Comparative Evaluation of Agronomic Performance of Selected Landraces And Improved Groundnuts Cultivars In Central Uganda

Comparative Evaluation of Agronomic Performance of Selected Landraces And Improved Groundnuts Cultivars In Central Uganda | 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 Comparative Evaluation of Agronomic Performance of Selected Landraces And Improved Groundnuts Cultivars In Central Uganda John W Mulumba, Ronald Kakeeto, Rose Nankya, Hannington Lwandasa, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-696706/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Groundnut ( Arachis hypogaea L.) is important for providing food, income, livestock fodder for smallholder farmers, and improving soil fertility. However, groundnut yields on farmers’ fields in Sub-Saharan Africa are still very low due to various constraints. Several groundnut cultivars are available within the farmer’s domain but the adoption of these varieties favours landraces as opposed to improved varieties. Limited information is available on performance of commonly grown cultivars for guiding selection by different user groups (farmers, breeders and other users). This study was thus designed to determine the performance of selected landraces and improved groundnut varieties in Uganda. 23 groundnut lines with varying degrees of tolerance to a range of stresses were evaluated at two sites. Results showed significant (P ≤ 0.05 to P≤ 0.001) differences among genotypes for yield. Significant (P≤0.05 to P≤0.001) varietal differences were also observed between landraces and improved varieties for growth and physiological traits but not for pest and disease reaction. Clustering was not evident on the basis of either landraces or improved cultivars for pests and diseases incidences. However, associations of a mix of both groundnut classes of with particular diseases and/or pests were observed. Varieties such as India, Serenut 10, Kabonge, and DOK Tan associated with diseases such as rosette virus disease and its vector pest, the aphids. The results reported in this study shall be useful for driving the development of new cultivars owing to their good adaptability and acceptance thus the need to conserve and ensure sustainable use of these germplasm. Agronomy Behavioral Ecology Diversity peanuts conservation germplasm Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Groundnut ( Arachis hypogaea L.) is an economically valuable oilseed and cash crop grown extensively in the semi-arid tropical regions of the world. It is cultivated for direct consumption as food and for industrial use. Production of the crop is concentrated primarily in the semi-arid tropical regions of Asia and Africa, which together account for over 96% of world groundnut area and 92% of total global groundnut output. In Uganda, groundnut is the second most important legume after common bean (Okello et al. 2010 ; 2014 ). Besides being a major food crop, it also represents a significant source of income, thus contributing to improved livelihoods. Groundnut seeds contain 40–50 % high quality edible oil, 20–50% easily digestible protein and 10–20% carbohydrate depending on variety. Groundnut is also a nutritional source of vitamin E, niacin, falacin, calcium, phosphorous, magnesium, zinc, iron, riboflavin, thiamine and potassium (Savage and Keenan 1994 ). This makes groundnut an important source of nutrition in the country. In Uganda, groundnut is grown in diverse environments; and also utilized in various ways leading to diversity in variety preferences for this crop. Most literature on seed supply systems for crop varieties often refers to seeds as either ‘modern varieties’ or ‘landraces’. While a ‘modern variety’ is understood to be a variety that is improved by a formal breeding programme (Morris et al. 2003 ), released under a registered name and differing from other varieties by distinctive properties for which it is uniform and breeds true, a “landrace” is defined as dynamic population of a cultivated plant with a historical origin, distinct identity, often genetically diverse and locally adapted, and associated with a set of farmers’ practices of seed selection and field management as well as with a farmers’ knowledge base (Villa et al. 2005 ). The main contributions of landraces to plant breeding have been traits for adaptation to stressful environments such as water stress, salinity, low-input farming system, high temperatures and several biotic stresses such as pests and diseases ( Zeven 1998 ; Paterniani et al. 2000 ; Sharma et al. 2000 ; Araújo et al. 2002; Kashiwagi et al. 2005 ; Herzberg et al. 2004; Futakuchi et al. 2003 ) as well as useful genes for nutrient dense foods. As such, they act as useful starting materials for variety development strategies carried out at present and also for future use. In addition, a more efficient use of plant genetic diversity has been identified as a prerequisite for meeting the challenges of development, food security and poverty alleviation (FAO 1996 ). Therefore, it is of great importance to conserve and maintain a broad base of germplasm because they constitute valuable genetic resources for multiple desirable traits within the country’s groundnut gene pool. In Uganda, groundnut production is characterized by resource-constrained small-scale farmers who cannot afford inputs such as improved seed and fertilisers and, therefore rely on fellow farmers, farmer groups, local markets, NGOs and research organisations for these inputs (Mugisha et al. 2014 ). Given the lack of capital resources, the farmers are left with no option but to resort to using traditional farming methods with low levels of mechanisation, and many a time with varieties which compromise yields of the crop despite the existence of a wide range of varietal choice ranging from well adapted, but not readily available traditional varieties (due to lack of entry point into the formal seed system) to a number of released varieties which have been improved for several traits. Several pests and diseases attack groundnuts leading to reduction of yields and lowering the quality of produce hence increasing the cost of production. The major diseases of groundnuts include: Rosette caused by a complex of three viruses namely; Groundnut Rosette Virus (GRV), Groundnut Rosette Assistor Virus (GRAV) and satellite RNA (satRNA) transmitted by a single species of aphid ( Aphis craccivora Koch); Early Leaf Spot ( Cercospora arachidicola ); Late Leaf Spot ( Phaeoisariopis personata ); Root Rot; Mosaic; Rust ( Puccinia arachids ) and aflatoxin contamination (caused by Aspergillus niger and Aspergillus flavus ). The Groundnut Rosette Virus Disease (GRVD) is considered the most important constraint and can cause losses of up 100% if it occurs before flowering (Okello et al. 2010 ; Nigam et al. 2012 ). The important pests of groundnut are aphids ( Aphis craccivora Koch), a vector of groundnut rosette disease, leaf miner ( Aproarema modicella Deventer), thrips ( Thrips palmi Karny, Frankiniella schultzie Trybom, Scirtothrips dorsalis Hood) and termites (Isoptera) (Okello et al. 2010 ; Okello et al. 2014 ). Thrips and aphids are considered more important as vectors of viruses than as causing direct damage to groundnuts. In addition, the Groundnut Leaf Miner, a Lepidopteran defoliator was reported as an emerging threat to groundnut production areas in Uganda, especially those areas prone to drought (Mukankusi et al. 2000 ; Okello et al. 2010 ). As groundnut is grown in predominantly semi-arid regions characterized by erratic rainfall and on predominantly loose sandy loam soils, drought is often a recurring production constraint. This situation also coincides with the climate change phenomenon which projects disturbances such as a decrease in the lengths of the rainy seasons especially in semi-arid tropics (SAT) where most groundnuts are grown (Pasupuleti and Nigam 2013 ). In addition, drought has significant implications on groundnut quality which undermines the value of groundnut products on local, regional and international markets. The foregoing constraints notwithstanding, the success of a plant breeding program is anchored upon its ability to provide farmers with genotypes with guaranteed superior performance (phenotype) in terms of yield and/or quality across a range of environmental conditions. To achieve this aim, it is necessary to have an understanding of the factors leading to a good phenotype. Generally, the phenotype is the value for a trait at the end of the growing season, e. g kernel weight at maturity, and is the cumulative result of a number of continuous interactions between the genetic make-up of the plant (the genotype) and the conditions or stimuli in which that plant developed (the environment) and this varies from plant to plant. Environments differ in the amount and quality of inputs and stimuli that they convey to plants including, e.g., the amount of water, nutrients or incoming radiation. The primary objective in plant breeding is to match genotypes and environments in such a way that improved phenotypes are obtained. As quantitatively inherited trait, seed yield performance of a genotype often varies from one environment to another, leading to a significant genotype by environment (GxE) interaction which can severely limit gain of selecting superior genotypes. Understanding the interaction of those factors and how they affect seed yield is crucial for maintaining high yield (David et al. 2016 ). It is acknowledged that there can be genotypes that do well across a wide range of conditions (widely adapted genotypes), but there are also genotypes that do relatively better than others exclusively under a restricted set of conditions (specifically adapted genotypes). Specific adaptation of genotypes is closely related to the phenomenon of genotype-by environment interaction (GEI). GEI exists whenever the relative phenotypic performance of genotypes depends on the environment, or in other words, when the difference in reactions of genotypes varies with the environment. Some scenarios that can occur when comparing the performances of pairs of genotypes across environments are presented in Fig. 1 . The function describing the phenotypic performance of a genotype in relation to an environmental characterization is called the “norm of reaction” (Griffithsetal.1996). Figure 1A shows the case where there is no GEI, the genotype and the environment behave additively and the reaction norms are parallel. The remaining plots show different situations in which GEI occurs: divergence (Fig. 1B), convergence (Fig. 1C), and the most critical one, cross over interaction (Fig. 1D). Cross over interactions are the most important for breeders as they imply that the choice of the best genotype is determined by the environment. Therefore, given the complexity of the mechanisms and processes underlying the phenotypic response across diverse and changing environmental conditions, several analytical tools have been developed to help breeders understand GEI (Yates and Cochran 1938 ; Finlay and Wil- kinson 1963; Eberhart and Russell 1966 ; Gauch 1988 ; Singh et al. 1996b ) among others. The use of adequate strategies to analyze GEI is a first and important step toward more informed breeding decisions but details of how these tools are used is beyond the scope of this study. However, in finding workable solutions to limited information on performance of commonly grown groundnut landraces and improved varieties for guiding selection of groundnut varieties by different user groups (farmers, breeders and other users), the specific objectives of this study therefore were; (i) to interpret genotype (G), Class (Landrace and improved varieties) and Site (E) main effects and GE interaction for growth, pests and disease reaction, and yield performances of 23 groundnut genotypes evaluated in two growing sites (ii) Explore the nature of GE interaction and suggest strategies for exploiting it for improved targeting of varieties to different growing sites. Materials And Methods Site description The study was carried out in the Central Wooded Savanna ecological zone of Uganda, in Nakaseke (0°43’29” N, 32° 54’04” E) and Nakasongola (1°18’32” N, 32° 27’23”E) districts. In Nakasongola, the annual daily temperatures range from 18 o C to 35 o C, with mean daily maximum of 30°C. Rainfall ranges between 500 to 1000 mm per annum and there are two rain seasons. The vegetation in the study site mainly comprises three vegetation cover types depending on the extent of anthropogenic activities/disturbance on specific ranch sites. The three vegetation cover types include dense vegetation cover (>50% basal cover), sparse vegetation cover (25 to 50% basal cover) and bare ground. The area is characterized by prolonged droughts and floods due to shifting rainfall pattern (Nimusiima et al . 2013). Hitherto dominated by livestock grazing, the area is increasingly changing in land use, with crop farming especially for maize production becoming common. The altitudinal range is 600-1160msl. Nakaseke site has traditionally been described as the coffee–banana farming system. This area falls within an altitudinal range of 1086–1280 masl, with mean annual rainfall of up to 1100 mm. The annual daily temperatures range from 16 ◦C to 30 ◦C. Bi-modal rainfall distribution characterizes the two districts with the first rainy season extending from March to June, while the second rainy season starts in late August or early September to November-December (Ogwang et al .2016). The main rain season occurs from March-April to June July while the second rain season follows from August to October November. A long dry season occurs from December to February while a short spell comes around July-August. Trial gardens were established in two districts of Nakasongola and Nakaseke, each district taken as a site. In each site replication was done in four villages. In Nakaseke trial gardens were established in the villages of Kiziba, Namirali, Kalagala and Kyamutakasa while in Nakasongola they were established in Naitondo, Kasambya, Kalobokwe and Kiralamba (Figure 1 & Figure 2) Field layout Twenty-three groundnut varieties were planted in each site. The varieties included improved and farmer local varieties. The seeds for the improved varieties were sourced from the National Agricultural Semi-Arid Resources Research institute (NASARRI) while the farmer local varieties were from farmers in Amuria district. Each variety was planted to a single plot of 3 m x 4 m and at a plot-plot spacing of 1m with a plant population of 300 plants. A row to row spacing of 40 cm, and plant to plant spacing of 10 cm was used. Data collection Data was taken on common groundnut diseases and pests. The diseases included; Groundnut Rosette, Leaf Spot, Root-rot, and Groundnut Mosaic while the pests included aphids and leaf minor. Disease and pest incidences were assessed (at 1, 2 and 3 months after planting by counting the number of plants affected per variety (NaSARRI, unpublished). In addition, plant growth performance was assessed by measuring plant height while germination uniformity was scored 2 weeks from germination (Wood and Roper, 2000). Using a scale of 1 to 4, where 1= poor and 4 = very good performance. Stay green as a measure of drought tolerance was also evaluated using a scale of 1 to 4 which were subsequently converted to percentages. Yield was assessed in terms of number of pods per plant measured on twenty selected plants from five middle rows per plot for each variety Disease scores Leaf spot (Early and late leaf spot disease) Each leaf spot disease was scored separately using 1-9 scale on periodic basis after first appearance of the disease and subsequent scoring was done at an interval of 15 days and stopped at 20 days before harvest. Leaf spot was recorded using 9-point scale as described below (Subrahmanyam, P. et al . 1995). The severity scores were used to compute the area under disease progress curve AUDPC values (Van Der Plank 1965). Groundnut Rosette Virus Disease (GRVD) severity rating Visual assessments and scoring of GRVD severity were carried out thrice; at 30, 60 and 90 days after planting (DAP). The disease severity on each individual plant was rated using a quantitative scale adapted from Waliyar et al. (2007) as follows: no visible symptoms on leaf (highly resistant), rosette symptoms covering 1- 20% of leaf area but no obvious stunting (resistant), rosette symptoms on 21-50% area of leaf with stunting (moderately resistant), severe rosette symptoms on 51-70% area of leaf with stunting (susceptible), and severe symptoms on 71-100% area of leaf with stunting (highly susceptible). Area under the disease progress curve (AUDPC) values were calculated. Root rot This disease was scored after first appearance of plants showing rot root symptoms and subsequent scoring was done at an interval of 15 days up to 30 days after planting. Scoring was done based on visual rating scale of 0 to 3 where: 0 = clean, 1 = slight, 2 = moderate and 3 = severe (Ledingham et al. 1973). Area under the disease progress curve (AUDPC) values were calculated. Groundnut Mosaic (CABMV) Disease severity was scored using a scale of 1-5 (Adamu et al .2015) as follows: 1 = no symptoms (apparently healthy plant); 2 = mild mosaic (10-30 % infection); 3 = moderate mosaic (31-50 % infection); 4 = severe mosaic, chlorosis and stunting; (51-70 % infection); 5 = very severe mosaic, chlorosis, stunting; and plant dead (>70 % infection). Area under the disease progress curve (AUDPC) values were calculated. Leaf miner and aphids Observations on leaf miner incidence and defoliator damage were recorded regularly at 15-days interval. Observations were made on top five leaves of five randomly selected plants in each replication for number of leaflets damaged by leaf miner and extent of defoliation by defoliators. From these observations, per cent incidence of leaf miner and per cent defoliation were calculated. Agronomic data Data on selected agronomic traits were collected on plot basis. Yield data were recorded from five middle rows, excluding plants at the end of rows for each of the variety, based on number of pods per plot. All plants were clipped at the soil surface, the pods were dug up and pods were then detached, bulked together and counted. Stay green trait Starting from pod initiation to physiological maturity, visual scoring for stay-green were carried out at two-weeks intervals. The stay-green characteristic of the genotypes was scored on a scale of 1 to 5 based on the proportion of the total leaf area that had senesced with 1 being no leaf senescence and 5 completely senesced plant (Xu et. 2000). The stay green scores were used to compute the leaf area under greenness (LAUG) values (Joshi et al. 2017). Data analysis Data for each variety was summarised using descriptive statistics with means presented with respective standard error of the means. All variables were tested for normality using Shapiro-Wilk test and the strongly skewed variables were transformed prior to analyses of variance where necessary, to meet the assumption of normality and homogeneity of variances. Variables expressed as percentages (%) were arcsine-square-root (+0.5) transformed, while counts of individuals were log (log (x +1)) transformed. Where transformation was not sufficient to improve data shape, an appropriate non-parametric test was applied. The differences among varieties in yield performance was compared using analysis of variance (ANOVA), with post-hoc means separation tested using Tukey (HSD) at 5% probability level. Differences in medians of germination rate (%), growth (%), pest and disease incidence, and drought tolerance among varieties were compared using Kruskal-Wallis test, with Mann-Whitney post-hoc medians separation at 5% probability level. Site and variety interactions in growth performance, pest, and disease and drought tolerance were tested with General Linear Model (GLM) two-way analysis of variance (ANOVA). Where the GLM test indicated significant differences, post-hoc Tukey (HSD) test was used. To assess similarity among varieties, hierarchical cluster analysis using Bray-Curtis distance measure was used to depict variety performance similarity with dendrogram. Correspondence analysis ordination with symmetric scaling was used to assess associations between pest and diseases, and the various varieties. All the tests were done using PAST software (Oyvind 2002). Results Evaluation of the groundnut cultivars for yield performance The results of the evaluation of the genotypic variation among the groundnut genotypes are presented in Table 1 . The one-way ANOVA showed large and significant (P ≤ 0.05 to P ≤ 0.001) mean squares (MS) for differences between groundnut lines for yield performance. The yield of these varieties per se varied from 1,575,284 (Muddugavu) to 4545201(Erudu Red) pods per hectare, with an average yield of 2,551,235 pods/hectare, regardless of the class of groundnut variety evaluated. The combined analysis for varieties tested over two growing sites for yield showed non-significant (P > 0.05) MS for variation between classes of groundnuts (i.e., between the landraces and improved varieties (Table 2 and Table 4 ). Moreover, the yield of these varieties varied from 1,940,111 (DOK Red) to 3,143,422 (Serenut 12 R) and from 1,575,284 (Muddugavu) to 4,545,201(Erudu Red) pods per hectare, with an average yield of 2,494,851 and 2,612,317 pods/hectare for improved and landraces, respectively. Table 1 Yield performance of the 25 groundnut cultivars Accession Trait Accession Trait Improved varieties Yield (000,000) pods Landraces Yield (000,000) pods Serenut 12Red 1.91 a Mudugavu 1.58 a DOK Red 1.94 a EruduWhite 1.69 ab Serenut 8 Red 2 a Kabonge Red 1.97 abc Serenut 5 Red 2.21 ab Emoit 2.34 bcd Serenut 7 Tan 2.3 ab Otira 2.56 cd DOK Tan 2.35 abc India 2.59 cd Serenut 8 Tan 2.35 abc Kabonge White 2.6 cd Serenut 11 Tan 2.38 abc Ogwara 2.71 d Serenut 9Tan 2.42 abc Egoromoit 2.85 d Serenut 6 Tan 2.42 abc Gabon 2.95 d Serenut 10 Red 2.82 bc Kawanda Bulk 2.95 d Serenut 14 Red 2.95 c Erudu Red 4.55 e Serenut 12 Tan 3.14 bc Mean 2.39 2.58 S.E 0.04 0.05 CV(%) 67.70 73.39 Means sharing the same letter in the group label are not significantly different at the 5% level Table 2 Tests for equal means (landraces versus improved groundnut varieties t value: 3.0855 Critical t value (P = 0.05): 1.9607 p (same mean): 0.002048 UnEq. Var. t: 3.0913 p (same mean): 0.00201 Monte Carlo permutation: p (same mean): 0.0025 Evaluation of the selected groundnut varieties for growth performance The results of varietal comparisons based on growth parameters are presented in Table 3 . Significant variability (P ≤ 0.05 to P ≤ 0.001) of Kruskal-Wallis H-values for varietal trait scores between landraces and the improved was observed for all traits evaluated. The stay green index (drought tolerance) of these varieties varied from 25.1 (Serenut 8T and Serenut 12T) to 65 (Serenut 12 R) and from 25.1 (Erudu white) to 61.25 (Kabonge white), with an average of 45.36 and 48.9 for improved and landraces, respectively. Growth measured as germination percentage of these varieties varied from 50 (Serenut 8T and Serenut 12T) to 79.17 (Serenut 5 R) and from 33.3 (Erudu red) to 85.25 (Kabonge white), with an average of 66.17 and 67.85 for improved and landraces, respectively. Table 3 Comparison of growth performance of Landraces and improved varieties of groundnut Varieties Traits Drought tolerance (% based on greenness) Plant height (cm) Germination (%) Modern Varieties Serenut 14 45 ± 1.9 39.38 ± 1.4 63.75 ± 1.4 Serenut 8 Red 39.90 ± 1.7 42.42 ± 2.3 64.65 ± 1.7 Serenut 10R 47.92 ± 1.7 44.79 ± 1.5 58.33 ± 2.0 Serenut 5R 51.04 ± 2.4 52.08 ± 2.0 79.17 ± 1.6 Serenut 11 Tan 43.75 ± 1.9 49.11 ± 2.2 63.39 ± 1.6 Serenut 9 Tan 46.43 ± 2.1 49.11 ± 2.5 84.82 ± 1.0 Serenut 6 Tan 43.75 ± 2.2 40.63 ± 1.7 68.75 ± 1.6 Serenut 7 Tan 46.43 ± 2.1 45.54 ± 2.3 75 ± 1.6 Serenut 12 Red 65 ± 2.0 48.75 ± 1.5 57.5 ± 1.4 Serenut 8 Tan 25 ± 1.4 25 ± 0.6 50 ± 1.1 Serenut 12 Tan 25 ± 1.2 50 ± 0.3 50 ± 0.9 DOK Red 56.25 ± 2.6 51.56 ± 2.0 78.13 ± 1.6 DOK Tan 54.17 ± 2.8 41.67 ± 2.2 66.67 ± 1.7 Means 45.36 44.62 66.17 Landraces       India 56.25 ± 3.08 44.64 ± 2.0 79.46 ± 1.4 Otira 50 ± 2.33 39.58 ± 1.6 73.61 ± 1.3 Emoit 47.22 ± 1.63 52.08 ± 2.2 72.92 ± 1.4 Kabonge Red 56.25 ± 2.50 59.38 ± 1.1 41.67 ± 1.7 Egromoit 45.45 ± 2.0 41.48 ± 1.9 67.61 ± 1.0 Gabon 53.57 ± 2.9 46.43 ± 2.3 81.25 ± 0.9 Muddugavu 45.54 ± 2.3 44.64 ± 2.1 77.68 ± 0.9 Kabonge White 61.25 ± 3.2 56.25 ± 2.9 85.25 ± 1.5 Ogwara 47.22 ± 2.4 45.14 ± 2.0 71.53 ± 1.1 Kawanda Bulk 50 ± 1.8 40.28 ± 1.2 61.11 ± 1.3 Erudu white 25 ± 1.6 25 ± 1.0 68.75 ± 1.2 Erudu Red 50 ± 1.0 58.33 ± 0.0 33.33 ± 0.8 Means 48.98 46.10 67.85 H (chi Squared value) 197.1 262.1 767 Hc (tie corrected) 235.6 308.9 903 P (0.05) 1.151E-36 2.715E-51 3.442E-175 U-test (U, P –Value) 1.21E + 06, 0.0039 1.27E + 06, 0.8184 1.20E + 06, 0.00061 *Means sharing the same letter in the column label are not significantly different at the 5% level Evaluation of the groundnut cultivars for pest and disease reaction The results of U-test for difference in reaction to pests and diseases by improved and landrace groundnuts lines are presented in Fig. 1. Although improved varieties showed better resistance to pests and diseases (Fig. 1), the difference between landrace and improved varieties was not significant (P > 0.05). Results of association of diseases and pests with test varieties, using correspondence ordination analysis with symmetric scaling explained by principal components accounting for 65 % of total variation among the accessions, showed that the most resistant genotypes to virus diseases by graphical positioning were Gabon, Serenut 5, Serenut 14, Serenut 5, Serenut 12, Ogwara, Otira and Egoromoit (Fig. 2 and Fig. 3 ). However, all the varieties were tolerant to leafspot diseases owing to the position and separation between varieties and leaf spot diseases. Moreover, varieties such as India, Serenut 8, Serenut 6, Serenut 10, Kabonge, Mudugavu, DOR red, DOK clustered with diseases (Yellow Mosaic and Green Rosette) and their vector pests such as aphids (Fig. 3 ). However, their positioning closer to the origin and being far away from the particular diseases or pests shows they were tolerant to the diseases or pests. These correspondence ordination with symmetrical scaling for association of pests, diseases and varieties results were also supported by those from hierarchical clustering (Fig. 3 ). Generally, the genetic distances between varieties were small which can be owed to low genetic diversity in the set of varieties used in this study. Moreover, there were no specific clusters for pests and diseases of reaction for landraces or improved varieties but rather a mixture of both landraces and improved varieties (Fig. 2 and Fig. 3 ). In relation to reaction of groundnut accessions to aphids and Rosette virus disease, three clusters (I, II & III) could be identified as resistant, tolerant and susceptible, respectively (Fig. 3 ). Evaluation of growth and yield performance of groundnuts at the two study sites Results of combined analysis for growth and yield over two growing locations are presented in Table 4 and Fig. 4. Significant (P < 0.05 P 0.05) MS for yield and growth were observed for variation due to class of genotype. Significant (P < 0.05 to P < 0.001) MS due to variation in the locations (sites) were observed for all traits. The interactions MS between class and site were also significant (P < 0.05 to P < 0.001) for all the traits. Table 4 Significance of mean squares for growth and yield performance for different class groundnut accessions grown at different sites. Source of variation Df Germination Growth Drought tolerance Yield Site 1 307756 *** 1.15E + 06* 1.87E + 06 * 1.45E + 15 *** Class 1 3999.55 *** 316.179 2306.5 *** 2.70E + 12 Interaction 1 2579.87 *** 18111.7 *** 32006.2 *** 1.18E + 14 * Within 3275 298.28 Total 3278 Graphical representation of mean yield performance of improved and landraces at different growing sites is presented in Fig. 4. The interaction between site and mean genotypic performance for traits can be described as qualitative (crossover) for the case of yield and quantitative (non-crossover) for other traits (growth, drought tolerance and germination (Fig. 4). Discussion Comparison of yield performance of selected improved groundnut varieties and landraces Genetic variability of traits plays an important role in plant survival, adaptability, and can be utilised to predict the genetic gain from selection in breeding programmes. A wide range in values of yield was observed for the groundnut accessions tested in this study which confirms the existence of genetic variability for the yield traits (Upadhyaya et al. 2005; Nigram and Aruna 2008; Songsri et al. 2008; 2009, 2013). However, yield was higher in landraces compared to improved varieties. This may be explained by higher greenness index (persistence and concentration of chlorophyll in leaves) observed in landraces compared to improved varieties. A higher greenness index is associated with the ability of the crop to accumulate high biomass which is also correlated to pod yield under both stress and non-stress conditions (Koolachart et al. 2013). This observation agrees with findings of Oppong-Sekyere et al. (2019) and Kakeeto et al. (2020). Comparison of germination performance of selected improved and landraces A higher germination of seeds depends on availability of favourable environmental factors like adequate temperature, light, salinity, moisture, water (Cokkizgin 2012) and presence of seed borne pathogens (Ahmed et al. 2017). In this study, landraces performed better than improved varieties when judged in terms of germination. The difference in germination between these classes of groundnut could be related to adaptability of these lines to growing environments. This observation is supported by that of Salasya et al. (2007). Moreover, farmers are known to regenerate their seeds on a regular basis since they cannot afford other seed preservation methods. However, what cannot be explained by these results though is the known fact that seed in farmers’ hands tend to accumulate seed borne diseases (Frost et al. 2013; Gergerich et al. 2015; Thomas‐Sharma et al. 2016) which should reduce their vigour at germination and growth period. Comparison of growth parameters of selected improved varieties and landraces Growth form in groundnuts differs depending on the subspecies and botanical variety (Krapovikas and Gregory 1994). Groundnut accessions used in this study differed in their growth abilities with landraces being relatively taller than improved varieties. The difference in plant height between these classes can be attributed the sub species maintained or managed in the country’s gene pool. Most of the improved varieties used in this study belong to sub species hypogaea (virginia market types) and these are normally runners or small bush types while most of the landraces were predominantly well adapted sub species fastigiata (valencia market types) which are normally erect with potential to grow taller depending on the growing environment, including competition subjected to them by weeds or other crops in mixed cropping systems. Growth progression measured as plant height among landraces ranged from 25 to 59.4 cm while that in the modern varieties ranged from 25 to 52.1cm. Literature pertaining to differences in plant growth of landraces versus improved varieties is not well documented. However, results from studies by Kakeeto (2018) found that plant height of groundnut materials tested in Uganda varied from 15.3 to 54.6 depending on season and the botanical variety of the groundnut accession. Moreover, Salasya et al. (2007) reported that improved groundnut varieties took longer days to emerge and flower due to poor adaptation to the environment, but the landrace grew better because they were well-adapted to the environment. Comparison of drought tolerance level of selected improved groundnut varieties and landraces Stay green is an important trait that allows plants to retain their leaves in an active photosynthetic state when exposed to stress conditions (Thomas and Howarth 2000). Stay-greenness has been used as a criterion for selecting stay-green genotypes in various crops (Christopher et al. 2014; Lope and Reynolds 2012; Trachsel et al. 2016; Borrell et al. 2014). We report significant variation in the stay green trait among landraces and improved varieties with the former maintaining greenness for a longer time compared to latter. This is in contradiction to the findings by Oppong-Sekyere et al. (2019) who found improved varieties to have higher chlorophyll concentration than landraces over well-watered and water-stressed conditions. Reaction of selected improved groundnut varieties and landraces to natural pest and disease infestations Another important selection criterion used by groundnut producers is the pests and disease reaction (Okello et al. 2010, 2014, Mugisa et al. 2015, Kakeeto et al. 2018). The reaction of groundnut varieties to pests and diseases didn’t significantly differ between landraces and improved varieties, even though incidence of pests and diseases was lower on improved varieties. These results corroborate those of Kakeeto et al. (2018) where farmers selected improved varieties over landraces for their pest and disease resistance. However, these results contradict those of Aina et al. (2011) who reported that landraces had better tolerance to CMD and CBB diseases compared to improved varieties of cassava. Results from similarity clustering showed that clustering was not based on groupings as landrace or improved variety but rather a combination of both improved and landraces. Moreover, these combinations had unique associations with particular pests and diseases. These results imply that choice of a resistant groundnut variety shouldn’t be informed by their grouping as landraces or improved varieties, but on associations identified between individual varieties and pest/diseases that have to be considered when making selections for breeding pipe lines or target production environments (high disease pressure vs low disease pressure) growing areas. Effect of significant GE interaction on performance of selected improved groundnut varieties and landraces Genotype environment interaction exists whenever the relative phenotypic performance of genotypes varies with the environment. Significant G x E interactions were observed in all characters studied for both landraces and improved varieties. Several research groups have also reported similar results (Mothilal et al. 2010; Songsri et al. 2008; Minde et al. 2017; Aina et al. 2011). In this study, both crossover and non-cross over GE were observed. Significance of GE has serious implications for deployment of varieties (Kang 1993). While non-crossover GE can be exploited by improving the growing environment, the crossover GE calls for selection and deployment of specifically adapted varieties. Cross- over GE was only observed for yield implying that high performers from both improved and landraces could be specifically deployed in the respective sites. On the other hand, non-cross over GE could be overcome by modifying the production sites. Related to this recommendation, biophysical description of the two sites indicates that although Nakaseke site has better conditions for crop growth, Nakasongola has the largest share of locations suitable for groundnut production; which also confirms the inherent drought tolerant nature of this crop (Erickson and Ketring 1985; Reddy et al. 2003). Therefore, strategies such as irrigation, use of conservation agriculture, and adoption of drought tolerant varieties could boost performance of both improved varieties and landraces in Nakasongola. Conclusion The current study aimed to explore the presence of genetic and geographic structures in a collection of groundnuts representing the existing variability for this species in the Ugandan gene pool. There were no clear structures for either landraces or improved varieties with respect to the traits investigated. The differences or similarities observed could largely be explained by the genetic pools managed by the breeding programmes operating in the country and those in the hands of farmers coupled with differences in the target growing environments. The results reported in the current study may be used to facilitate development of new cultivars building on inherent strengths of both well adapted landraces and improved varieties with desirable traits thus the need to conserve these varieties for sustainable use. Declarations Conflicts of Interest/competing interests The authors declare no conflicts of interest. The sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results. Data Availability of data and materials Data used to support these findings can be sourced from the corresponding author. The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. Code Availability The analysis code can be accessed from corresponding author Authors’ Contribution: NA Ethics approval: NA Consent to participate: NA Consent for publication: NA Acknowledgments We thank the site teams and the farmers of the Nakaseke and Nakasongola sites for their participation in the research on which the paper is based. References Adamu AS, Salaudeen MT, Gana AS, Ishaq MN (2015) Response of selected soybean (Glycine max [L.] Merr.) lines to Cucumber mosaic virus disease in Minna, Niger State. Nig J Agric Food Environ 11(4):45–51 Ahmed O, Olayika BU, Garuba T, Ahmed J, Etejere EO (2017) Germination of several groundnut cultivars in relation to incidence of fungi. 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Plant Pathol 65:3–16 Trachsel S, Sun D, SanVicente FM et al (2016) “Identification of QTL for early vigor and stay-green conferring tolerance to drought in two connected advanced backcross populations in tropical maize ( Zea mays L.),” PLoS One , vol. 11, no. 3, Article ID e0149636 Trachsel S, Sun D, SanVicente FM et al (2016) “Identification of QTL for early vigor and stay-green conferring tolerance to drought in two connected advanced backcross populations in tropical maize ( Zea mays L.),” PLoS One , vol. 11, no. 3, Article ID e0149636 Upadhyaya HD (2005) Variability for drought resistance related traits in the mini core collection of peanuts. Crop Sci 45:1432–1440 Van Der Plank JE (1965) Dynamics of epidemics of plant disease. International Journal of Pest Management: Part B 11(3):307–317 Villa TCC, Maxted N, Scholten M, Ford-Lloyd B (2005) Defining and identifying crop landraces. Plant Genet Resour 3, 373–384. doi: 10.1079/ PGR200591 Waliyar F (1991) Evaluation of yield losses due to groundnut leaf diseases in West Africa. Summary proceedings of the second ICRISAT regional groundnut meeting for west Africa, 11–14 Sep 1990, ICRISAT Sahelian Centre, Niamey, Niger. Patancheru 502 324, Andhra Pradesh, India: ICRISAT, pp 32–33 Wood AJ, Roper J (2000) A Simple and Nondestructive Technique for Measuring Plant Growth and Development. American Biology Teacher v62:n3 p215–17 Xu W, Rosenow DT, Nguyen HT (2000) Stay green trait in grain sorghum: relationship between visual rating and leaf chlorophyll concentration. Plant Breeding 119(4):365–367 Yates F, Cochran WG (1938) The analysis of groups of experiments. J Agric Sci 28:556–580 Zeven AC (1998) Landraces: A review of definitions and classifications. 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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-696706","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":42446817,"identity":"3ae1d289-5294-43e8-9359-3bb32519adf1","order_by":0,"name":"John W Mulumba","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYBACxgYg8YCBIYGBvYGBmXgtCSDEc4BILWAA1iKRQKQW5hnZaRKJbdvy+Ge+MfxcUGHDwN/enYDfYTNytwG13C6WuJ1jLD3jTBqDxJmzG/BrmQ3RkthwO8dAmrftMIOBRC6RWubfPGP8mzQtG27wmBFpy/y3my0Szt0uNjyTVmbNcyaNh6BfDHvObrzxoex2ntzxw5tv81TYyPG39xLQ0gBnchiASB68ykFAHsFkf0BQ9SgYBaNgFIxMAACaLUxDuM3xbgAAAABJRU5ErkJggg==","orcid":"","institution":"National Agricultural Research Organisation","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"John","middleName":"W","lastName":"Mulumba","suffix":""},{"id":42446818,"identity":"96ea391b-57c5-40f7-982a-6badb31a82e9","order_by":1,"name":"Ronald Kakeeto","email":"","orcid":"","institution":"National Semi arid Resources Research 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pests","description":"","filename":"fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-696706/v1/880a866db794a4de74d4c5df.png"},{"id":11969034,"identity":"7d95e38b-d75e-468f-922e-12f27476d0e7","added_by":"auto","created_at":"2021-07-30 18:54:27","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":58729,"visible":true,"origin":"","legend":"Correspondence ordination with symmetrical scaling for association of pests, diseases and varieties","description":"","filename":"fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-696706/v1/13035a2bdc343d624184b695.png"},{"id":11969215,"identity":"eb0e61c2-c717-4879-b23c-70c4bd0ef8d1","added_by":"auto","created_at":"2021-07-30 18:57:27","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":65473,"visible":true,"origin":"","legend":"Hierarchical clustering using distance matrices showing similarities between varieties in relation to aphids and Rosette virus disease reaction","description":"","filename":"fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-696706/v1/63c5a285018854fef939f2c1.png"},{"id":11969037,"identity":"81feab2c-73c0-4f6b-ad9c-53e846e19604","added_by":"auto","created_at":"2021-07-30 18:54:27","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":99796,"visible":true,"origin":"","legend":"Genotype-by-environment interaction in terms of changing mean performances across environments: (A) Yield, (B) Growth, (C) Drought tolerance, (D) Germination ","description":"","filename":"fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-696706/v1/af5e32016153060d7e0d45f9.png"},{"id":13708005,"identity":"24c826ed-75d2-4c26-8fae-63b7afbbd975","added_by":"auto","created_at":"2021-09-17 14:05:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5152677,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-696706/v1/2827bd58-2f7e-48af-92f6-4c2ad6931be7.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eComparative Evaluation of Agronomic Performance of Selected Landraces And Improved Groundnuts Cultivars In Central Uganda\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGroundnut (\u003cem\u003eArachis hypogaea\u003c/em\u003e L.) is an economically valuable oilseed and cash crop grown extensively in the semi-arid tropical regions of the world. It is cultivated for direct consumption as food and for industrial use. Production of the crop is concentrated primarily in the semi-arid tropical regions of Asia and Africa, which together account for over 96% of world groundnut area and 92% of total global groundnut output. In Uganda, groundnut is the second most important legume after common bean (Okello et al. \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e; \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). Besides being a major food crop, it also represents a significant source of income, thus contributing to improved livelihoods. Groundnut seeds contain 40\u0026ndash;50 % high quality edible oil, 20\u0026ndash;50% easily digestible protein and 10\u0026ndash;20% carbohydrate depending on variety. Groundnut is also a nutritional source of vitamin E, niacin, falacin, calcium, phosphorous, magnesium, zinc, iron, riboflavin, thiamine and potassium (Savage and Keenan \u003cspan class=\"CitationRef\"\u003e1994\u003c/span\u003e). This makes groundnut an important source of nutrition in the country. In Uganda, groundnut is grown in diverse environments; and also utilized in various ways leading to diversity in variety preferences for this crop.\u003c/p\u003e\n\u003cp\u003eMost literature on seed supply systems for crop varieties often refers to seeds as either \u0026lsquo;modern varieties\u0026rsquo; or \u0026lsquo;landraces\u0026rsquo;. While a \u0026lsquo;modern variety\u0026rsquo; is understood to be a variety that is improved by a formal breeding programme (Morris et al. \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e), released under a registered name and differing from other varieties by distinctive properties for which it is uniform and breeds true, a \u0026ldquo;landrace\u0026rdquo; is defined as dynamic population of a cultivated plant with a historical origin, distinct identity, often genetically diverse and locally adapted, and associated with a set of farmers\u0026rsquo; practices of seed selection and field management as well as with a farmers\u0026rsquo; knowledge base (Villa et al. \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e). The main contributions of landraces to plant breeding have been traits for adaptation to stressful environments such as water stress, salinity, low-input farming system, high temperatures and several biotic stresses such as pests and diseases ( Zeven \u003cspan class=\"CitationRef\"\u003e1998\u003c/span\u003e; Paterniani et al. \u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e; Sharma et al. \u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e; Ara\u0026uacute;jo et al. 2002; Kashiwagi et al. \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e; Herzberg et al. 2004; Futakuchi et al. \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e) as well as useful genes for nutrient dense foods. As such, they act as useful starting materials for variety development strategies carried out at present and also for future use. In addition, a more efficient use of plant genetic diversity has been identified as a prerequisite for meeting the challenges of development, food security and poverty alleviation (FAO \u003cspan class=\"CitationRef\"\u003e1996\u003c/span\u003e). Therefore, it is of great importance to conserve and maintain a broad base of germplasm because they constitute valuable genetic resources for multiple desirable traits within the country\u0026rsquo;s groundnut gene pool.\u003c/p\u003e\n\u003cp\u003eIn Uganda, groundnut production is characterized by resource-constrained small-scale farmers who cannot afford inputs such as improved seed and fertilisers and, therefore rely on fellow farmers, farmer groups, local markets, NGOs and research organisations for these inputs (Mugisha et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). Given the lack of capital resources, the farmers are left with no option but to resort to using traditional farming methods with low levels of mechanisation, and many a time with varieties which compromise yields of the crop despite the existence of a wide range of varietal choice ranging from well adapted, but not readily available traditional varieties (due to lack of entry point into the formal seed system) to a number of released varieties which have been improved for several traits.\u003c/p\u003e\n\u003cp\u003eSeveral pests and diseases attack groundnuts leading to reduction of yields and lowering the quality of produce hence increasing the cost of production. The major diseases of groundnuts include: Rosette caused by a complex of three viruses namely; Groundnut Rosette Virus (GRV), Groundnut Rosette Assistor Virus (GRAV) and satellite RNA (satRNA) transmitted by a single species of aphid (\u003cem\u003eAphis craccivora\u003c/em\u003e Koch); Early Leaf Spot (\u003cem\u003eCercospora arachidicola\u003c/em\u003e); Late Leaf Spot (\u003cem\u003ePhaeoisariopis personata\u003c/em\u003e); Root Rot; Mosaic; Rust (\u003cem\u003ePuccinia arachids\u003c/em\u003e) and aflatoxin contamination (caused by \u003cem\u003eAspergillus niger\u003c/em\u003e and \u003cem\u003eAspergillus flavus\u003c/em\u003e). The Groundnut Rosette Virus Disease (GRVD) is considered the most important constraint and can cause losses of up 100% if it occurs before flowering (Okello et al. \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e; Nigam et al. \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe important pests of groundnut are aphids (\u003cem\u003eAphis craccivora\u003c/em\u003e Koch), a vector of groundnut rosette disease, leaf miner (\u003cem\u003eAproarema modicella\u003c/em\u003e Deventer), thrips (\u003cem\u003eThrips palmi\u003c/em\u003e Karny, \u003cem\u003eFrankiniella schultzie\u003c/em\u003e Trybom, \u003cem\u003eScirtothrips dorsalis\u003c/em\u003e Hood) and termites (Isoptera) (Okello et al. \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e; Okello et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). Thrips and aphids are considered more important as vectors of viruses than as causing direct damage to groundnuts. In addition, the Groundnut Leaf Miner, a Lepidopteran defoliator was reported as an emerging threat to groundnut production areas in Uganda, especially those areas prone to drought (Mukankusi et al. \u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e; Okello et al. \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eAs groundnut is grown in predominantly semi-arid regions characterized by erratic rainfall and on predominantly loose sandy loam soils, drought is often a recurring production constraint. This situation also coincides with the climate change phenomenon which projects disturbances such as a decrease in the lengths of the rainy seasons especially in semi-arid tropics (SAT) where most groundnuts are grown (Pasupuleti and Nigam \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). In addition, drought has significant implications on groundnut quality which undermines the value of groundnut products on local, regional and international markets.\u003c/p\u003e\n\u003cp\u003eThe foregoing constraints notwithstanding, the success of a plant breeding program is anchored upon its ability to provide farmers with genotypes with guaranteed superior performance (phenotype) in terms of yield and/or quality across a range of environmental conditions. To achieve this aim, it is necessary to have an understanding of the factors leading to a good phenotype. Generally, the phenotype is the value for a trait at the end of the growing season, e. g kernel weight at maturity, and is the cumulative result of a number of continuous interactions between the genetic make-up of the plant (the genotype) and the conditions or stimuli in which that plant developed (the environment) and this varies from plant to plant.\u003c/p\u003e\n\u003cp\u003eEnvironments differ in the amount and quality of inputs and stimuli that they convey to plants including, e.g., the amount of water, nutrients or incoming radiation. The primary objective in plant breeding is to match genotypes and environments in such a way that improved phenotypes are obtained. As quantitatively inherited trait, seed yield performance of a genotype often varies from one environment to another, leading to a significant genotype by environment (GxE) interaction which can severely limit gain of selecting superior genotypes. Understanding the interaction of those factors and how they affect seed yield is crucial for maintaining high yield (David et al. \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). It is acknowledged that there can be genotypes that do well across a wide range of conditions (widely adapted genotypes), but there are also genotypes that do relatively better than others exclusively under a restricted set of conditions (specifically adapted genotypes). Specific adaptation of genotypes is closely related to the phenomenon of genotype-by environment interaction (GEI). GEI exists whenever the relative phenotypic performance of genotypes depends on the environment, or in other words, when the difference in reactions of genotypes varies with the environment. Some scenarios that can occur when comparing the performances of pairs of genotypes across environments are presented in \u003cstrong\u003eFig.\u0026nbsp;1\u003c/strong\u003e. The function describing the phenotypic performance of a genotype in relation to an environmental characterization is called the \u0026ldquo;norm of reaction\u0026rdquo; (Griffithsetal.1996). Figure\u0026nbsp;1A shows the case where there is no GEI, the genotype and the environment behave additively and the reaction norms are parallel. The remaining plots show different situations in which GEI occurs: divergence (Fig.\u0026nbsp;1B), convergence (Fig.\u0026nbsp;1C), and the most critical one, cross over interaction (Fig.\u0026nbsp;1D). Cross over interactions are the most important for breeders as they imply that the choice of the best genotype is determined by the environment.\u003c/p\u003e\n\u003cp\u003eTherefore, given the complexity of the mechanisms and processes underlying the phenotypic response across diverse and changing environmental conditions, several analytical tools have been developed to help breeders understand GEI (Yates and Cochran \u003cspan class=\"CitationRef\"\u003e1938\u003c/span\u003e; Finlay and Wil- kinson 1963; Eberhart and Russell \u003cspan class=\"CitationRef\"\u003e1966\u003c/span\u003e; Gauch \u003cspan class=\"CitationRef\"\u003e1988\u003c/span\u003e; Singh et al. \u003cspan class=\"CitationRef\"\u003e1996b\u003c/span\u003e) among others. The use of adequate strategies to analyze GEI is a first and important step toward more informed breeding decisions but details of how these tools are used is beyond the scope of this study. However, in finding workable solutions to limited information on performance of commonly grown groundnut landraces and improved varieties for guiding selection of groundnut varieties by different user groups (farmers, breeders and other users), the specific objectives of this study therefore were; (i) to interpret genotype (G), Class (Landrace and improved varieties) and Site (E) main effects and GE interaction for growth, pests and disease reaction, and yield performances of 23 groundnut genotypes evaluated in two growing sites (ii) Explore the nature of GE interaction and suggest strategies for exploiting it for improved targeting of varieties to different growing sites.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003e\u003cstrong\u003eSite description\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was carried out in the Central Wooded Savanna ecological zone of Uganda, in Nakaseke (0\u0026deg;43\u0026rsquo;29\u0026rdquo; N, 32\u0026deg; 54\u0026rsquo;04\u0026rdquo; E) and Nakasongola (1\u0026deg;18\u0026rsquo;32\u0026rdquo; N, 32\u0026deg; 27\u0026rsquo;23\u0026rdquo;E) districts. \u0026nbsp;In Nakasongola, the annual daily temperatures range from 18\u003csup\u003eo\u003c/sup\u003eC to 35\u003csup\u003eo\u003c/sup\u003eC, with mean daily maximum of 30\u0026deg;C. Rainfall ranges between 500 to 1000 mm per annum and there are two rain seasons. The vegetation in the study site mainly comprises three vegetation cover types depending on the extent of anthropogenic activities/disturbance on specific ranch sites. The three vegetation cover types include dense vegetation cover (\u0026gt;50% basal\u0026nbsp;cover), sparse vegetation cover (25 to 50% basal cover) and bare ground. The area is characterized by prolonged droughts and floods due to shifting rainfall pattern (Nimusiima \u003cem\u003eet\u003c/em\u003e \u003cem\u003eal\u003c/em\u003e. 2013). Hitherto dominated by livestock\u0026nbsp;grazing, the area is increasingly changing in land use, with\u0026nbsp;crop farming especially for maize production becoming common. The altitudinal range is 600-1160msl.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNakaseke site has traditionally been described as the coffee\u0026ndash;banana farming system. This area falls within an altitudinal range of 1086\u0026ndash;1280 masl, with mean annual rainfall of up to 1100 mm. The annual daily temperatures range from 16 ◦C to 30 ◦C.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBi-modal rainfall distribution characterizes the two districts with the first rainy season extending from March to June, while the second rainy season starts in late August or early September to November-December (Ogwang \u003cem\u003eet al\u003c/em\u003e.2016). The main rain season occurs from March-April to June July while the second rain season follows from August to October November. A long dry season occurs from December to February while a short spell comes around July-August.\u003c/p\u003e\n\u003cp\u003eTrial gardens were established in two districts of Nakasongola and Nakaseke, each district taken as a site. In each site replication was done in four villages. In Nakaseke trial gardens were established in the villages of Kiziba, Namirali, Kalagala and Kyamutakasa while in Nakasongola they were established in Naitondo, Kasambya, Kalobokwe and Kiralamba (Figure 1 \u0026amp; Figure 2)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eField layout\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwenty-three groundnut varieties were planted in each site. The varieties included improved and farmer local varieties. The seeds for the improved varieties were sourced from the National Agricultural Semi-Arid Resources Research institute (NASARRI) while the farmer local varieties were from farmers in Amuria district. Each variety was planted to a single plot of 3 m x 4 m and at a plot-plot spacing of 1m with a plant population of 300 plants. A row to row spacing of 40 cm, and plant to plant spacing of 10 cm was used. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData was taken on common groundnut diseases and pests. The diseases included; Groundnut Rosette, Leaf Spot, Root-rot, and Groundnut Mosaic while the pests included aphids and leaf minor. Disease and pest incidences were assessed (at 1, 2 and 3 months after planting by counting the number of plants affected per variety (NaSARRI, unpublished). In addition, plant growth performance was assessed by measuring plant height while germination uniformity was scored 2 weeks from germination (Wood and Roper, 2000). \u0026nbsp;Using a scale of 1 to 4, where 1= poor and 4 = very good performance. Stay green as a measure of drought tolerance was also evaluated using a scale of 1 to 4 which were subsequently converted to percentages. \u0026nbsp;Yield was assessed in terms of number of pods per plant measured on twenty selected plants from five middle rows per plot for each variety\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisease scores\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLeaf spot (Early and late leaf spot disease)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach leaf spot disease was scored separately using 1-9 scale on periodic basis after first appearance of the disease and subsequent scoring was done at an interval of 15 days and stopped at 20 days before harvest. Leaf spot was recorded using 9-point scale as described below (Subrahmanyam, P. \u003cem\u003eet al\u003c/em\u003e. 1995).\u0026nbsp;The severity scores were used to compute the area under disease progress curve AUDPC values (Van Der Plank 1965).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGroundnut Rosette Virus Disease (GRVD) severity rating\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVisual assessments and scoring of GRVD severity were carried out thrice; at 30, 60 and 90 days after planting (DAP). The disease severity on each individual plant was rated using a quantitative scale adapted from Waliyar et al. (2007) as follows: no visible symptoms on leaf (highly resistant), rosette symptoms covering 1- 20% of leaf area but no obvious stunting (resistant), rosette symptoms on 21-50% area of leaf with stunting (moderately resistant), severe \u0026nbsp;rosette symptoms on 51-70% area of \u0026nbsp;leaf with stunting (susceptible), and severe symptoms on 71-100% area of leaf with stunting (highly susceptible). \u0026nbsp;Area under the disease progress curve (AUDPC) values were calculated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRoot rot\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis disease was scored after first appearance of\u0026nbsp;plants showing rot root symptoms\u0026nbsp;and subsequent scoring was done at an interval of 15 days up to 30 days after planting. Scoring was done\u0026nbsp;based on visual rating scale of 0 to 3 where: 0 = clean, 1 = slight, 2 = moderate and 3 = severe (Ledingham et al. 1973).\u0026nbsp;Area under the disease progress curve (AUDPC) values were calculated.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGroundnut Mosaic (CABMV)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDisease severity was scored using a scale of 1-5 (Adamu \u003cem\u003eet al\u003c/em\u003e.2015) as follows: 1 = no symptoms (apparently healthy plant); 2 = mild mosaic (10-30 % infection); 3 = moderate mosaic (31-50 % infection); 4 = severe mosaic, chlorosis and stunting; (51-70 % infection); 5 = very severe mosaic, chlorosis, stunting; and plant dead (\u0026gt;70 % infection).\u0026nbsp;Area under the disease progress curve (AUDPC) values were calculated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLeaf miner and aphids\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eObservations on leaf miner incidence and defoliator damage were recorded regularly at 15-days interval. Observations were made on top five leaves of five randomly selected plants in each replication for number of leaflets damaged by leaf miner and extent of defoliation by defoliators. From these observations, per cent incidence of leaf miner and per cent defoliation were calculated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAgronomic data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData on selected agronomic traits were collected on plot basis. Yield data were recorded from five middle rows, excluding plants at the end of rows for each of the variety, based on number of pods per plot. All plants were clipped at the soil surface, the pods were dug up and pods were then detached, bulked together and counted.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStay green trait\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStarting from pod initiation to physiological maturity, visual scoring for stay-green were carried out at two-weeks intervals. The stay-green characteristic of the genotypes was scored on a scale of 1 to 5 based on the proportion of the total leaf area that had senesced with 1 being no leaf senescence and 5 completely senesced plant (Xu et. 2000). The stay green scores were used to compute the leaf area under greenness (LAUG) values (Joshi et al. 2017).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData for each variety was summarised using descriptive statistics with means presented with respective standard error of the means. All variables were tested for normality using Shapiro-Wilk test and the strongly skewed variables were transformed prior to analyses of variance where necessary, to meet the assumption of normality and homogeneity of variances. Variables expressed as percentages (%) were arcsine-square-root (+0.5) transformed, while counts of individuals were log (log (x +1)) transformed. Where transformation was not sufficient to improve data shape, an appropriate non-parametric test was applied. The differences among varieties in yield performance was compared using analysis of variance (ANOVA), with post-hoc means separation tested using Tukey (HSD) at 5% probability level. Differences in medians of germination rate (%), growth (%), pest and disease incidence, and drought tolerance among varieties were compared using Kruskal-Wallis test, with Mann-Whitney post-hoc medians separation at 5% probability level. Site and variety interactions in growth performance, pest, and disease and drought tolerance were tested with General Linear Model (GLM) two-way analysis of variance (ANOVA). Where the GLM test indicated significant differences, post-hoc Tukey (HSD) test was used. To assess similarity among varieties, hierarchical cluster analysis using Bray-Curtis distance measure was used to depict variety performance similarity with dendrogram. Correspondence analysis ordination with symmetric scaling was used to assess associations between pest and diseases, and the various varieties. All the tests were done using PAST software (Oyvind 2002).\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv class=\"Section2\" id=\"Sec16\"\u003e\n \u003cp\u003e\u003cstrong\u003eEvaluation of the groundnut cultivars for yield performance\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe results of the evaluation of the genotypic variation among the groundnut genotypes are presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The one-way ANOVA showed large and significant (P\u0026thinsp;\u0026le;\u0026thinsp;0.05 to P\u0026thinsp;\u0026le;\u0026thinsp;0.001) mean squares (MS) for differences between groundnut lines for yield performance. The yield of these varieties \u003cem\u003eper se\u003c/em\u003e varied from 1,575,284 (Muddugavu) to 4545201(Erudu Red) pods per hectare, with an average yield of 2,551,235 pods/hectare, regardless of the class of groundnut variety evaluated.\u003c/p\u003e\n \u003cp\u003eThe combined analysis for varieties tested over two growing sites for yield showed non-significant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) MS for variation between classes of groundnuts (i.e., between the landraces and improved varieties (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Moreover, the yield of these varieties varied from 1,940,111 (DOK Red) to 3,143,422 (Serenut 12 R) and from 1,575,284 (Muddugavu) to 4,545,201(Erudu Red) pods per hectare, with an average yield of 2,494,851 and 2,612,317 pods/hectare for improved and landraces, respectively.\u003c/p\u003e\n \u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eYield performance of the 25 groundnut cultivars\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eAccession\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003eTrait\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 20.6322%;\"\u003e\n \u003cp\u003eAccession\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTrait\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eImproved varieties\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003eYield\u003c/p\u003e\n \u003cp\u003e(000,000) pods\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\n \u003cp\u003eLandraces\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYield\u003c/p\u003e\n \u003cp\u003e(000,000) pods\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eSerenut 12Red\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e1.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\n \u003cp\u003eMudugavu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ea\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eDOK Red\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\n \u003cp\u003eEruduWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eSerenut 8 Red\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\n \u003cp\u003eKabonge Red\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eabc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eSerenut 5 Red\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\n \u003cp\u003eEmoit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebcd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eSerenut 7 Tan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\n \u003cp\u003eOtira\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eDOK Tan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e2.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eabc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eSerenut 8 Tan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e2.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eabc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\n \u003cp\u003eKabonge White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eSerenut 11 Tan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eabc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\n \u003cp\u003eOgwara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eSerenut 9Tan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eabc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\n \u003cp\u003eEgoromoit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eSerenut 6 Tan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eabc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\n \u003cp\u003eGabon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eSerenut 10 Red\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e2.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\n \u003cp\u003eKawanda Bulk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eSerenut 14 Red\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ec\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\n \u003cp\u003eErudu Red\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ee\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eSerenut 12 Tan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e3.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ebc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e2.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eS.E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 24.6257%;\"\u003e\n \u003cp\u003eCV(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.6638%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 19.8004%;\"\u003e\n \u003cp\u003e67.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4975%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 20.6322%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 1.4976%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003eMeans sharing the same letter in the group label are not significantly different at the 5% level\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eTests for equal means (landraces versus improved groundnut varieties\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003et value:\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e3.0855\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCritical t value (P\u0026thinsp;=\u0026thinsp;0.05):\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9607\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep (same mean):\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnEq.\u0026nbsp;Var. t:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0913\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep (same mean):\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00201\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonte Carlo permutation:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep (same mean):\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cstrong\u003eEvaluation of the selected groundnut varieties for growth performance\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eThe results of varietal comparisons based on growth parameters are presented in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. Significant variability (P\u0026thinsp;\u0026le;\u0026thinsp;0.05 to P\u0026thinsp;\u0026le;\u0026thinsp;0.001) of Kruskal-Wallis H-values for varietal trait scores between landraces and the improved was observed for all traits evaluated. The stay green index (drought tolerance) of these varieties varied from 25.1 (Serenut 8T and Serenut 12T) to 65 (Serenut 12 R) and from 25.1 (Erudu white) to 61.25 (Kabonge white), with an average of 45.36 and 48.9 for improved and landraces, respectively. Growth measured as germination percentage of these varieties varied from 50 (Serenut 8T and Serenut 12T) to 79.17 (Serenut 5 R) and from 33.3 (Erudu red) to 85.25 (Kabonge white), with an average of 66.17 and 67.85 for improved and landraces, respectively.\u003c/p\u003e\n\u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of growth performance of Landraces and improved varieties of groundnut\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003eVarieties\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 40.164%;\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" style=\"width: 38.2434%;\"\u003e\n \u003cp\u003eTraits\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrought tolerance\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(% based on greenness)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlant height (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGermination (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModern Varieties\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003eSerenut 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e39.38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e63.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003eSerenut 8 Red\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e39.90\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e42.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e64.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003eSerenut 10R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e47.92\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e44.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e58.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003eSerenut 5R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e51.04\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e52.08\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e79.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003eSerenut 11 Tan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e43.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e49.11\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e63.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003eSerenut 9 Tan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e46.43\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e49.11\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e84.82\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003eSerenut 6 Tan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e43.75\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e40.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e68.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003eSerenut 7 Tan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e46.43\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e45.54\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003eSerenut 12 Red\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e48.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e57.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003eSerenut 8 Tan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003eSerenut 12 Tan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003eDOK Red\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e56.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e51.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e78.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003eDOK Tan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e54.17\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e41.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e66.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeans\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 40.164%;\"\u003e\n \u003cp\u003e45.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 16.6507%;\"\u003e\n \u003cp\u003e44.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1568%;\"\u003e\n \u003cp\u003e66.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLandraces\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e56.25\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e44.64\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e79.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eOtira\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e39.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e73.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eEmoit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e47.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e52.08\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e72.92\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eKabonge Red\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e56.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e59.38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e41.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eEgromoit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e45.45\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e41.48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e67.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eGabon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e53.57\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e46.43\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e81.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eMuddugavu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e45.54\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e44.64\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e77.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eKabonge White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e61.25\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e56.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e85.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eOgwara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e47.22\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e45.14\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e71.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eKawanda Bulk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e40.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e61.11\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eErudu white\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e68.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eErudu Red\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e58.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e33.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eMeans\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e48.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e46.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e67.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eH (chi Squared value)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e197.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e262.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e767\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eHc (tie corrected)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e235.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e308.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e903\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eP (0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e1.151E-36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e2.715E-51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e3.442E-175\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 21.3805%;\"\u003e\n \u003cp\u003eU-test (U, P \u0026ndash;Value)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 39.9056%;\"\u003e\n \u003cp\u003e1.21E\u0026thinsp;+\u0026thinsp;06, 0.0039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.0022%;\"\u003e\n \u003cp\u003e1.27E\u0026thinsp;+\u0026thinsp;06, 0.8184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.2826%;\"\u003e\n \u003cp\u003e1.20E\u0026thinsp;+\u0026thinsp;06, 0.00061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 90.1501%;\"\u003e*Means sharing the same letter in the column label are not significantly different at the 5% level\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eEvaluation of the groundnut cultivars for pest and disease reaction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of U-test for difference in reaction to pests and diseases by improved and landrace groundnuts lines are presented in Fig.\u0026nbsp;1. Although improved varieties showed better resistance to pests and diseases (Fig.\u0026nbsp;1), the difference between landrace and improved varieties was not significant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cp\u003eResults of association of diseases and pests with test varieties, using correspondence ordination analysis with symmetric scaling explained by principal components accounting for 65 % of total variation among the accessions, showed that the most resistant genotypes to virus diseases by graphical positioning were Gabon, Serenut 5, Serenut 14, Serenut 5, Serenut 12, Ogwara, Otira and Egoromoit (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). However, all the varieties were tolerant to leafspot diseases owing to the position and separation between varieties and leaf spot diseases. Moreover, varieties such as India, Serenut 8, Serenut 6, Serenut 10, Kabonge, Mudugavu, DOR red, DOK clustered with diseases (Yellow Mosaic and Green Rosette) and their vector pests such as aphids (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). However, their positioning closer to the origin and being far away from the particular diseases or pests shows they were tolerant to the diseases or pests.\u003c/p\u003e\n\u003cp\u003eThese correspondence ordination with symmetrical scaling for association of pests, diseases and varieties results were also supported by those from hierarchical clustering (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Generally, the genetic distances between varieties were small which can be owed to low genetic diversity in the set of varieties used in this study. Moreover, there were no specific clusters for pests and diseases of reaction for landraces or improved varieties but rather a mixture of both landraces and improved varieties (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). In relation to reaction of groundnut accessions to aphids and Rosette virus disease, three clusters (I, II \u0026amp; III) could be identified as resistant, tolerant and susceptible, respectively (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"Section2\" id=\"Sec18\"\u003e\n \u003cp\u003e\u003cstrong\u003eEvaluation of growth and yield performance of groundnuts at the two study sites\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eResults of combined analysis for growth and yield over two growing locations are presented in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig. 4. Significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) MS for drought tolerance and germination but non-significant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) MS for yield and growth were observed for variation due to class of genotype. Significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 to P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) MS due to variation in the locations (sites) were observed for all traits. The interactions MS between class and site were also significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 to P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) for all the traits.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab5\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSignificance of mean squares for growth and yield performance for different class groundnut accessions grown at different sites.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSource of variation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDf\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGermination\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGrowth\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDrought tolerance\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYield\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e307756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.15E\u0026thinsp;+\u0026thinsp;06*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.87E\u0026thinsp;+\u0026thinsp;06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.45E\u0026thinsp;+\u0026thinsp;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3999.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e316.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2306.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.70E\u0026thinsp;+\u0026thinsp;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInteraction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2579.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18111.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32006.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.18E\u0026thinsp;+\u0026thinsp;14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWithin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e298.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eGraphical representation of mean yield performance of improved and landraces at different growing sites is presented in Fig.\u0026nbsp;4. The interaction between site and mean genotypic performance for traits can be described as qualitative (crossover) for the case of yield and quantitative (non-crossover) for other traits (growth, drought tolerance and germination (Fig.\u0026nbsp;4).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003eComparison of yield performance of selected improved groundnut varieties and landraces\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGenetic variability of traits plays an important role in plant survival, adaptability, and can be utilised to predict the genetic gain from selection in breeding programmes. \u0026nbsp;A wide range in values of yield was observed for the groundnut accessions tested in this study which confirms the existence of genetic variability for the yield traits (Upadhyaya et al. 2005; Nigram and Aruna 2008; Songsri et al. 2008; 2009, 2013). However, yield was higher in landraces compared to improved varieties. This may be explained by higher greenness index (persistence and concentration of chlorophyll in leaves) observed in landraces compared to improved varieties. A higher greenness index is associated with the ability of the crop to accumulate high biomass which is also correlated to pod yield under both stress and non-stress conditions (Koolachart et al. 2013). This observation agrees with findings of Oppong-Sekyere et al. (2019) and Kakeeto et al. (2020). \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of germination performance of selected improved and landraces\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA higher germination of seeds depends on availability of favourable environmental factors like adequate temperature, light, salinity, moisture, water (Cokkizgin 2012) and presence of seed borne pathogens (Ahmed et al. 2017). In this study, landraces performed better than improved varieties when judged in terms of germination. The difference in germination between these classes of groundnut could be related to adaptability of these lines to growing environments. This observation is supported by that of Salasya et al. (2007). Moreover, farmers are known to regenerate their seeds on a regular basis since they cannot afford other seed preservation methods. \u0026nbsp;However, what cannot be explained by these results though is the known fact that seed in farmers\u0026rsquo; hands tend to accumulate seed borne diseases (Frost et al. 2013; Gergerich et al. 2015; Thomas‐Sharma et al. 2016) which should reduce their vigour at germination and growth period. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of growth parameters of selected improved varieties and landraces\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGrowth form in groundnuts differs depending on the subspecies and botanical variety (Krapovikas and Gregory 1994). Groundnut accessions used in this study differed in their growth abilities with landraces being relatively taller than improved varieties. The difference in plant height between these classes can be attributed the sub species maintained or managed in the country\u0026rsquo;s gene pool. Most of the improved varieties used in this study belong to \u003cem\u003esub species\u003c/em\u003e \u003cem\u003ehypogaea\u003c/em\u003e (virginia market types) and these are normally runners or small bush types while most of the landraces were predominantly well adapted \u003cem\u003esub species fastigiata\u003c/em\u003e (valencia market types) which are normally erect with potential to grow taller depending on the growing environment, including competition subjected to them by weeds or other crops in mixed cropping systems. Growth progression measured as plant height among landraces ranged from 25 to 59.4 cm while that in the modern varieties ranged from 25 to 52.1cm. Literature pertaining to differences in plant growth of landraces versus improved varieties is not well documented. However, results from studies by Kakeeto (2018) found that plant height of groundnut materials tested in Uganda varied from 15.3 to 54.6 depending on season and the botanical variety of the groundnut accession. Moreover, Salasya et al. (2007) reported that improved groundnut varieties took longer days to emerge and flower due to poor adaptation to the environment, but the landrace grew better because they were well-adapted to the environment.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of drought tolerance level of selected improved groundnut varieties and landraces\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStay green is an important trait that allows plants to retain their leaves in an active photosynthetic state when exposed to stress conditions (Thomas and Howarth 2000). Stay-greenness has been used as a criterion for selecting stay-green genotypes in various crops (Christopher et al. 2014; Lope and Reynolds 2012; Trachsel et al. 2016; Borrell et al. 2014). We report significant variation in the stay green trait among landraces and improved varieties with the former maintaining greenness for a longer time compared to latter. \u0026nbsp;This is in contradiction to the findings by Oppong-Sekyere et al. (2019) who found improved varieties to have higher chlorophyll concentration than landraces over well-watered and water-stressed conditions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReaction of selected improved groundnut varieties and landraces to natural pest and disease infestations\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnother important selection criterion used by groundnut producers is the pests and disease reaction (Okello et al. 2010, 2014, Mugisa et al. 2015, Kakeeto et al. 2018). The reaction of groundnut varieties to pests and diseases didn\u0026rsquo;t significantly differ between landraces and improved varieties, even though incidence of pests and diseases was lower on improved varieties. These results corroborate those of Kakeeto et al. (2018) where farmers selected improved varieties over landraces for their pest and disease resistance. However, these results contradict those of Aina et al. (2011) who reported that landraces had better tolerance to CMD and CBB diseases compared to improved varieties of cassava. \u0026nbsp;Results from similarity clustering showed that clustering was not based on groupings as landrace or improved variety but rather a combination of both improved and landraces. Moreover, these combinations had unique associations with particular pests and diseases. These results imply that choice of a resistant groundnut variety shouldn\u0026rsquo;t be informed by their grouping as landraces or improved varieties, but on associations identified between individual varieties and pest/diseases that have to be considered when making selections for breeding pipe lines or target production environments (high disease pressure vs low disease pressure) growing areas.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffect of significant GE interaction on performance of selected improved groundnut varieties and landraces\u003c/p\u003e\n\u003cp\u003eGenotype environment interaction exists whenever the relative phenotypic performance of genotypes varies with the environment. \u0026nbsp;Significant G x E interactions were observed in all characters studied for both landraces and improved varieties. Several research groups have also reported similar results (Mothilal et al. 2010; Songsri et al. 2008; Minde et al. 2017; Aina et al. 2011). In this study, both crossover and non-cross over GE were observed. \u003c/p\u003e\n\u003cp\u003eSignificance of GE has serious implications for deployment of varieties (Kang 1993). While non-crossover GE can be exploited by improving the growing environment, the crossover GE calls for selection and deployment of specifically adapted varieties. Cross- over GE was only observed for yield implying that high performers from both improved and landraces could be specifically deployed in the respective sites. On the other hand, non-cross over GE could be overcome by modifying the production sites. Related to this recommendation, biophysical description of the two sites indicates that although Nakaseke site has better conditions for crop growth, Nakasongola has the largest share of locations suitable for groundnut production; which also confirms the inherent drought tolerant nature of this crop (Erickson and Ketring 1985; Reddy et al. 2003). Therefore, strategies such as irrigation, use of conservation agriculture, and adoption of drought tolerant varieties could boost performance of both improved varieties and landraces in Nakasongola.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe current study aimed to explore the presence of genetic and geographic structures in a collection of groundnuts representing the existing variability for this species in the Ugandan gene pool. There were no clear structures for either landraces or improved varieties with respect to the traits investigated. The differences or similarities observed could largely be explained by the genetic pools managed by the breeding programmes operating in the country and those in the hands of farmers coupled with differences in the target growing environments. The results reported in the current study may be used to facilitate development of new cultivars building on inherent strengths of both well adapted landraces and improved varieties with desirable traits thus the need to conserve these varieties for sustainable use.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicts of Interest/competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData used to support these findings can be sourced from the corresponding author. The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis code can be accessed from corresponding author\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contribution: NA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval: NA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent\u0026nbsp;\u003c/strong\u003eto\u003cstrong\u003e\u0026nbsp;participate: NA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication: NA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the site teams and the farmers of the Nakaseke and Nakasongola sites for their participation in the research on which the paper is based.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdamu AS, Salaudeen MT, Gana AS, Ishaq MN (2015) Response of selected soybean (Glycine max [L.] Merr.) lines to Cucumber mosaic virus disease in Minna, Niger State. Nig J Agric Food Environ 11(4):45\u0026ndash;51\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhmed O, Olayika BU, Garuba T, Ahmed J, Etejere EO (2017) Germination of several groundnut cultivars in relation to incidence of fungi. Science World Journal 12(1):38\u0026ndash;41\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAina OO, Dixon AGO, Ilona P, Akinrinde EA (2009) Gx E interaction effects on yield and yield components of cassava (landraces and improved) genotypes in the savanna regions of Nigeria. Africa Journal of Biotechnology Vol 8(19):4933\u0026ndash;4945\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAra\u0026uacute;jo PM, Nass LL (2002) Caracteriza\u0026ccedil;\u0026atilde;o e avalia\u0026ccedil;\u0026atilde;o de popula\u0026ccedil;\u0026otilde;es de milho crioulo. Science in Agriculture 59:589\u0026ndash;593\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorrell AK, van Oosterom EJ, Mullet JE et al (2014) Stay-green alleles individually enhance grain yield in sorghum under drought by modifying canopy development and water uptake patterns. New Phytol 203(3):817\u0026ndash;830\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChristopher JT, Veyradier M, Borrell AK, Harvey G, Fletcher S, Chenu K (2014) Phenotyping novel stay-green traits to capture genetic variation in senescence dynamics. Funct Plant Biol 41(11):1035\u0026ndash;1048\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCokkizgin A (2012) Salinity Stress in Common Bean (Phaseolus vulgaris L.). Seed Germination Not Bot Horti Agrobo 40(1):177\u0026ndash;182\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavid AM, Haverkampb BJ, Laurenzc RG, Orlowskid JM, Wilsone EW, Casteelf SN, Leeg CD et al (2016) Characterizing genotype \u0026times; management interactions on soybean seed yield. Crop Sci 56(2):786\u0026ndash;796\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEberhart SA, Russell WA (1966) Stability parameters for comparing varieties. Crop Sci 6:36\u0026ndash;40\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErickson P, Ketring D (1985) Evaluation of peanut genotypes for resistance to water stress in situ. 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Euphytica 104:127\u0026ndash;139\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"genetic-resources-and-crop-evolution","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gres","sideBox":"Learn more about [Genetic Resources and Crop Evolution](https://www.springer.com/journal/10722)","snPcode":"10722","submissionUrl":"https://submission.nature.com/new-submission/10722/3","title":"Genetic Resources and Crop Evolution","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Diversity, peanuts, conservation, germplasm","lastPublishedDoi":"10.21203/rs.3.rs-696706/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-696706/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGroundnut (\u003cem\u003eArachis hypogaea\u003c/em\u003e L.) is important for providing food, income, livestock fodder for smallholder farmers, and improving soil fertility. However, groundnut yields on farmers’ fields in Sub-Saharan Africa are still very low due to various constraints. Several groundnut cultivars are available within the farmer’s domain but the adoption of these varieties favours landraces as opposed to improved varieties. Limited information is available on performance of commonly grown cultivars for guiding selection by different user groups (farmers, breeders and other users). This study was thus designed to determine the performance of selected landraces and improved groundnut varieties in Uganda. 23 groundnut lines with varying degrees of tolerance to a range of stresses were evaluated at two sites. Results showed significant (P ≤ 0.05 to P≤ 0.001) differences among genotypes for yield. Significant (P≤0.05 to P≤0.001) varietal differences were also observed between landraces and improved varieties for growth and physiological traits but not for pest and disease reaction. Clustering was not evident on the basis of either landraces or improved cultivars for pests and diseases incidences. However, associations of a mix of both groundnut classes of with particular diseases and/or pests were observed. Varieties such as India, Serenut 10, Kabonge, and DOK Tan associated with diseases such as rosette virus disease and its vector pest, the aphids. The results reported in this study shall be useful for driving the development of new cultivars owing to their good adaptability and acceptance thus the need to conserve and ensure sustainable use of these germplasm.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Comparative Evaluation of Agronomic Performance of Selected Landraces And Improved Groundnuts Cultivars In Central Uganda","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-07-30 18:54:25","doi":"10.21203/rs.3.rs-696706/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2021-08-11T13:37:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-07-28T10:49:23+00:00","index":0,"fulltext":""},{"type":"editorAssigned","content":"","date":"2021-07-16T03:01:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Genetic Resources and Crop Evolution","date":"2021-07-07T10:34:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"genetic-resources-and-crop-evolution","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gres","sideBox":"Learn more about [Genetic Resources and Crop Evolution](https://www.springer.com/journal/10722)","snPcode":"10722","submissionUrl":"https://submission.nature.com/new-submission/10722/3","title":"Genetic Resources and Crop Evolution","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"02062c71-dc30-4573-93e3-1679c8fea861","owner":[],"postedDate":"July 30th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":6100600,"name":"Agronomy"},{"id":6100601,"name":"Behavioral Ecology"}],"tags":[],"updatedAt":"2021-07-30T18:54:25+00:00","versionOfRecord":[],"versionCreatedAt":"2021-07-30 18:54:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-696706","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-696706","identity":"rs-696706","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}