to 50% flowering (12.34) and days to pod formation (11.77). High genetic advance was also documented in Indian beans by Thasneem et al. ( 2022 ), Afsan and Roy ( 2020 ) and Peer et al. ( 2018 ) for days to first harvest, length of inflorescence, number of flowers/plant, number of pods/plant, In the present study maximum traits revealed high heritability values accompanied with high GA as per cent of mean, because additive gene effects mainly control the expression of these attributes, phenotypic performance-based selection will be useful in the future for improving these characters. Pearson correlation analysis The correlation analysis revealed positive as well as negative correlations among various morphological and yield-related traits (Fig. 6 ). In the present investigation, yield/plant showed a highly significant positive correlation with pods/plant (0.89), Pod width (0.82), number of primary branches (0.77), pod length (0.76), number of racemes/plant (0.70), pod width (0.58) and number of seeds/pod (0.56) indicating that these attributes strongly influenced the yield/plant of hyacinth bean. Therefore, even though direct selection for improvement has not been done for the yield character, methods of selection for the improvement of one character inevitably result in the improvement of another trait as well. Plant height showed a significant and positive correlation with pod length (0.46) and pods/plant (0.40). The number of primary branches noticed that significant and positive correlation with all the attributes except days to germination, plant height, days to first flowering, days to 50% flowering, days to pod formation and pod width. Days to first flowering showed a positive and significant correlation with days to 50% flowering (0.65) and days to pod formation (0.69). Days to pod formation exhibited a highly positive and significant association with days to first flowering. The number of racemes/plant showed that significant association with primary branches (0.56), number of seeds/pod (0.58), pod length (0.84), pod width (0.46), pods/plant (0.76) and pod weight (0.59), rest of the traits shown a non-significant correlation. The number of seeds/pod recorded that positive and significant association with the number of primary branches (0.60), number of racemes/plant (0.58), pod length (0.75), pods/plant (0.53) and pod weight (0.67), It shows that negative association with days to pod formation (-0.43). This indicated that there was a high degree of interrelationship between the yield/plant and other yield attributes at the genotypic level. The positive association for the related traits has been depicted earlier by Chaitanya et al. ( 2014 ), Thorat et al. ( 2020 ) and Attar et al. ( 2022 ) in hyacinth bean. The positive association among the studied traits indicated the scope for simultaneous improvement of these traits in a breeding programme. The results indicate that hyacinth bean yield potential can be increased by applying the strong selection to plant height, number of racemes/plant, pods/plant, seeds/pod, pod weight, pod length and pod width and days to 50% flowering. These results indicate the true genetic relationship between these traits and direct selection through these traits will be rewarding to improve the yield. Similar types of findings were also reported by Geetha and Divya ( 2021 ) and Bansod et al. ( 2021 ) in dolichos bean. Clustering of hyacinth genotypes Depending on the proportion of D 2 estimates 26 genotypes were classified into five clusters. The distribution of various genotypes in each cluster is shown in Table 5 and Fig. 7 . Cluster IV possesses the most genotypes (9), followed by cluster III (7), cluster I (5), cluster II (4) and cluster V (1). Each cluster represented the greatest variance in the contribution of various attributes, reflected in the profile plot (Fig. 8 ). Arka Vijay is the only genotype in cluster V and all the traits positively contributed to this cluster V, especially the number of primary branches, pod weight and yield/plant followed by cluster II. Among all the clusters, cluster I genotypes had fewer values in each trait followed by cluster III. So, it is recommended to use clustering or grouping of germplasm based on both morphological and yield traits, since this sort of clustering contributes to the selection of genotypes that have superior yield. This type of clustering will be useful in identifying the superior genotypes in an extensive population. These findings are consistent with the findings of Gangadhara et al. ( 2014 ) and Haralayya et al. ( 2017 ), who examined D 2 clustering in french beans and Gangadhara et al. ( 2024 ) and Kiran et al. ( 2024 ) in dolichos beans. Table 5 Grouping of 26 bush-type hyacinth bean genotypes into five clusters based on cluster analysis S. No. Clusters No of genotypes Name of genotypes 1 I 5 PKMLP 1, PKMLP 4, PKMLP 6, PKMLP 15, PKMLP 19 2 II 4 PKMLP 2, PKMLP 4, PKMLP 11 [Co (Gb)14], PKMLP 27 (Arka Jay) 3 III 7 PKMLP 3, PKMLP 5, PKMLP 7, PKMLP 13, PKMLP 30, PKMLP 32, PKMLP 34 4 IV 9 PKMLP 12, PKMLP 16, PKMLP 23, PKMLP 24, PKMLP 25 (Arka Amogh), PKMLP 28 (Arka Sowmya), PKMLP 29 (Arka Sambhram), PKMLP 35 5 V 1 PKMLP 26 (Arka Vijay) Principal component analysis (PCA) in hyacinth bean genotypes The present study demonstrates the different variables contribute to a grouping of genotypes based on the PCA. The eigenvalues are associated with each PC, while the cumulative variability rises and illustrated as a scree plot (Fig. 9 ). A total of eighteen components are depicted as a scree plot showing the 100% genetic variation. The first 5 PCs had recorded more than one eigenvalue and accounted for 82.62% of the total variance among 26 genotypes. The PC1 accounts for 47.52% of the total variance, followed by PC2 (13.60%), PC3 (9.12%) and PC4 (7.38%), indicating the presence of significant variability among genotypes for the variables under consideration. The individual eigenvector value of different variables reveals their contribution towards the total variation of that particular PC (Table 6 ). The traits that contributed positively to PC1 were pod yield/plot (0.32), followed by yield/plant (0.31), pod length (0.31), pods/plant (0.30), number of racemes/plant (0.29), pod weight (0.28) whereas the traits that contributed negatively to PC1 were days to first flowering (-0.01) and days to pod formation (-0.07. As a result, early yield will benefit greatly through selection for these traits. This demonstrates that PC1 generated a significant amount of variability due to its early emergence as well as yield contributing features (Fig. 10 ). The factors that contributed favourably to PC2 were days to first flowering (0.59), days to pod formation (0.53) and days to 50% flowering (0.50) whereas, negative impact characteristics such as the number of seeds/pod (-0.19), pod length (-0.10), pod width (-0.09) and number of primary branches (-0.03). The components with eigenvalues greater than one are deemed as primary or significant components because they account for a high share of the variance. Plant breeders usually select such components for plant selection. Table 6 Factor loadings of yield and its components traits and biochemical traits for the first five major principal components Variables PC1 PC2 PC3 PC4 PC5 Days to germination 0.01 0.05 0.61 0.24 0.26 Germination percentage 0.13 -0.02 -0.41 0.50 0.33 Plant height (cm) 0.14 0.02 -0.43 -0.32 0.51 Number of primary branches 0.28 -0.03 -0.23 0.23 -0.17 Days to first flowering -0.01 0.59 0.02 0.14 -0.09 Days to 50% flowering 0.05 0.50 -0.17 0.05 0.02 Number of racemes/plant 0.29 -0.07 0.07 -0.11 0.08 Days to pod formation -0.07 0.53 0.02 -0.20 0.03 Number of seeds/pod 0.25 -0.19 -0.01 0.26 -0.16 Pod length (cm) 0.31 -0.10 0.04 -0.01 0.21 Pod width (cm) 0.20 -0.09 0.00 -0.49 -0.28 Number of pods/plant 0.30 0.06 -0.07 -0.13 -0.14 Pod weight (g) 0.28 0.08 0.05 0.33 -0.24 Protein content (%) 0.22 0.10 0.37 -0.06 0.43 Fibre content (%) 0.30 -0.05 0.20 -0.02 0.02 Phenol content (mg/100g) 0.31 0.04 0.01 -0.11 0.20 Yiel/plant (g) 0.31 0.13 0.03 -0.03 -0.23 Yield/plot (kg) 0.32 0.12 0.04 -0.07 -0.14 Per cent (%) of variance 47.52 13.60 9.12 7.38 5.00 A biplot was drawn between PC1 and PC2 to observe the relationship of variables and grouping of genotypes (Fig. 11 ). PKM LP 26 is a high yielder placed at the extreme right corner of the biplot, whereas PKM LP 4 and PKM LP 15 are a low yielding genotype placed at the extreme left corner of the biplot. The contrasting characters were placed in an opposite position. The outcome of PCA was consistent with the result of cluster analysis. These findings are consistent with previous research by Reddy et al. ( 2021 ) on French bean, Singh et al. ( 2021 ), Shibli et al. ( 2021 ) and Kumari et al. ( 2022 ) on dolichos bean, which examined the per cent variation and trait contribution of plant height, number of pods/plant, pod length, pod weight and pod yield to total diversity. Identification of superior genotypes based on MGIDI analysis Plant breeders aim to cumulate various suitable morphological traits in one genotype that finally leads to reaching superior performance. The MGIDI selection index was performed to identify the superior performance genotypes based on the multiple traits. Among 26 genotypes, four genotypes were identified through (MGIDI) and which are indicated in red colour. Four genotypes including PKM LP 13, PKM LP 26, PKM LP 27 and PKM LP 35 genotypes performed well for multiple traits and four factors, indicating significant potential for improving 18 measured traits simultaneously in a hyacinth bean breeding program (Fig. 12 ). Strengths and weaknesses of genotypes based on MGIDI factors Table 7 summarises the strengths and weaknesses of selected genotypes, as measured by each factor's contribution to the multi-trait genotype ideotype distance index (MGIDI). The genotypes associated with factor 1 (FA1), such as PKM LP 26 (Arka Vijay), demonstrate particular strengths in traits such as germination percentage, plant height, branches/plant, days to 50% flowering, number of seeds/pod, pod length, number of pods/plant, pod weight, yield/plant, yield/plot, phenol content and fibre content. On the other hand, genotypes PKM LP 35 linked to FA2, PKM LP 27 (Arka Jay) and PKM LP 13 genotypes are associated with FA3. Lastly, Factor 4 (FA4) with genotypes like PKM LP 35 and PKM LP 13 demonstrates strength in traits like the primary branches, days to first flowering and pod formation, seeds/pod, pods/plant, pod length, width and yield/plant. These insights on genotype strengths and weaknesses can help advise future breeding programs in terms of parent selection. These findings are similar to the prior study conducted on sorghum by Behera et al. ( 2024 ), guar by Benakanahalli et al. ( 2021 ), rice by Pallavi et al. ( 2024 ), and barley by Zali et al. (2023). The multi-trait genotype-ideotype distance index (MGIDI) was extremely effective in identifying improved hyacinth bean genotypes, resulting in acceptable improvements across numerous traits. The identified genotypes such as PKM LP 26 (Arka Vijay), PKM LP 35, PKM LP 27 (Arka Jay) and PKM LP 13 by MGIDI reveal their potential for commercial availability or use as vital breeding resources in hyacinth bean breeding improvement efforts. The detailed examination of strengths and weaknesses yielded useful insights, emphasising the importance of a superior hyacinth bean genotype with better quantitative traits. Table 7 Grouping of genotypes into 4 factors through MGIDI and its positively contributed traits S. No. Factors Genotypes Positively contributed traits 1 FA1 PKM LP 26 (Arka Vijay) Germination percentage, plant height, number of branches/plant, days to 50% flowering, number of seeds/pod, pod length, number of pods/plant, pod weight, yield/plant, yield/plot, phenol content and fibre content 2 FA2 PKM LP 35 Germination percentage, plant height, days to first flowering and 50% flowering and days to pod formation 3 FA3 PKM LP 27 (Arka Jay) and PKM LP 13 Days to germination, number of seeds/pod, number of pods/plant, pod weight, yield/plant, yield/plot and fibre content 4 FA4 PKM LP 35 and PKM LP 13 Number of primary branches/plant, days to first flowering and pod formation, number of seeds/pod, number of pods/plant, pod length, pod weight and yield/plant Bean common mosaic and pod borer incidence in hyacinth bean genotypes Identifying pest and disease resistance sources is the primary goal of the crop improvement programme. Pod borer and bean mosaic is a major constraint to the production and productivity of hyacinth beans. In this study, bean common mosaic and pod borer incidence showed significant variation between 26 germplasms (Table 8 ). PKM LP 04 exhibited higher pod borer incidence (33.82%) followed by PKM LP 19 (25.20%) and less pod borer (13.20%) incidence was noted in PKM LP 02. The highest bean mosaic virus incidence (21.66%) was found in PKM LP 15, followed by PKM LP 19 (20.97%) and mosaic virus incidence (8.25%) lower in PKM LP 35. Table 8 Pod borer and bean mosaic incidence in hyacinth bean genotypes S. No. Code of Genotypes Pod borer incidence (%) Rate of infestation Bean mosaic virus incidence (%) Rate of infestation 1 PKM LP 01 22.31 Moderate 19.08 Moderate susceptible 2 PKM LP 02 13.20 Moderate 9.34 Moderate resistant 3 PKM LP 03 21.09 Moderate 18.74 Moderate susceptible 4 PKM LP 04 33.82 High 19.33 Moderate susceptible 5 PKM LP 05 19.39 Moderate 18.54 Moderate susceptible 6 PKM LP 06 23.53 Moderate 19.38 Moderate susceptible 7 PKM LP 07 19.05 Moderate 13.42 Moderate resistant 8 PKM LP 08 17.54 Moderate 10.72 Moderate resistant 9 PKM LP 11 Co (Gb) 14 13.29 Moderate 11.14 Moderate resistant 10 PKM LP 12 17.38 Moderate 12.65 Moderate resistant 11 PKM LP 13 22.48 Moderate 19.22 Moderate susceptible 12 PKM LP 15 24.98 Moderate 21.66 Moderate susceptible 13 PKM LP 16 20.49 Moderate 16.65 Moderate susceptible 14 PKM LP 19 25.20 Moderate 20.97 Moderate susceptible 15 PKM LP 23 19.09 Moderate 17.67 Moderate susceptible 16 PKM LP 24 19.87 Moderate 13.54 Moderate resistant 17 PKM LP 25 (Arka Amogh) 19.32 Moderate 13.31 Moderate resistant 18 PKM LP 26 (Arka Vijay) 13.93 Moderate 10.86 Moderate resistant 19 PKM LP 27 (Arka Jay) 14.94 Moderate 10.45 Moderate resistant 20 PKM LP 28 (Arka Sowmya 20.32 Moderate 17.06 Moderate susceptible 21 PKM LP 29 (Arka Sambhram) 19.32 Moderate 14.09 Moderate resistant 22 PKM LP 30 19.54 Moderate 17.85 Moderate susceptible 23 PKM LP 31 19.91 Moderate 13.43 Moderate resistant 24 PKM LP 32 21.54 Moderate 15.98 Moderate susceptible 25 PKM LP 34 (IC 636214) 20.89 Moderate 17.89 Moderate susceptible 26 PKM LP 35 19.50 Moderate 8.25 Moderate resistant Mean 19.65 15.51 SED (±) 0.40 0.47 CD at 5% 1.13 1.35 Conclusion Study of genetic diversity of hyacinth bean landraces for yield and its attributing traits is crucial for their efficient use in hyacinth bean breeding improvement programme. In this study, 26 hyacinth bean germplasms including 19 landraces and 7 commercial varieties were assessed for eighteen traits. Among 26 genotypes, PKM LP 11 and PKM LP 26 had the highest yield and the superior yield-related attributes. substantial heritability estimates, along with substantial genetic progress as a percentage of the mean, showed that the qualities under research are mostly influenced by additive gene action and phenotypic selection will be desirable. The number of primary branches, racemes/plant, pods/plant, pod length, width and weight all had a positive impact on the yield/plant, indicating that these are most considerable traits for increasing yield in hyacinth bean. Heritability estimates for yield/plot were highest, followed by yield/plant, days to germination, pods/plant, number of racemes/plant, pod width and number of seeds/pod, indicating that environment has less of an impact on these characters. PKM LP 02 and PKM LP 35 landraces are reported as highly resistant against to pod borer and bean mosaic virus, respectively. The multi-trait genotype-ideotype distance index (MGIDI) was highly successful in identifying more accurate hyacinth bean genotypes, with acceptable improvements across a wide range of characteristics. In the current study, two genotypes including PKM LP 26 (Arka Vijay), PKM LP 27 (Arka Jay) and two landraces such as PKM LP 35 and PKM LP 13 were found by MGIDI analysis and demonstrated their potential for commercial availability or usage as essential breeding resources in hyacinth bean breeding improvement efforts. These two landraces were shown to perform better and they can be employed as possible donors for enhancing yield and agro-morphological features in future breeding programs. Declarations Conflict of interest All the authors declare that there are no conflicts of interest to disclose. Consent to participate All authors have given consent to participate. Consent for publication All authors have given consent to publication. Funding The work was supported by Horticultural College and Research Institute, Periyakualm, Tamil Nadu, India Data availability Raw data are available upon request from the corresponding author. Author contributions MH designed the field layout and MH. SKR collected genotypes from various regions of south Indian states. SKR and KH helped in data analysis, table formatting and manuscript writing. The first draft of the manuscript was written by MH, SKR and KH. KV and SSR commented and corrected on previous versions of the manuscript. All authors read and approved the final manuscript. Acknowledgements The authors would like to acknowledge the Dean of Horticultural College and Research Institute, Periyakulam, Tamil Nadu, India for providing the necessary facilities. The authors, staff and students would like to thank the HC&RI, Periyakulam for providing all financial support for collections of genotypes from different regions of South India. References Afsan N, Roy AK (2020) Genetic variability, heritability and genetic advance of some yield contributing characters in lablab bean ( Lablab purpureus L. Sweet). J Bio-Sci 28:13–20. https://doi.org/10.3329/jbs.v28i0.44706 AOAC (1960) Official and tentative methods of analysis. 9th Edn. Association of official analytical chemists, Washington DC, pp 73 Attar SD, Bhavidoddi A, Gasti VD, Tirakannanavar S, Patil S, Yashavantakumar KH (2022) Correlation and path coefficient analysis in dolichos bean ( Lablab purpureus L). Pharma Innov 11(5):1625–1628 Bansod P, Bhalekar MN, Kshirsagar DB (2021) Path coefficient analysis of dolichos bean ( Lablab purpureus L.) genotypes. 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Czech J Genet Plant Breed 51:110–116. 10.17221/32/2015-CJGPB Shibli RMM, Golam RM, Islam AKM, Saikat MMH, Haque MM (2021) Genetic diversity of country bean ( Lablab purpureus ) genotypes collected from the coastal regions of Bangladesh. J Hortic Postharvest Res 4(2):219–230. https://doi.org/10.22077/JHPR.2020.3282.1135 Singh G, Sharma YR, Kaur L (1992) Methods of rating yellow mosaic virus of mung bean and urdu bean. J Plant Dis Res 7(1):1–6 Singh K, Gupta K, Tyagi V, Rajkumar S (2020) Plant genetic resources in India: management and utilization. Vavilov J Genet Breed 24(3):306–314. 10.18699/VJ20.622 Singh S, Bhatia R, Kumar R, Sharma K, Dash S, Dey SS (2018) Cytoplasmic male sterile and doubled haploid lines with desirable combining ability enhances the concentration of important antioxidant attributes in Brassica oleracea . Euphytica 214:207. https://doi.org/10.1007/s10681-018-2291-3 Singh S, Dey SS, Bhatia R, Kumar R, Sharma K, Behera TK (2019) Heterosis and combining ability in cytoplasmic male sterile and doubled haploid based Brassica oleracea progenies and prediction of heterosis using microsatellites. PLoS ONE 14:e0210772. https://doi.org/10.1371/journal.pone.0210772 Singh SP, Gepts P, Debouck DG (1991) Races of common bean ( Phaseolus vulgaris , Fabaceae). Econ Bot 45:379–396. https://doi.org/10.1007/BF02887079 Singh SR, Rajan S, Kumar D, Soni VK (2021) Genetic diversity assessment in dolichos bean ( Lablab purpureus L.) based on principal component analysis and single linkage cluster analysis. Legume Res 47(5):731–737 Srungarapu R, Mohammad LA, Mahendrakar MD, Chand U, Jagarlamudi Venkata R, Kondamudi KP, Nandigam S, Vemula A, Samineni S (2022) Genetic variation for grain protein, Fe and Zn content traits in chickpea reference set. J Food Compost Anal 114:104774. https://doi.org/10.1016/j.jfca.2022.104774 Thant AA, Teutscherova N, Vazquez E, Kalousova M, Phyo A, Singh RK, Lojka B (2020) On-farm rice diversity and farmers preferences for varietal attributes in Ayeyarwady Delta. Myanmar J Crop Improv 34(4):549–570. https://doi.org/10.1080/15427528.2020.1746457 Thasneem SN, Sreenivas M, Nagaraju K, Saidaiah P, Pandravada SR (2022) Variability, heritability (h 2 b) and genetic advance studies in dolichos bean ( Lablab purpureus L.) genotypes. Pharma innov 11(12):6005–6008 Thorat AR, Shinde KG, Bhalekar MN, Ranpise SA (2020) Correlation studies in different genotypes of dolichos bean ( Lablab purpureus L). J Pharmacogn Phytochem 9(6):1027–1029 Tindall HD (1983) Vegetables in the tropics. AVI Publishing Company, INC West Port, Connecticut, pp 302–303 Vaijayanthi PV, Ramesh S, Mohan RA, Mangala N, Ashwini M (2018) Identification and characterization of contrasting genotypes for productivity traits from a core set of dolichos bean germplasm. Int j chem stud 6(2):2946–2949 Yadav RK, Yadav DS, Rai N, Patel KK (2003) Prospects of horticulture in North Eastern region. Envis Bull Himal Ecol 11:10–25 Zali H, Pour-Aboughadareh A (2023) Identification of superior genotypes of barley for cultivation in the south regions of Fars province using MGIDI, FAI-BLUP indices. Plant Productions 46(3):335–351. https://doi.org/10.22055/ppd.2024.45295.2134 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6181502","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":425835644,"identity":"a094c7de-3427-492f-9a7c-dae6e9702e91","order_by":0,"name":"M. 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Horticultural University-College of Horticulture, Anantharajupeta 516105, Andhra Pradesh, India","correspondingAuthor":false,"prefix":"","firstName":"P.","middleName":"Syam Sundar","lastName":"Reddy","suffix":""}],"badges":[],"createdAt":"2025-03-08 02:11:37","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":true,"humanSubjectCaseReport":true,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6181502/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6181502/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78249528,"identity":"10fd5db1-186a-44b6-9bf6-05e10d81e5e0","added_by":"auto","created_at":"2025-03-11 09:50:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":708705,"visible":true,"origin":"","legend":"\u003cp\u003eHyacinth bean landraces collection sites from various local regions of Southern India\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6181502/v1/23cddf9bf715c306bc0b5321.png"},{"id":78249495,"identity":"233536fe-7220-4122-a9b7-06eebd7b0528","added_by":"auto","created_at":"2025-03-11 09:50:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3238285,"visible":true,"origin":"","legend":"\u003cp\u003ePlant morphology and pod variability in selected hyacinth bean germplasms\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6181502/v1/d52a95d3a4eb63d0acbf2894.png"},{"id":78249493,"identity":"152d9a11-73a5-4264-a275-d8708545a8ab","added_by":"auto","created_at":"2025-03-11 09:50:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":583836,"visible":true,"origin":"","legend":"\u003cp\u003eFlowering pattern and its colour variability in hyacinth bean germplasms\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6181502/v1/ccaefda1b62b82b3bc2f51c3.png"},{"id":78250975,"identity":"91135c83-a31a-4d98-b5e1-18ffc81118e3","added_by":"auto","created_at":"2025-03-11 09:58:38","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":261876,"visible":true,"origin":"","legend":"\u003cp\u003eSeed coat variability in 26 hyacinth bean genotypes\u003c/p\u003e","description":"","filename":"image4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6181502/v1/628b08ada9aba7e8b84988d6.jpeg"},{"id":78249579,"identity":"5cff9d79-c314-4e44-b31d-57f875c2fcba","added_by":"auto","created_at":"2025-03-11 09:50:48","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":308591,"visible":true,"origin":"","legend":"\u003cp\u003ePod shape and color variability of 26 hyacinth bean germplasms\u003c/p\u003e","description":"","filename":"image5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6181502/v1/f3ab616cc5c5b76cf2b81217.jpeg"},{"id":78250976,"identity":"11428351-56df-4ac5-8954-64a6fc7b39ae","added_by":"auto","created_at":"2025-03-11 09:58:39","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":190549,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelogram showing the relationship among 18 traits of 26 hyacinth bean genotypes; DFG: Days to germination; GP: Germination percentage; PH: Plant height; NPB: Number of primary branches; DFF: Days to first flowering; DTFPF: Days to 50% flowering; NRPP: Number of racemes/plant; DTPF: Days to pod formation; NSPP: Number of seeds/pod; PL: Pod length; PW: Pod width; PPP: Number of pods/plant; PWT: Pod weight; PC: Protein content; FC: Fibre content; PHC: Phenol content; YPLA: Yield/plant; YPLO: Yield/plot\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-6181502/v1/026792db7eb739b2d3100417.png"},{"id":78249578,"identity":"70428f1e-9ca9-4e10-8e74-5955a3e9d49a","added_by":"auto","created_at":"2025-03-11 09:50:48","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":82448,"visible":true,"origin":"","legend":"\u003cp\u003eDendrogram showing the relationship among 26 hyacinth bean genotypes\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-6181502/v1/2f14f030181f8ad75ede14bf.png"},{"id":78249501,"identity":"85d2f6c4-cc3c-4446-adb4-03f9195c36ce","added_by":"auto","created_at":"2025-03-11 09:50:39","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":66535,"visible":true,"origin":"","legend":"\u003cp\u003eProfile plot showing the variability patterns between 5 clusters\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-6181502/v1/69053ca3e0947c6695a6242d.png"},{"id":78250977,"identity":"1c6209c4-fcf6-4ae7-983b-ba59d7632540","added_by":"auto","created_at":"2025-03-11 09:58:39","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":25505,"visible":true,"origin":"","legend":"\u003cp\u003eScree plot for eigen values and cumulative variability explained by principal components in hyacinth bean genotypes\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-6181502/v1/81cfcc77194f61cee05234bd.png"},{"id":78249506,"identity":"a40988ab-8eaf-4c78-bfae-3cd8b735b0e7","added_by":"auto","created_at":"2025-03-11 09:50:39","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":48236,"visible":true,"origin":"","legend":"\u003cp\u003eContribution on the individual trait in first 8 major principal com\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-6181502/v1/2d9cadf8085c8df509dea742.png"},{"id":78249505,"identity":"f217420e-3c36-460a-b1ef-06e6c275a405","added_by":"auto","created_at":"2025-03-11 09:50:39","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":118099,"visible":true,"origin":"","legend":"\u003cp\u003ePCA biplot between PC1 (47.52%) and PC2 (13.60%) scores of hyacinth bean landraces and its variables\u003c/p\u003e","description":"","filename":"image11.png","url":"https://assets-eu.researchsquare.com/files/rs-6181502/v1/fd5950de64fdbc7dd42ecef5.png"},{"id":78251794,"identity":"a32b23c3-16e5-4fe8-81a4-f56e01018189","added_by":"auto","created_at":"2025-03-11 10:06:39","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":51742,"visible":true,"origin":"","legend":"\u003cp\u003eIdentified best landraces through MGIDI analysis and its strengths and weaknesses\u003c/p\u003e","description":"","filename":"image12.png","url":"https://assets-eu.researchsquare.com/files/rs-6181502/v1/2b3fba888dfe8e7f3e8e3795.png"},{"id":78253449,"identity":"24f3048c-4ac0-4b36-9ed7-86318e0f75ab","added_by":"auto","created_at":"2025-03-11 10:22:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7599286,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6181502/v1/04aa058d-1bae-4190-9339-88be9c475451.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eUnlocking the genetic diversity of bush hyacinth bean (Lablab purpureus var. typicus L.) landraces under South Indian agro-ecologies \u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePlant genetic resources (PGR\u0026rsquo;s) are the major genetic materials in any crop improvement programme especially for nutritional security (Singh et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The PGR\u0026rsquo;s include wild relatives, advanced breeding lines, modern cultivars, landraces and induced mutants (Salgotra and Chauhan \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Landraces are traditional specific crop resources that play a vital role in maintaining the sustainability of traditional agroecosystems, food and nutritional security (Puneeth et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These local ecotypes have varied morphological and less productive, but are generally extremely nutritious. Due to the adoptive evolution, landraces comprised a pool of genes for nutritive value and resistance to biotic and abiotic stresses (Palni et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Insufficient documentation, inadequate transmission of ethnobotanical significance, lack of interest among younger generations and ineffective policy intervention have resulted in poor conservation and use of landraces in plant breeding. Plant breeders have been endeavouring to document the on-farm conserving activities across the global level (Conversa et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Thant et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHyacinth bean (\u003cem\u003eLablab purpureus\u003c/em\u003e var. \u003cem\u003etypicus\u003c/em\u003e) is a versatile and ancient vegetable crop with 2n\u0026thinsp;=\u0026thinsp;22 chromosomes (She and Jiang, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), belonging to the Fabaceae family. It originated in India and distributed to South Asia, Southeast Asia, Africa and other tropical nations (Raghu et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Fresh pods of hyacinth beans are highly nutritious and comprise 86.1% moisture, 3.8% protein, 6.7% carbohydrates 0.7% fat, 0.9% minerals and 312 I.U. of vitamin A/100g of edible amount (Tindall \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1983\u003c/span\u003e). The seeds are used as vegetables in India, particularly in tribal areas (Dwivedi et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Seeds contain 15\u0026ndash;25% more protein than the pods (Gopalan et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Consuming common beans regularly can lower the risk of coronary heart disease, type II diabetes, and cancer (Kutos et al. 2003; Krupa \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite its many uses and benefits, it is only grown in a small area and crops are underutilized due to photosensitivity, insufficient yields, erratic flowering, long growth habit and consumer preferences for pod size, shape, colour and aroma (Vaijayanthi et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Hyacinth bean is a predominantly self-pollinated vegetable crop with limited genetic diversity for the most significant economic attributes (Gangadhara et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Collection and study of genetic diversity for morphological and yield traits across landraces is crucial for successful breeding and selection of certain traits (Parmar et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). It's difficult to determine if observed variability is hereditary or caused by environmental factors alone. Understanding heritability is crucial for selection-based development since it determines how a character will be handed down to future generations (Singh et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). D\u003csup\u003e2\u003c/sup\u003e statistical analysis is a useful method for assessing the degree of divergence across genotypes and biological populations at the genotypic level to choose better genotypes effectively. Studying the connections between attributes, especially yield and other tangible characteristics is crucial as yield is a complex character resulting from plant interactions (Singh et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Olivoto and Nardino (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) developed the multi-trait genotype-ideotype distance index (MGIDI). This unique multivariate selection index has been carefully built to solve the drawbacks of multiple traits. Unlike conventional techniques, the MGIDI takes into account the underlying connection between features and effectively picks all factors in the assessment process.\u003c/p\u003e \u003cp\u003eThe hyacinth bean is a commercial vegetable crop in south India but there are no studies available on the cultivation and assessment of hyacinth beans in the south Indian agroclimatic conditions. However, little research on this crop in the southern region of India has hindered advances in genetic improvement. As a result, the current study was done to assess genetic factors such as descriptive traits, correlation studies, clustering, PCA analysis and MGIDI for yield-attributing and three biochemical variables among extant hyacinth bean landraces and germplasm. The study aimed to characterise and identify the permitted lines and resources for further genetic improvement of the hyacinth bean.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eExperimental location\u003c/p\u003e \u003cp\u003eThe current investigation was carried out by conducting field experiments for two consecutive years during the summer season of 2021 and 2022, at the research farm of the Department of Vegetable Science, Horticultural College and Research Institute, Periyakulam, Tamil Nadu, India. Geographically, the experimental site was located between 10.13 \u003csup\u003e0\u003c/sup\u003eN latitude and 77.59 \u003csup\u003e0\u003c/sup\u003eE longitude and at 356 m above the mean sea level.\u003c/p\u003e \u003cp\u003eGenetic materials\u003c/p\u003e \u003cp\u003eThe experimental material for this study comprised 19 landraces of hyacinth beans obtained from various local regions of South Indian states including Andhra Pradesh, Tamil Nadu, Karnataka and Kerala. The details of landraces, along with seed, flower, pod colour variations and source of collection were illustrated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Additionally, five commercial cultivars Arka Amogh, Arka Jay, Arka Vijay, Arka Sowmya and Arka Sambhram were collected from the Indian Institute of Horticultural Research (IIHR), Bengaluru, Karnataka, India. One variety, Co (Gb) 14, was obtained from Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu and another variety, IC636214 was obtained from the NBPGR Regional Research Station, Kerala. These seven cultivars are commercially cultivated by farmers under South Indian agroecological conditions and were used as checks in this study.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSources and DUS characteristics of hyacinth bean germplasm used for the study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCode of genotypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLongitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLatitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFlower colour\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePod shape\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePod colour\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSeed colour\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTheni local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;42ʹ22ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u0026deg;86ʹ92ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAppipatti local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;37ʹ90ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u0026deg;83ʹ47ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChinnamanur local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;38ʹ49ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u0026deg;84ʹ15ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDark green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBodinayakanur local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;35ʹ04ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u0026deg;03ʹ24ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUthamapalayam local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;32ʹ99ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u0026deg;76ʹ62ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMayiladumparai local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;50ʹ67ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u0026deg;78ʹ80ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCumbum local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;28ʹ53ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u0026deg;73ʹ94ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKamatchipuram local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;54ʹ67ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u0026deg;11ʹ98ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePurple\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCurved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDark green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 11 Co (Gb) 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTNAU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76\u0026deg;96ʹ28ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u0026deg;00ʹ18ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePollachi local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;00ʹ87ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u0026deg;65ʹ88ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDark green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eErode local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;35ʹ05ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u0026deg;49ʹ05ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKarur local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78\u0026deg;38ʹ28ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u0026deg;82ʹ17ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDark green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNamakkal local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78\u0026deg;11ʹ86ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u0026deg;30ʹ33ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWalajapet local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79\u0026deg;36ʹ37ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026deg;92ʹ54ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDark green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKadapa local II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78\u0026deg;82ʹ35ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14\u0026deg;47ʹ75ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChittoor local II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79\u0026deg;10ʹ75ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13\u0026deg;21ʹ57ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCream\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 25 (Arka Amogh)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIIHR, Bangalore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;60ʹ41ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026deg;93ʹ16ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCream\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 26 (Arka Vijay)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIIHR, Bangalore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;60ʹ41ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026deg;93ʹ16ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 27 (Arka Jay)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIIHR, Bangalore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;60ʹ41ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026deg;93ʹ16ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePink\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCurved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCream\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 28 (Arka Sowmya)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIIHR, Bangalore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;60ʹ41ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026deg;93ʹ16ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCream\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 29 (Arka Sambhram)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIIHR, Bangalore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;60ʹ41ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026deg;93ʹ16ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCurved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDark green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMadurai local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78\u0026deg;11ʹ40ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u0026deg;92ʹ61ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKandamanur local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;53ʹ57ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u0026deg;94ʹ96ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKanavilaku local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;60ʹ36ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u0026deg;99ʹ62ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 34 IC 636214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNBPGR Regional station, Kerala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76\u0026deg;21ʹ46ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u0026deg;52ʹ70ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLight green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCream\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKadamalaikundu local\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u0026deg;42ʹ22ʺE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u0026deg;86ʹ92ʺN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDark green\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBrown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAllocation of genotypes and data collection\u003c/p\u003e \u003cp\u003eA randomized complete block design (RCBD) was used to study the genotypes of hyacinth beans during the summer seasons of 2021 and 2022. The experiment was conducted in 78 plots, each measuring about 2.5 \u0026times; 2.5 meters. In each plot, twenty-five plants were allocated from each genotype in three replications. Before sowing, half of the nitrogen and the full doses of phosphate and potash were applied as a basal dosage. The remaining nitrogen was applied as a top dressing 30 days after sowing. Five plants from every plot were randomly labelled to monitor growth, yield and biochemical traits such as days to germination, germination percentage, plant height (cm), number of primary branches, days to first flowering, days to 50% flowering, number of racemes/plant, days to pod formation, number of seeds/pod, pod length (cm), pod width (cm), number of pods/plant, pod weight (g), protein content (%), fibre content (%), phenol content (mg/100 g), yield/plant (g) and yield/plot (kg) and their mean value of each genotype in every replication was determined.\u003c/p\u003e \u003cp\u003eBiochemical assays\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eTotal proteins\u003c/strong\u003e \u003cp\u003eThe protein content of pods were estimated by multiplying the amount of nitrogen (%) value. The kjeldahl method was used to assess the nitrogen content in the pods (AOAC \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1960\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eTotal phenols\u003c/strong\u003e \u003cp\u003eTotal phenol content was estimated by using the method described by Sadasivam and Manickam (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). One gram of sample was separated using 80% ethanol. The resulting mixture was centrifuged at 10,000 rpm for 20 min. The supernatant was evaporated until dry. The leftover substance was dissolved in 5 ml of distilled water. An aliquot (0.5 ml) was transferred in a test tube and filled to a volume of 3 ml with distilled water, followed by the addition of 0.5 ml Folin-Ciocalteau reagent and 20% Na\u003csub\u003e2\u003c/sub\u003eCO\u003csub\u003e3\u003c/sub\u003e (2 ml) after 3 minutes and thoroughly mixed. The test tubes were immersed in warm water for one minute and then cooled. Absorbance at 765 nm was recorded against a reagent blank. A standard curve was generated using various amounts of gallic acid and the phenol content of the test sample was calculated as mg/100 g of sample.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCrude fibre\u003c/strong\u003e \u003cp\u003eThe crude fibre content was determined using a methodology summarised by Sadasivam and Manickam (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). One gram of sample was added to 100 ml of 1.25% H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e and heated for 30 minutes on a magnetic hot plate with continual stirring. The sample was then filtered through muslin cloth and rinsed with hot water to remove the acid. The residue was treated similarly with 1.25% NaOH and filtered before being rinsed with hot water. The resulting residue was rewashed with boiling 1.25% H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e, 50 ml water and 25 ml alcohol. After washing, the residue was placed in a crucible and baked in an oven at 130\u0026thinsp;\u0026plusmn;\u0026thinsp;2 \u003csup\u003e0\u003c/sup\u003eC for 2 hours. The sample was ultimately cooled in a desiccator before being weighed. The sample was then transferred to a muffle furnace at 600 \u003csup\u003e0\u003c/sup\u003eC for 30 minutes to be ignited. Thereafter, the sample was cooled and weighed to determine the crude fibre content using the expression (Sadasivam and Manikam, 1992)\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv id=\"Equa\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{C}\\text{r}\\text{u}\\text{d}\\text{e}\\:\\text{f}\\text{i}\\text{b}\\text{r}\\text{e}\\:\\left(\\text{%}\\right)=\\frac{\\text{W}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t}\\:\\text{l}\\text{o}\\text{s}\\text{s}\\:\\text{d}\\text{u}\\text{r}\\text{i}\\text{n}\\text{g}\\:\\text{i}\\text{g}\\text{n}\\text{i}\\text{t}\\text{i}\\text{o}\\text{n}}{\\text{I}\\text{n}\\text{i}\\text{t}\\text{i}\\text{a}\\text{l}\\:\\text{w}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t}\\:\\text{o}\\text{f}\\:\\text{t}\\text{h}\\text{e}\\:\\text{s}\\text{a}\\text{m}\\text{p}\\text{l}\\text{e}}\\times\\:100$$\u003c/div\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eAssessment the prevalence of diseases and pests under epiphytic conditions\u003c/p\u003e \u003cp\u003ePod borer incidence (%): The total number of healthy and infested pods was recorded during each harvest. After the last harvest, the average number of pods in each replication was estimated by summarising all healthy and infected pods of each genotype (Mallikarjuna 2012).\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:\\text{P}\\text{o}\\text{d}\\:\\text{b}\\text{o}\\text{r}\\text{e}\\text{r}\\:\\text{i}\\text{n}\\text{c}\\text{i}\\text{d}\\text{e}\\text{n}\\text{c}\\text{e}\\:\\left(\\text{%}\\right)=\\frac{\\text{N}\\text{u}\\text{m}\\text{b}\\text{e}\\text{r}\\:\\text{o}\\text{f}\\:\\text{p}\\text{o}\\text{d}\\text{s}\\:\\text{i}\\text{n}\\text{f}\\text{e}\\text{s}\\text{t}\\text{e}\\text{d}\\:\\text{w}\\text{i}\\text{t}\\text{h}\\:\\text{p}\\text{o}\\text{d}\\:\\text{b}\\text{o}\\text{r}\\text{e}\\text{r}}{\\text{T}\\text{o}\\text{t}\\text{a}\\text{l}\\:\\text{n}\\text{u}\\text{m}\\text{b}\\text{e}\\text{r}\\:\\text{o}\\text{f}\\:\\text{p}\\text{o}\\text{d}\\text{s}\\:\\text{h}\\text{a}\\text{r}\\text{v}\\text{e}\\text{s}\\text{t}\\text{e}\\text{d}\\:\\:}\\:\\times\\:100$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eBean mosaic virus incidence (%): In each genotype, bean mosaic virus incidence was visually assessed by observation of 25 randomly selected plants from each replication and plants were scored as either infected with mosaic or not under natural epiphytic conditions (Singh et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). The incidence of mosaic disease infestation was then computed as the percentage of plants exhibiting symptoms as follows,\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:\\text{B}\\text{e}\\text{a}\\text{n}\\:\\text{m}\\text{o}\\text{s}\\text{a}\\text{i}\\text{c}\\:\\text{v}\\text{i}\\text{r}\\text{u}\\text{s}\\:\\text{i}\\text{n}\\text{c}\\text{i}\\text{d}\\text{e}\\text{n}\\text{c}\\text{e}\\:\\left(\\text{%}\\right)=\\frac{\\text{N}\\text{u}\\text{m}\\text{b}\\text{e}\\text{r}\\:\\text{o}\\text{f}\\:\\text{p}\\text{o}\\text{d}\\text{s}\\:\\text{i}\\text{n}\\text{f}\\text{e}\\text{s}\\text{t}\\text{e}\\text{d}\\:\\text{w}\\text{i}\\text{t}\\text{h}\\:\\text{m}\\text{o}\\text{s}\\text{a}\\text{i}\\text{c}\\:\\text{s}\\text{y}\\text{m}\\text{p}\\text{t}\\text{o}\\text{m}\\text{s}}{\\text{T}\\text{o}\\text{t}\\text{a}\\text{l}\\:\\text{n}\\text{u}\\text{m}\\text{b}\\text{e}\\text{r}\\:\\text{o}\\text{f}\\:\\text{p}\\text{l}\\text{a}\\text{n}\\text{t}\\text{s}\\:\\text{o}\\text{b}\\text{s}\\text{e}\\text{r}\\text{v}\\text{e}\\text{d}}\\:\\times\\:100$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe data recorded on different parameters were subjected to statistical analysis for estimation of various genetic parameters and to find out the degree of association among different characters and their contribution to the pod yield. Principal component analysis and cluster analysis were performed in XLStat 2020 software. The descriptive statistical analysis and Pearson correlation were analysed by using GRAPES software. The MGIDI analysis was computed by using the RStudio 4.4.1 version.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result and Discussion","content":"\u003cp\u003eMean performance of morphological and biochemical traits\u003c/p\u003e \u003cp\u003eThe pooled data analysis of two years (2021 and 2022) morphological, quality and yield components of the bush type of hyacinth bean germplasms revealed substantial genetic and morphological variations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), which is a pre-requisite for the selection of landraces for hyacinth bean improvement programme. The minimum days (4.00) to germination in PKM LP 01, PKM LP 06 and PKM LP 16, whereas the maximum days taken in PKM LP 30 (7.50). Concerning plant height, the highest value was noticed in PKM LP 02 (76.75 cm) genotype, followed by PKM LP 27 (75.95 cm), whereas the lowest plant height was reported in PKM LP 07 (44.90 cm). The differences in plant growth may be due to genetic variability within the genotypes or it may be due to the environmental effects (Reddy et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Among the genotypes, the maximum (6.76) number of branches was obtained in PKM LP 26 (Arka Vijay), followed by PKM LP 11 (5.20). In contrast, the lowest number of primary branches was notified in PKM LP 06 (4.16). 26 hyacinth bean genotypes showed the maximum variations in branching patterns, plant stature and flower colour (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Considering the days to first flowering, early flowering was observed in PKM LP 06 (38.40 days) followed by PKM LP 03 (39.20 days), whereas the maximum number of days to first flowering in PKM LP 35 (53.43 days) and this genotype considered as late flowering type. It concerned days to 50% flowering, minimum days taken in PKMLP 03 (45.20 days), followed by PKM LP 01 ((46.23 days) and maximum days taken in PKM LP 35 (58.83 days). The maximum number of racemes with a value of 6.93 was reported in PKM LP 08, followed by PKM LP 02 (6.53). PKM LP 11 genotype took fewer days (44.50 days) for pod formation, followed by PKM LP 08 (44.61 days), whereas the maximum duration was observed for the formation of pods in the PKM LP 35 genotype (57.23 days) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMorphological characterization of hyacinth bean genotypes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCode of genotypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDays to germination\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGermination percentage (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePlant height\u003c/p\u003e \u003cp\u003e(cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNumber of\u003c/p\u003e \u003cp\u003eprimary\u003c/p\u003e \u003cp\u003ebranches\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDays to first flowering\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDays to 50% flowering\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNumber of racemes/plant\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDays to pod formation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNumber of seeds/pod\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.00 g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89.20 a-c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.00 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.26 k-m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.13 l-n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e46.23 hi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.63 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e47.51 e-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.20 h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.50 f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.30 e-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.75 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.90 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43.40 g-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e57.30 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.53 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e48.43 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.26 c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.00 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81.20 h-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.25 ij\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.63 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39.20 mn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e45.20 i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.13 kl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e44.76 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.33 bc\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.00 e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79.10 j-n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.30 de\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.23 lm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42.30 i-k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54.16 c-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.50 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e48.53 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.23 gh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.50 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81.60 g-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.50 gh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.60 e-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.23 j-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51.43 g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.90 de\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e45.50 gh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.36 bc\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.00 g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.50 n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.40 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.16 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38.40 n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e48.32 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.13 n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e48.70 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.21 h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.50 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85.70 c-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.90 k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.46 g-k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.33 e-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54.26 c-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.40 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49.20 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.46 a-c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.50 f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87.30 b-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.55 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.96 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.56 i-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51.50 g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.93 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e44.61 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.56 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 11 (Co (Gb) 14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.50 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90.40 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73.80 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.20 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.30 j-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e46.26 hi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.33 bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e44.50 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.51 ab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.00 e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.90 d-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.35 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.60 e-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46.40 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e58.80 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.26 i-k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e50.23 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.46 a-c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.86 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79.98 i-m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.88 j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.66 e-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45.63 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51.53 fg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.60 fg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49.73 c-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.30 c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.50 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.09 d-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.00 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.30 j-m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45.69 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e52.33 e-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.43 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e50.90 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.33 e-h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.00 g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82.29 f-k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.75 gh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.70 ef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46.16 c-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54.46 c-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.76 ef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e50.50 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.43 d-g\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.50 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86.50 b-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.25 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.33 i-m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42.83 h-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e53.63 d-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.80 o\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e47.23 e-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.21 h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.00 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77.70 l-n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57.00 g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.53 f-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.23 f-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e55.20 b-d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.16 j-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49.21 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.40 d-h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.50 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.60 mn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60.75 ef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.33 i-m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50.30 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e52.10 e-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.93 l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e54.53 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.46 d-f\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 25 (Arka Amogh)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.50 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.50 k-n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.75 fg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.50 f-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46.60 k-m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54.33 c-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.53 f-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e50.30 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.30 f-h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e 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colname=\"c11\"\u003e \u003cp\u003e4.53 ab\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 27 (Arka Jay)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.50 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85.50 c-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.95 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.90 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43.33 g-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e53.10 d-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.40 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e48.71 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.30 c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 28 (Arka Sowmya\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.50 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79.30 j-n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67.45 bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.40 h-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.60 k-m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e52.26 e-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.06 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e56.23 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.42 d-g\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 29 (Arka Sambhram)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.00 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.20 d-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.30 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.76 de\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.86 d-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54.13 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.33 h-k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e48.13 d-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.60 d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.50 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79.40 j-n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.25 hi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.33 i-m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42.43 h-k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e53.33 c-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.43 g-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e47.10 fg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.23 gh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.00 e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86.70 b-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.30 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.53 f-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e47.33 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e56.36 a-c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.36 g-k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e51.00 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.46 d-f\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.00 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.30 d-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.25 j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.60 e-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46.20 c-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54.40 c-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.40 g-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e50.53 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.53 de\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 34 (IC 636214)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.50 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87.80 b-d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56.75 g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.50 f-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43.13 g-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e53.53 d-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.60 fg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e48.51 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.43 d-g\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.00 e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89.40 a-c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67.30 bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.56 e-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53.43 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e58.83 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.63 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e57.23 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.46 d-f\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSED (\u0026plusmn;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCD at 5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eNote: Means with the different superscript letters are statistically different at p\u0026thinsp;\u0026gt;\u0026thinsp;0.05 based on Tukey\u0026rsquo;s test\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll 26 hyacinth bean genotypes had maximum variations concerning pod shape, seed coat and pod colour (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). PKM LP 08 elite genotype had more seeds/pod (4.56) and also similar results were obtained in PKM LP 26 (4.53) and PKM LP 11 (4.51). Pod length differed considerably among all genotypes which was highest in PKM LP 11 (8.56 cm), followed by Arka Jay (8.40 cm) and short pod length was noticed in PKM LP 06 (5.80 cm). The maximum pod width was obtained in PKM LP 06 (1.80 cm) and the minimum pod length was noticed in PKM LP 19 with the value of 1.06 cm. PKM LP 26 genotype had more pods/plant with a value of 39.66, followed by PKM LP 11 (38.45) and less number pods were observed in PKM LP 15 (24.19). The maximum yield/plant (1.32 g) yield/plot (7.32 kg) was exhibited in PKM LP 11 followed by PKM LP 26 (1.30 g). The maximum protein content (21.78%), fibre content (1.32%) and maximum phenols (7.32 mg/100 g) content were reported in the PKM LP 11 genotype (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The current findings are the results of Kushwah et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) for phenological traits, Srungarapu et al. (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) for the agronomic, yield traits in chickpeas, Mohan et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), Gangadhara et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) in dolichos bean and Reddy et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Reddy and Dhathri (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) in cucumber for the quality traits.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean performance of hyacinth bean genotypes for yield-related and biochemical traits\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCode of genotypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePod length\u003c/p\u003e \u003cp\u003e(cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePod width\u003c/p\u003e \u003cp\u003e(cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNumber of pods/plant\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePod weight\u003c/p\u003e \u003cp\u003e(g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eProtein content (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eFibre\u003c/p\u003e \u003cp\u003econtent (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePhenol\u003c/p\u003e \u003cp\u003econtent\u003c/p\u003e \u003cp\u003e(mg/100 g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eYield/plant\u003c/p\u003e \u003cp\u003e(g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eYield/plot\u003c/p\u003e \u003cp\u003e(kg)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.36 lm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.18 r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.13 lm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.07 jk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81.25 no\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.14 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17.31 i-k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.12 k-n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.25 jk\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.83 bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.56 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.00 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.48 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e126.29 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.37 e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.59 b-d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.25 b-d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.25 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.85 f-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.31 i-o\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.00 lm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.43 c-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90.28 lm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.43 kl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17.76 hi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.24 c-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.29 jk\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.13 mn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.23 p-r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.00 j-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.73 l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75.60 p\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.05 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17.25 i-k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.09 mn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.15 jk\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.35 de\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.30 l-o\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.56 jk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.49 b-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e98.20 jk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.55 k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.67 e-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.14 i-m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.32 i-k\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.80 o\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.80 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.85 kl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.03 k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e85.33 mn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.13 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16.76 j-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.10 l-n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.03 kl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.80 g-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.36 i-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.38 k-m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.49 b-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e93.67 kl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.45 kl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.54 b-e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.26 bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e 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\u003cp\u003e1.28 a-c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.50 b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 11 Co (Gb) 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.56 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.53 de\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.45 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.55 bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e138.94 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.7 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21.78 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.32 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.32 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.05 e-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.24 o-q\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.51 fg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.36 e-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e105.45 gh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e 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\u003cp\u003e128.31 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.01 fg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17.65 h-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.25 b-d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.59 g-i\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.86 no\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.10 s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.19 n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.24 hi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e79.47 op\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.08 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16.09 l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.03 o\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.32 m\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.56 i-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.20 qr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e 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\u003cp\u003ePKM LP 24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.68 i-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.43 f-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.37 j-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.45 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e130.97 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.46 de\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.36 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.19 e-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.03 de\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 25 (Arka Amogh)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.39 k-m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.48 ef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.83 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.42 c-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e120.11 e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.13 f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.41 b-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.23 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.28 b-d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 26 (Arka Vijay)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.03 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.58 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.66 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.08 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e163.56 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.92 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.39 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.30 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.35 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 27 (Arka Jay)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.40 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.63 bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.60 d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.64 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e132.90 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.56 cd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.78 b-d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.28 a-c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.53 b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 28 (Arka Sowmya\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.65 h-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.32 k-n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.95 fg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.27 g-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e103.43 g-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.75 ij\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.89 bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.26 bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.37 bc\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 29 (Arka Sambhram)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.03 e-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.42 f-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.85 hi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.40 c-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e101.87 h-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.78 h-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20.32 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.27 a-c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.43 b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.71 i-k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38 h-k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.76 gh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.32 f-i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99.94 ij\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.68 j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.35 c-f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.17 g-k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.37 h-j\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.78 g-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.35 j-m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.31 j-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.38 d-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e94.38 kl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.34 l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.72 b-d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.15 h-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.30 b-d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.45 j-m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.39 g-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.21 f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.41 c-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e107.21 g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.79 h-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.60 fg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.13 j-m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.01 de\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 34 (IC 636214)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.58 i-l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.27 n-p\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.32 ij\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.39 c-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100.23 h-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.75 ij\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.89 bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.20 d-h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.83 e-g\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.75 h-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38 h-k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.89 e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.41 c-g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e115.21 ef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.02 fg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17.65 h-j\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.16 h-k\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.13 jk\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSED (\u0026plusmn;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCD at 5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eNote: Means with the different superscript letters are statistically different at p\u0026thinsp;\u0026gt;\u0026thinsp;0.05 based on Tukey\u0026rsquo;s test\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDescriptive parameters of hyacinth bean genotypes\u003c/p\u003e \u003cp\u003eThe assessment of variability parameters revealed a tremendous amount of variation among the genotypes for different characters. The GCV and PCV values provide insight into the magnitude of genetic variation. The heritability assessed in conjunction with estimates of genetic advance indicates genetic gains in the following generation or the change in average values between generations. The estimates of GCV, PCV, heritability and genetic advance of pooled data analysis are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive parameters for 18 characters in 26 hyacinth bean genotypes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraits\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGenotypic variance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePhenotypic variance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEnvironmental variance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePCV (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGCV (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHeritability\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGenetic advance as % mean\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDays to germination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e97.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGermination percentage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e78.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlant height (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of primary branches\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDays to flowering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDays to 50% flowering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e86.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of racemes/plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e97.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDays to pod formation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of seeds/pod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePod length (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e94.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePod width (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of pods/plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e97.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePod weight (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e88.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein content (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e88.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFibre content (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e85.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhenol content (mg/100g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYield/plant (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e450.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e460.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e97.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYield/plot (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e98.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e39.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe PCV ranged from 5.78\u0026ndash;19.91% and the maximum was reported in yield/plant (19.91%) and the lowest PCV was observed in the case of germination percentage (5.78%). The genotypes show a wide range of GCV for growth, yield and biochemical traits and it ranges from 5.1\u0026ndash;19.69%. Days to germination, plant height, number of primary branches, number of racemes/plant, number of seeds/pod, pod length, pod width, pods/plant, phenol content, yield/plant and yield/plot exhibit moderate PCV and GCV indicates a moderate amount of variation. The moderate estimates of PCV and GCV have been reported previously by Patel et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) for pod length, pod weight and number of pods/plant, indicating low response to selection for these traits. Likewise, moderate to high estimates of GCV were reported in another study by Kumar et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Gamit et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The lowest GCV and PCV values were noted for the traits \u003cem\u003eviz.\u003c/em\u003e, days to first flowering, days to 50% flowering, days to pod formation, pod weight, protein content and fibre content. GCV and PCV are not much different in the majority of traits, revealing that the environment has less influence. The slight variations between PCV and GCV suggested that the heritable component is necessary for their expression and also the selection of genotypes.\u003c/p\u003e \u003cp\u003eIn the present study heritability ranges from 78% in germination percentage to 98% in yield/plot. High heritability estimates were recorded for yield/plot (98%) followed by yield/plant (97.8%), days to germination (97.4%), pods/plant (97.3%), number of racemes/lant (97%), pod width (96.9%) shows less impact environment on these characters. High heritability was observed in all the characters and a strong influence of genetic constitution on character expression; from a breeding perspective, such traits are considered for selection. These findings suggest the implication of selection procedures for the improvement of dolichos bean (Lahari et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Thasneem et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). GA as per cent of the mean ranged from 9.28 in germination percentage to 40.10 in yield/plant. In this study high values of GA as a per cent of the mean were observed \u003cem\u003eviz.\u003c/em\u003e, yield/plant (40.10), yield/plot (39.09), and days to germination (33.66). During the present investigation moderate values of GA as a per cent of the mean were noticed in days for first flowering (14.77), days to 50% flowering (12.34) and days to pod formation (11.77). High genetic advance was also documented in Indian beans by Thasneem et al. (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Afsan and Roy (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and Peer et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) for days to first harvest, length of inflorescence, number of flowers/plant, number of pods/plant, In the present study maximum traits revealed high heritability values accompanied with high GA as per cent of mean, because additive gene effects mainly control the expression of these attributes, phenotypic performance-based selection will be useful in the future for improving these characters.\u003c/p\u003e \u003cp\u003ePearson correlation analysis\u003c/p\u003e \u003cp\u003eThe correlation analysis revealed positive as well as negative correlations among various morphological and yield-related traits (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). In the present investigation, yield/plant showed a highly significant positive correlation with pods/plant (0.89), Pod width (0.82), number of primary branches (0.77), pod length (0.76), number of racemes/plant (0.70), pod width (0.58) and number of seeds/pod (0.56) indicating that these attributes strongly influenced the yield/plant of hyacinth bean. Therefore, even though direct selection for improvement has not been done for the yield character, methods of selection for the improvement of one character inevitably result in the improvement of another trait as well. Plant height showed a significant and positive correlation with pod length (0.46) and pods/plant (0.40). The number of primary branches noticed that significant and positive correlation with all the attributes except days to germination, plant height, days to first flowering, days to 50% flowering, days to pod formation and pod width. Days to first flowering showed a positive and significant correlation with days to 50% flowering (0.65) and days to pod formation (0.69). Days to pod formation exhibited a highly positive and significant association with days to first flowering.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe number of racemes/plant showed that significant association with primary branches (0.56), number of seeds/pod (0.58), pod length (0.84), pod width (0.46), pods/plant (0.76) and pod weight (0.59), rest of the traits shown a non-significant correlation. The number of seeds/pod recorded that positive and significant association with the number of primary branches (0.60), number of racemes/plant (0.58), pod length (0.75), pods/plant (0.53) and pod weight (0.67), It shows that negative association with days to pod formation (-0.43). This indicated that there was a high degree of interrelationship between the yield/plant and other yield attributes at the genotypic level. The positive association for the related traits has been depicted earlier by Chaitanya et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), Thorat et al. (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and Attar et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) in hyacinth bean. The positive association among the studied traits indicated the scope for simultaneous improvement of these traits in a breeding programme. The results indicate that hyacinth bean yield potential can be increased by applying the strong selection to plant height, number of racemes/plant, pods/plant, seeds/pod, pod weight, pod length and pod width and days to 50% flowering. These results indicate the true genetic relationship between these traits and direct selection through these traits will be rewarding to improve the yield. Similar types of findings were also reported by Geetha and Divya (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Bansod et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) in dolichos bean.\u003c/p\u003e \u003cp\u003eClustering of hyacinth genotypes\u003c/p\u003e \u003cp\u003eDepending on the proportion of D\u003csup\u003e2\u003c/sup\u003e estimates 26 genotypes were classified into five clusters. The distribution of various genotypes in each cluster is shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. Cluster IV possesses the most genotypes (9), followed by cluster III (7), cluster I (5), cluster II (4) and cluster V (1). Each cluster represented the greatest variance in the contribution of various attributes, reflected in the profile plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Arka Vijay is the only genotype in cluster V and all the traits positively contributed to this cluster V, especially the number of primary branches, pod weight and yield/plant followed by cluster II. Among all the clusters, cluster I genotypes had fewer values in each trait followed by cluster III. So, it is recommended to use clustering or grouping of germplasm based on both morphological and yield traits, since this sort of clustering contributes to the selection of genotypes that have superior yield. This type of clustering will be useful in identifying the superior genotypes in an extensive population. These findings are consistent with the findings of Gangadhara et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and Haralayya et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), who examined D\u003csup\u003e2\u003c/sup\u003e clustering in french beans and Gangadhara et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and Kiran et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) in dolichos beans.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGrouping of 26 bush-type hyacinth bean genotypes into five clusters based on cluster analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClusters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo of genotypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eName of genotypes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePKMLP 1, PKMLP 4, PKMLP 6, PKMLP 15, PKMLP 19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePKMLP 2, PKMLP 4, PKMLP 11 [Co (Gb)14], PKMLP 27 (Arka Jay)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePKMLP 3, PKMLP 5, PKMLP 7, PKMLP 13, PKMLP 30, PKMLP 32, PKMLP 34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePKMLP 12, PKMLP 16, PKMLP 23, PKMLP 24, PKMLP 25 (Arka Amogh), PKMLP 28 (Arka Sowmya), PKMLP 29 (Arka Sambhram), PKMLP 35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePKMLP 26 (Arka Vijay)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePrincipal component analysis (PCA) in hyacinth bean genotypes\u003c/p\u003e \u003cp\u003eThe present study demonstrates the different variables contribute to a grouping of genotypes based on the PCA. The eigenvalues are associated with each PC, while the cumulative variability rises and illustrated as a scree plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). A total of eighteen components are depicted as a scree plot showing the 100% genetic variation. The first 5 PCs had recorded more than one eigenvalue and accounted for 82.62% of the total variance among 26 genotypes. The PC1 accounts for 47.52% of the total variance, followed by PC2 (13.60%), PC3 (9.12%) and PC4 (7.38%), indicating the presence of significant variability among genotypes for the variables under consideration.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe individual eigenvector value of different variables reveals their contribution towards the total variation of that particular PC (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The traits that contributed positively to PC1 were pod yield/plot (0.32), followed by yield/plant (0.31), pod length (0.31), pods/plant (0.30), number of racemes/plant (0.29), pod weight (0.28) whereas the traits that contributed negatively to PC1 were days to first flowering (-0.01) and days to pod formation (-0.07. As a result, early yield will benefit greatly through selection for these traits. This demonstrates that PC1 generated a significant amount of variability due to its early emergence as well as yield contributing features (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). The factors that contributed favourably to PC2 were days to first flowering (0.59), days to pod formation (0.53) and days to 50% flowering (0.50) whereas, negative impact characteristics such as the number of seeds/pod (-0.19), pod length (-0.10), pod width (-0.09) and number of primary branches (-0.03). The components with eigenvalues greater than one are deemed as primary or significant components because they account for a high share of the variance. Plant breeders usually select such components for plant selection.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactor loadings of yield and its components traits and biochemical traits for the first five major principal components\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePC1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePC2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePC3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePC4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePC5\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDays to germination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGermination percentage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlant height (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of primary branches\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDays to first flowering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDays to 50% flowering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of racemes/plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDays to pod formation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of seeds/pod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePod length (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePod width (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of pods/plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePod weight (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein content (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFibre content (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhenol content (mg/100g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYiel/plant (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYield/plot (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePer cent (%) of variance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA biplot was drawn between PC1 and PC2 to observe the relationship of variables and grouping of genotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e). PKM LP 26 is a high yielder placed at the extreme right corner of the biplot, whereas PKM LP 4 and PKM LP 15 are a low yielding genotype placed at the extreme left corner of the biplot. The contrasting characters were placed in an opposite position. The outcome of PCA was consistent with the result of cluster analysis. These findings are consistent with previous research by Reddy et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) on French bean, Singh et al. (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Shibli et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Kumari et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) on dolichos bean, which examined the per cent variation and trait contribution of plant height, number of pods/plant, pod length, pod weight and pod yield to total diversity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIdentification of superior genotypes based on MGIDI analysis\u003c/p\u003e \u003cp\u003ePlant breeders aim to cumulate various suitable morphological traits in one genotype that finally leads to reaching superior performance. The MGIDI selection index was performed to identify the superior performance genotypes based on the multiple traits. Among 26 genotypes, four genotypes were identified through (MGIDI) and which are indicated in red colour. Four genotypes including PKM LP 13, PKM LP 26, PKM LP 27 and PKM LP 35 genotypes performed well for multiple traits and four factors, indicating significant potential for improving 18 measured traits simultaneously in a hyacinth bean breeding program (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eStrengths and weaknesses of genotypes based on MGIDI factors\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e summarises the strengths and weaknesses of selected genotypes, as measured by each factor's contribution to the multi-trait genotype ideotype distance index (MGIDI). The genotypes associated with factor 1 (FA1), such as PKM LP 26 (Arka Vijay), demonstrate particular strengths in traits such as germination percentage, plant height, branches/plant, days to 50% flowering, number of seeds/pod, pod length, number of pods/plant, pod weight, yield/plant, yield/plot, phenol content and fibre content. On the other hand, genotypes PKM LP 35 linked to FA2, PKM LP 27 (Arka Jay) and PKM LP 13 genotypes are associated with FA3. Lastly, Factor 4 (FA4) with genotypes like PKM LP 35 and PKM LP 13 demonstrates strength in traits like the primary branches, days to first flowering and pod formation, seeds/pod, pods/plant, pod length, width and yield/plant. These insights on genotype strengths and weaknesses can help advise future breeding programs in terms of parent selection. These findings are similar to the prior study conducted on sorghum by Behera et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), guar by Benakanahalli et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), rice by Pallavi et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and barley by Zali et al. (2023). The multi-trait genotype-ideotype distance index (MGIDI) was extremely effective in identifying improved hyacinth bean genotypes, resulting in acceptable improvements across numerous traits. The identified genotypes such as PKM LP 26 (Arka Vijay), PKM LP 35, PKM LP 27 (Arka Jay) and PKM LP 13 by MGIDI reveal their potential for commercial availability or use as vital breeding resources in hyacinth bean breeding improvement efforts. The detailed examination of strengths and weaknesses yielded useful insights, emphasising the importance of a superior hyacinth bean genotype with better quantitative traits.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGrouping of genotypes into 4 factors through MGIDI and its positively contributed traits\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGenotypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePositively contributed traits\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFA1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePKM LP 26 (Arka Vijay)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGermination percentage, plant height, number of branches/plant, days to 50% flowering, number of seeds/pod, pod length, number of pods/plant, pod weight, yield/plant, yield/plot, phenol content and fibre content\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFA2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePKM LP 35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGermination percentage, plant height, days to first flowering and 50% flowering and days to pod formation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFA3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePKM LP 27 (Arka Jay) and PKM LP 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDays to germination, number of seeds/pod, number of pods/plant, pod weight, yield/plant, yield/plot and fibre content\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFA4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePKM LP 35 and PKM LP 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNumber of primary branches/plant, days to first flowering and pod formation, number of seeds/pod, number of pods/plant, pod length, pod weight and yield/plant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBean common mosaic and pod borer incidence in hyacinth bean genotypes\u003c/p\u003e \u003cp\u003eIdentifying pest and disease resistance sources is the primary goal of the crop improvement programme. Pod borer and bean mosaic is a major constraint to the production and productivity of hyacinth beans. In this study, bean common mosaic and pod borer incidence showed significant variation between 26 germplasms (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). PKM LP 04 exhibited higher pod borer incidence (33.82%) followed by PKM LP 19 (25.20%) and less pod borer (13.20%) incidence was noted in PKM LP 02. The highest bean mosaic virus incidence (21.66%) was found in PKM LP 15, followed by PKM LP 19 (20.97%) and mosaic virus incidence (8.25%) lower in PKM LP 35.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePod borer and bean mosaic incidence in hyacinth bean genotypes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCode of Genotypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePod borer incidence\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRate of infestation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBean mosaic virus incidence (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRate of infestation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate susceptible\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate resistant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate susceptible\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate susceptible\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate susceptible\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate susceptible\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate resistant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate resistant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 11 Co (Gb) 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate resistant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate resistant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate susceptible\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate susceptible\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate susceptible\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate susceptible\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate susceptible\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate resistant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 25 (Arka Amogh)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate resistant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 26 (Arka Vijay)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate resistant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 27 (Arka Jay)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate resistant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 28 (Arka Sowmya\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate susceptible\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 29 (Arka Sambhram)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate resistant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate susceptible\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate resistant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate susceptible\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 34 (IC 636214)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate susceptible\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePKM LP 35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerate resistant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e15.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSED (\u0026plusmn;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCD at 5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eStudy of genetic diversity of hyacinth bean landraces for yield and its attributing traits is crucial for their efficient use in hyacinth bean breeding improvement programme. In this study, 26 hyacinth bean germplasms including 19 landraces and 7 commercial varieties were assessed for eighteen traits. Among 26 genotypes, PKM LP 11 and PKM LP 26 had the highest yield and the superior yield-related attributes. substantial heritability estimates, along with substantial genetic progress as a percentage of the mean, showed that the qualities under research are mostly influenced by additive gene action and phenotypic selection will be desirable. The number of primary branches, racemes/plant, pods/plant, pod length, width and weight all had a positive impact on the yield/plant, indicating that these are most considerable traits for increasing yield in hyacinth bean. Heritability estimates for yield/plot were highest, followed by yield/plant, days to germination, pods/plant, number of racemes/plant, pod width and number of seeds/pod, indicating that environment has less of an impact on these characters. PKM LP 02 and PKM LP 35 landraces are reported as highly resistant against to pod borer and bean mosaic virus, respectively. The multi-trait genotype-ideotype distance index (MGIDI) was highly successful in identifying more accurate hyacinth bean genotypes, with acceptable improvements across a wide range of characteristics. In the current study, two genotypes including PKM LP 26 (Arka Vijay), PKM LP 27 (Arka Jay) and two landraces such as PKM LP 35 and PKM LP 13 were found by MGIDI analysis and demonstrated their potential for commercial availability or usage as essential breeding resources in hyacinth bean breeding improvement efforts. These two landraces were shown to perform better and they can be employed as possible donors for enhancing yield and agro-morphological features in future breeding programs.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eConflict of interest\u003c/strong\u003e \u003cp\u003eAll the authors declare that there are no conflicts of interest to disclose.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to participate\u003c/strong\u003e \u003cp\u003eAll authors have given consent to participate.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eAll authors have given consent to publication.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe work was supported by Horticultural College and Research Institute, Periyakualm, Tamil Nadu, India\u003c/p\u003e \u003cp\u003e \u003cb\u003eData availability\u003c/b\u003e Raw data are available upon request from the corresponding author.\u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e \u003cp\u003eMH designed the field layout and MH. SKR collected genotypes from various regions of south Indian states. SKR and KH helped in data analysis, table formatting and manuscript writing. The first draft of the manuscript was written by MH, SKR and KH. KV and SSR commented and corrected on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors would like to acknowledge the Dean of Horticultural College and Research Institute, Periyakulam, Tamil Nadu, India for providing the necessary facilities. The authors, staff and students would like to thank the HC\u0026amp;RI, Periyakulam for providing all financial support for collections of genotypes from different regions of South India.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAfsan N, Roy AK (2020) Genetic variability, heritability and genetic advance of some yield contributing characters in lablab bean (\u003cem\u003eLablab purpureus\u003c/em\u003e L. Sweet). J Bio-Sci 28:13\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3329/jbs.v28i0.44706\u003c/span\u003e\u003cspan address=\"10.3329/jbs.v28i0.44706\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAOAC (1960) Official and tentative methods of analysis. 9th Edn. 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Plant Productions 46(3):335\u0026ndash;351. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.22055/ppd.2024.45295.2134\u003c/span\u003e\u003cspan address=\"10.22055/ppd.2024.45295.2134\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Dr YSR HORTICULTURAL UNIVERSITY ","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hyacinth bean. Descriptive analysis. Dendrogram. Principal components. MGIDI","lastPublishedDoi":"10.21203/rs.3.rs-6181502/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6181502/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHyacinth bean is an underutilized leguminous vegetable crop with tremendous potential to contribute enormously to sustainable agriculture and nutritional security. Conserving and utilising hyacinth bean landrace diversity is key to adapting the crop to challenges and identifying desirable traits such as yield and nutritional characteristics, benefiting both farmers and consumers. The current study was focused on the diversity of hyacinth beans based on the eighteen traits evaluated during two consecutive summer seasons of 2021 and 2022. Descriptive analysis of the traits revealed that the highest heritability and genetic advance were shown for yield/plot and yield/plant, respectively. Correlation is employed to arrange and examine the relationships between the eighteen yield and its attributing traits. The number of branches/plant, racemes/plant, seeds/pod, pod length, pod width, pods/plant and pod weight traits showed a significantly positive correlation with pod yield/plant. Dendrogram based clustering divided 26 genotypes into five groups, with cluster IV containing the most genotypes. The PCA analysis reveals the five principal components had eigenvalues of more than one and accounted for 82.62% of the total variation. PC1 alone contributed 47.52% of the total variance, followed by PC2 about 13.60%. Four superior genotypes including PKM LP 26 (Arka Vijay), PKM LP 35, PKM LP 27 (Arka Jay) and PKM LP 13 were identified as superior using the multi-trait genotype ideotype distance index (MGIDI). Two uncovered landraces such as PKM LP 35 and PKM LP 13 showed superior performance than the checks which can be used as vital assets for creating recombinant populations with effective crop enhancement strategies.\u003c/p\u003e","manuscriptTitle":"Unlocking the genetic diversity of bush hyacinth bean (Lablab purpureus var. typicus L.) landraces under South Indian agro-ecologies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-11 09:50:31","doi":"10.21203/rs.3.rs-6181502/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"857617c1-78b8-499c-b65c-910feb4a5f19","owner":[],"postedDate":"March 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":45386495,"name":"Horticulture"}],"tags":[],"updatedAt":"2025-03-11T09:50:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-11 09:50:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6181502","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6181502","identity":"rs-6181502","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}