Genetic Analysis of White Maize (Zea Mays L.) Inbred Lines Under Low Soil Nitrogen

Genetic Analysis of White Maize (Zea Mays L.) 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Inbred Lines Under Low Soil Nitrogen George Obeng, Benjamin Annor, Alexander Wireko Kena This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6379832/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Low soil nitrogen (N) is among the major constraints causing low grain yield of maize in sub-Saharan Africa. This study was conducted to (i) determine the level of tolerance of the hybrids under low-N, (ii) examine the mode of inheritance of grain yield and other traits of the inbreds, and (iii) assess the genetic diversity of the inbreds. Ninety-one hybrids developed from fourteen inbred lines using diallel mating design together with nine hybrid checks were evaluated under low (30 kg N ha-1) and optimum (90 kg N ha-1) nitrogen conditions at the KNUST Maize Breeding Pipeline in 2024. The results revealed a preponderance of the general combining ability (GCA) effect over specific combining ability (SCA) effects for the traits under low-N, optimum, and across environments, indicating that additive gene action is more important in the inheritance of the traits. The inbreds were classified into three clusters based on the GCA effect of multiple traits of inbreds (HGCAMT). Inbred lines CML 126, TZEEI-76, and USTEWI-7 were identified as the best testers for clusters 1, 2, and 3 respectively. Out of the best 15 and the worst 10 performing hybrids selected based on the base index, USTEWI-7 × USTEWI-11 and TZEEI-50 × TZEEI-4 were identified as the highest yielding and low nitrogen tolerant hybrids. The tolerant hybrids identified should be extensively evaluated to verify their consistency in performance under low nitrogen conditions. Inbred lines with desirable traits could be utilized to develop low nitrogen tolerant hybrids in maize breeding programs. Maize Combining ability Low soil nitrogen Genetic diversity Figures Figure 1 Introduction Maize (Zea mays) holds a paramount status as one of the world's key cereal crops, ranking third in global production following wheat and rice. Its remarkable adaptability enables widespread cultivation across various agroecological zones in West and Central Africa (Yadesa and Diro, 2023 ). The economic significance of maize has been on a steady rise, with forecasts indicating its trajectory to surpass other cereal crops and emerge as the foremost crop by 2025 (FAOSTAT, 2017 ). Maize serves multiple purposes, being utilized as a staple food for humans, fodder for livestock, and a versatile resource for producing biofuel, edible oil, and various industrial goods (Tajamul et al., 2016 ). Maize contributes significantly to dietary needs, providing approximately one-fifth of the total daily calorie intake and contributing between 17 and 60% of the daily protein supply across Africa (Yadesa and Diro, 2023 ). The annual worldwide land area dedicated to growing maize is approximately 197 million hectares (FAOSTAT, 2021). In sub-Saharan Africa (SSA), approximately 30 million hectares of arable land are allocated to maize cultivation (Annor et al., 2019 ). However, although there is considerable potential for boosting maize production in Ghana, the grain yield on farmers' fields has declined, averaging only 1.95 t/ha. This starkly contrasts the significantly higher yields observed in countries like the United States of America and China, where yields reach 11.07 t/ha and 10.53 t/ha respectively (FAOSTAT, 2020 ). The low grain yield across sub-Saharan Africa (SSA) can be partly attributed to the surge in biotic and abiotic stresses such as heat, drought, and inadequate soil fertility (Badu-Apraku et al., 2023 ). Biotic stresses encompass a range of challenges such as diseases like leaf blight and maize lethal necrosis, contamination by aflatoxins, and the presence of pests such as striga, weevils, armyworms, and stem borers (Njeru et al., 2023 ). Contributing to this scenario are factors like the slow adoption of improved maize varieties and socioeconomic constraints like limited financial resources, inadequate processing and marketing infrastructure, and challenges in post-harvest handling (Mutungi et al., 2023 ). Among the abiotic stresses, nitrogen deficiency is a critical issue constraining maize production in tropical regions. This deficiency worsens due to nutrient loss and low soil organic matter, making it difficult for smallholder farmers in Africa to grow maize sustainably (Zingore and Njoroge, 2022 ). Notably, nitrogen inadequacy alone incurs substantial yield losses in maize, ranging from 10–50% in West Africa (Badu-Apraku et al., 2016 ; Ribeiro et al., 2022 ). The productivity of maize exhibits variability across different soil fertility levels and nitrogen utilization efficiencies due to differences in gene expression related to maize's tolerance to low nitrogen conditions within various varieties (Ogunniyan et al., 2019 ). Understanding the combining abilities, heritability, and heterotic patterns of parental lines under nitrogen stress is important for identifying high-yielding hybrids suitable for commercial cultivation. Additionally, insights into the genetic diversity and population structure of inbred lines within hybrid breeding programs enable breeders to develop hybrids exhibiting strong heterosis and enhanced adaptation to varied environmental conditions (Abu et al., 2021 ). Ultimately, the ability to meet the rising need for resilient maize cultivars amidst shifting environmental challenges hinges on harnessing the wealth of genetic variability within maize populations. This study aims to contribute to the improvement of maize production in Ghana through increasing productivity by developing hybrids with high-yielding and low nitrogen tolerance potentials. The specific objectives of the study are to; (i) determine the level of tolerance of the hybrids under low soil nitrogen conditions, (ii) examine the mode of inheritance of grain yield and other traits of the inbred lines under low and optimum nitrogen conditions and (iii) assess the genetic diversity of the inbred lines under low and optimum nitrogen conditions. Materials and Methods Study site The study was conducted at the Maize Breeding Pipeline (Animal Science Department) of the Kwame Nkrumah University of Science and Technology, Kumasi-Ghana. The site is situated at a latitude of N 6°40'52.34952" and a longitude of W 1°33'25.45812" within the tropical rainforest climate zone. The area experiences a bimodal rainfall pattern with two main rainy seasons, the major season from March to July and the minor season from September to November. The average annual rainfall is around 1,448 mm and an average temperature of 24°C. The soil type is haplic alisols (Jones et al., 2013 ). Genetic Materials Fourteen (14) white maize inbred lines (Table 1 ) used in the present study were sourced from KNUST Maize Improvement Program of the Crop and Soil Sciences Department, KNUST. Table 1 List of inbred lines Entry Inbred lines Entry Inbred lines 1 CML 126 8 USTEWI-8 2 USTEEWI-2 9 USTEWI-11 3 TZEEI-6 10 TZEEI-21 4 TZEEI-50 11 TZEEI-76 5 USTEWI-7 12 TZEEI-24 6 TZEEI-15 13 USTEEWI-1 7 TZEEI-4 14 TZEEI-36 Generation of Diallel Crosses The 14 parental lines were crossed using a diallel mating design to generate ninety-one (91) single-cross hybrids. The inbred lines were crossed in all possible hybrid combinations without reciprocals and self, assuming no reciprocal effect of low nitrogen tolerance in maize, following Griffing’s (1956) diallel method four. Field evaluation The hybrids were evaluated under low (30 N kg/ha) and optimum (90 kg/ha) nitrogen conditions within the 2022 major cropping season. The experimental field was depleted of nitrogen due to continuous cultivation of densely populated maize and removal of all crop residues after harvest for many seasons. Before field preparation, soil samples from 0 to 15 cm depth were taken for analysis at the Soil Research Institute (SRI), Kwadaso-Kumasi. The Kjeldahl digestion and distillation procedure (Bremner and Mulvaney, 1982) was used for the analysis of the soil samples to determine the levels of Nitrogen (N), Phosphorus (P), and potassium (K). The soil contained 0.10% of N, 38.66 ppm of P, and 0.30 me/100g of K. Based on the soil test, urea was applied on the low nitrogen field immediately after thinning to bring the nitrogen content to 30kg N ha − 1 at 2 weeks after planting (WAP). In addition, 60kg ha − 1 each of P and K in the form of single superphosphate (P 2 0 5 ) and muriate of potash (K 2 O) fertilizers were applied. For the experiment under optimal conditions, NPK (15:15:15) was applied at 2 WAP to supply 60kg ha − 1 each of N, P, and K and top-dressed with an additional 30kg N ha − 1 at 4 WAP. Field Layout The hybrid experiment (91 diallel crosses plus 9 hybrid checks) was laid out using a 10 × 10 alpha lattice design with two replications. Each experimental unit was a single-row plot, 4 m long with a row spacing of 0.75 m and intra-row spacing of 0.4 m. Three seeds were planted and the seedlings were thinned to two per hill at 2 WAP to give a final plant population density of about 66,666 plants ha –1 . Weeds were controlled manually. Data Collection Days to 50% anthesis (DA) was recorded as the number of days from planting to when 50% of the plants in a plot had shed pollen. Days to 50% silking (DS) was obtained as the number of days from planting to when 50% of the plants in a plot had silks. Anthesis silking interval (ASI) was determined as the difference between DS and DA. The low nitrogen trial was assessed for stay green characteristic (STGR) at 65 days after planting based on leaf senescence on a scale of 1–9; where 1 = 0–10% dead leaf area and 9 = 81–100% dead leaf area, respectively. Plant height (PHT) and ear height (EHT) were scored as the distance from the base of the plant to the height of the first tassel branch and the node bearing the upper ear, respectively. Husk cover (HC) was recorded on a scale of 1–9; where 1 = tightly arranged husks extending beyond the tip of the ear and 9 = completely exposed ear tip. The number of ears per plant (EP) was calculated as the number of ears harvested per plot divided by the number of plants harvested. Plant aspect (PASP) was examined on a plot basis after flowering when plants were still green and ears fully developed on a scale of 1 to 9 where 1 = excellent and 9 = very poor. The PASP was the general appeal of the whole plant, based on the uniformity of the plant stands, plant and ear heights, reaction to diseases and insects as well as lodging. Ear aspect (EASP) was recorded on a scale of 1–9; where 1 = uniform, well-filled, large, and disease-free ears and 9 = undesirable ear features. Ear rot (ERT) was determined by counting the rotted ears per plot. Field weight (FW) was determined by weighing the ears harvested per plot after de-husking. Grain weight was determined by weighing the grains shelled per plot in kilograms using a digital weighing balance. The moisture content in the grains was determined using a grain moisture meter. Grain yield was determined in kilogram per hectare from the grain weight, adjusted to 15% moisture content under low nitrogen conditions. Under optimum conditions, a shelling percentage of 80 was assumed for all plots, and grain yield was calculated using ear weight adjusted to 15% moisture content. Statistical Analysis Analysis of Variance Analysis of variance (ANOVA) was performed on plot means for grain yield and other agronomic traits collected for each and across the environment using the Procedure for Generalized Linear Model (PROC GLM) in Statistical Analysis System (SAS) (SAS Institute, 2002). The genotypes were considered fixed effects while environments, replications, and blocks within replications were random effects. The least significant difference (LSD) according to Steel and Torrie ( 1980 ) was used to separate the means. The statistical models for each and across the environments were denoted as equations 1 and 2 respectively: Y ijk = µ + G i + R j + B k (j) + Ɛ ijk …………………………………………Eqn 1 Y ijlk = µ + E l + R j (l) + B k (lj) + G i + EG li + Ɛ ijlk ……………………….... Eq. 2 Where Y = observation, µ = overall mean, G = genotype effect, E = environment effect, Block = effect of the block, R = replicate effect, EG = interaction effect between environment and genotype and Ɛ = error Excluding the checks, the GCA effects of the parents and the SCA of the crosses for grain yield, days to 50% silking, days to 50% anthesis, anthesis silking interval, plant height, ear height, ear aspect, ear per plant, plant aspect and low nitrogen environment for stay green characteristics were estimated using AGD-R statistical package, version 5.0 developed by Rodriquez et al ., (2018). The GCA and SCA effects were tested for significance using the t-test and the standard errors were estimated as the square root of the GCA and SCA variances. The statistical models for diallel analysis of each and across environment were as follows; Y ijlk = µ + R i + Gj + Gk + S jk + Ɛ ijlk ………………………………………………………………………..………………… Eq. 1 Y ijlk = µ + E p + R i ( p ) + Gj + Gk + S jk + E p *G + Ep*S jk + Ɛ ijlpk ……………………….…. Eq. 2 Where; Y ijlk = the observation of parents, µ = the overall mean, Ri = replication effect, E p = effect of the environment, Gj and Gk = the general combining ability (GCA) effect of the j th and k th parents, S jk = specific combining ability effect (interaction effect) of the j th and k th parent and Ɛ ijk is the error associated with the observations ijk th Heritability estimates Broad sense heritability was estimated from the mean square values of the grain yield and other agronomic traits. Broad sense heritability ( H 2 ) = \(\:\frac{{{\sigma\:}}_{A}^{2}\:+{\:{\sigma\:}}_{D}^{2}}{{{\sigma\:}}_{A}^{2}+{{\sigma\:}}_{D}^{2}+{{\sigma\:}}_{E}^{2}\:}\) Selection of inbred lines under nitrogen stress using low-N base index The low nitrogen base index (LNBI) proposed by Badu-Apraku et al. , (2011) that combined grain yield (GY) under nitrogen stress with plant aspect (PASP), ear aspect (EASP), anthesis-silking interval (ASI), number of ears per plant (EPP) and the stay-green characteristic (STGR) was adopted to identify low nitrogen tolerant genotypes. Before the analysis, each trait was standardized to achieve a mean of zero and a standard deviation of 1 to reduce the effects of different scales used for measuring various traits. A positive value of LNBI was an indicator of tolerance to nitrogen stress while a negative value indicated susceptibility. The base index was estimated using the following equation: LNBI = [(2 × GY) + EPP - ASI - PASP - EASP - STGR]. Assessment of genetic diversity The clustering of inbred lines into heterotic groups was based on the GCA effect of multiple traits of inbreds (HGCAMT) method as suggested by Badu-Apraku et al., ( 2013 ). This method was employed by identifying the traits with significant mean squares across the test environment and standardizing their GCA effects to reduce the effect of different rating scales used to measure the traits. Thereafter, the standardized GCA values were used for cluster analysis based on Ward’s minimum variance method implemented in SAS (SAS Institute, 2002). Results Analysis of variance and heritability estimates of the hybrids evaluated under the test environments The analysis of variance for the hybrids showed highly significant differences (P < 0.01) for grain yield and other measured traits under low nitrogen conditions except for anthesis silking interval, plant aspect, and ear per plant (Table 2 ). General combining ability (GCA) was highly significant for grain yield and all other traits except ear per plant. Specific combining ability (SCA) was highly significant for grain yield, ear height, ear rot, and plant height, all other traits were not significant. Moderate to high broad sense heritability estimates were revealed for the measured traits ranging from 56% for plant aspect to 96% for grain yield. The ratio of GCA/SCA was more than unity for all measured traits. Under optimum conditions, highly significant differences were observed among the hybrids for grain yield and other traits except ear per plant and ear rot (Table 2 ). GCA was highly significant for grain yield and other traits except ear rot. SCA was highly significant for all measured traits except husk cover, ear per plant, and ear rot. Broad sense heritability estimates ranged from 49% for ear per plant to 97% for grain yield. In general, moderate to high heritability estimates were observed for the measured traits. The ratio of GCA/SCA was more than unity for all measured traits except ear rot. The combined analysis of variance of the hybrids across the test environments revealed highly significant mean squares for grain yield and other traits except ear per plant (Table 3 ). Highly significant differences were observed for the environments for all measured traits except anthesis silking interval, husk cover, ear per plant, and ear aspect. Hybrid × environment interactions were significantly different for grain yield, plant aspect, days to 50% anthesis, and plant height, all other traits were not significant. Mean squares due to GCA were highly significant for grain yield and other traits except ear per plant. Highly significant differences in SCA effect were observed for grain yield and all other characters except plant aspect and ear per plant. The environment × GCA interaction showed highly significant differences for grain yield and all other traits except anthesis silking interval and ear per plant. Mean squares due to environment × SCA interaction were highly significant for grain yield, days to 50% silking, plant height, and plant aspect. Anthesis silking interval, ear per plant, ear aspect, and ear rot were not significant. Moderate to high broad sense heritability estimates were revealed for the measured traits ranging from 53% for ear per plant to 98% for grain yield. The ratio of GCA/SCA was more than unity for all measured traits Table 2 Mean squares from the analysis of variance, heritability estimates and GCA/SCA ratio for grain yield and other traits of the hybrids evaluated under low and optimum nitrogen conditions Source of variation DF GY DA DS ASI PHT EHT PASP HC EPP EASP EROT STGR Low Nitrogen Rep 1 216.1 28.9 46.1 0.3 1010.9** 988.4** 0.6 2.4 0.4** 3.9 353.7** 6.1** Block (Rep) 18 281240.9** 33.5** 47.5** 2.9 496.1** 256.4** 1.2* 2.6* 0.1 2.6** 4.8 1.9** Hybrid 99 1294450.0** 31.8** 33.5** 4.3 401.7** 248.7** 0.8 2.1* 0.1 1.9** 6.6** 1.1* GCA 13 3907877.1** 134.0** 109.6** 8.0** 2306.2** 1204.2** 1.6* 6.4** 0.1 4.6** 18.5** 2.5** SCA 77 873234.2** 19.6 24.7 4.1 135.6* 87.8** 0.7 1.7 0.1 1.1 6.1** 0.8 Error 72 111326.3 14.1 18.7 3.3 84.1 44.6 0.7 1.4 0.1 1.0 3.5 0.8 H 2 0.96 0.80 0.75 0.67 0.90 0.91 0.56 0.70 0.6 0.69 0.78 0.6 GCA/SCA 4.5 6.8 4.4 2.0 17.0 13.7 2.3 3.8 1.0 4.2 3.0 3.1 Optimum Nitrogen Rep 1 99210.4 62.7* 57.2* 0.1 188.6 71.3 4.2** 4.5* 0.0 0.7 35.3** - Block (Rep) 18 71807.8 89.9** 102.7** 2.3 1067** 480.3** 1.7** 2.2** 0.0 3.5** 8.9** - Hybrid 99 1535868** 34.9** 28.7** 4.7** 595.8** 333.5** 1.1** 1.4** 0.1 2.7** 5.1 - GCA 13 5092919.5** 140.4** 91.8** 11.4** 3694.7** 1600.0** 3.1** 3.2** 0.1* 9.1** 4.9 - SCA 77 655313.2** 27.9** 29.7** 3.8** 374.6** 180.1** 1.1** 1.1 0.1 1.8** 5.7 - Error 72 77875.4 13.1 15.5 2.3 159.1 73.5 0.6 0.8 0.1 0.9 4.8 - H 2 0.97 0.85 0.81 0.78 0.90 0.90 0.79 0.73 0.49 0.85 0.6 - GCA/SCA 7.8 5.0 3.1 3.0 9.9 8.9 2.8 2.9 2.2 5.1 0.9 - *, ** = 0.05 and 0.01 probability levels, respectively; Rep = replication; DF = degree of freedom; GY = grain yield; DA = days to 50% anthesis; DS = days to 50% silking; ASI = anthesis silking interval; PHT = plant height; EHT = ear height; PASP = plant aspect; HC = husk cover; EPP = ear per plant; EASP = ear aspect; EROT = ear rot; GCA = General combining ability; SCA = Specific combining ability; H 2 = Broad sense heritability Table 3 Mean squares from the analysis of variance, heritability estimates and GCA/SCA ratio for grain yield and other traits for the hybrids evaluated across the environments Source of variation DF GY DA DS ASI PHT EHT PASP HC EPP EASP EROT Env 1 43636768.0** 1918.4** 1879.2** 3.8 1496.8** 721.6** 11.6** 0.0 0.0 2.0 475.2** Rep (Env) 2 49713.3 45.8* 51.7* 0.2 599.7** 529.8** 2.4* 3.5* 0.2* 2.3 194.5** Block (Env × Rep) 36 176524.3** 61.7** 75.1** 2.6 781.5** 368.3** 1.4** 2.4** 0.1 3.1** 6.8** Hybrid 99 2390266.0** 47.3** 40.8** 5.8** 821.5** 493.4** 1.0** 2.2** 0.1 3.4** 6.8** Env × Hybrid 99 440051.3** 19.4* 21.4 3.1 176.1* 88.8* 0.9** 1.4 0.1 1.2 4.9 GCA 13 8218635.4** 239.9** 173.6** 16.5** 5261.8** 2597.0** 2.7** 6.7** 0.1 9.2** 16.3** SCA 77 1164539.0** 25.3** 29.4** 4.7** 330.9** 163.2** 0.8 1.5* 0.1 1.6** 6.1* Env × GCA 13 745122.4** 37.4** 30.1* 2.2 591.3** 162.3** 1.9** 2.6* 0.1 4.4** 7.7* Env × SCA 77 361478.5** 21.7** 24.3* 3.2 180.3* 102.1** 0.9* 1.3** 0.1 1.3 5.3 Residual 144 95712.5 13.5 16.9 2.7 121.6 59.2 0.6 1.0 0.1 0.9 4.2 H 2 0.98 0.88 0.83 0.79 0.94 0.94 0.70 0.77 0.53 0.82 0.73 GCA/SCA 7.1 9.5 5.9 3.5 15.9 15.9 3.4 4.5 1.0 5.6 2.7 *, ** = 0.05 and 0.01 probability levels, respectively; Rep = replication; DF = degree of freedom; GY = grain yield; DA = days to 50% anthesis; DS = days to 50% silking; ASI = anthesis silking interval; PHT = plant height; EHT = ear height; PASP = plant aspect; HC = husk cover; EPP = ear per plant; EASP = ear aspect; EROT = ear rot; GCA = General combining ability; SCA = Specific combining ability; H 2 = Broad sense heritability Performance of the hybrids under stress and optimum conditions The mean grain yield of the hybrids under low nitrogen conditions ranged from 1085 kg/ha for TZEEI-4 × USTEEWI-1 to 4788.7 kg/ha for Check-DZIFOO with an overall mean yield of 2651.0 kg/ha (Table 4 ). The performance of hybrids check-DZIFOO, check-HONAMPA, TZEEI-50 × TZEEI-4 and USTEWI-7 × USTEWI-11 with their respective mean grain yield of 4788.7, 4643.7, 4350.5 and 4338.8 kg/ha were significantly higher than the average grain yield of the other hybrids. Among the best 15 and worst 10 of the 100 maize hybrids selected based on their performance under stress condition using base index, hybrids TZEEI-15 × TZEEI-21, TZEEI-6 × USTEWI-11, TZEEI-6 × USTEWI-76, USTEWI-11 × TZEEI-36, USTEWI-7 × USTEWI-11, TZEEI-6 × TZEEI-24, TZEEI-15 × USTEWI-11, TZEEI-21 × TZEEI-24, CML 126 × TZEEI-36, TZEEI-6 × TZEEI-21, TZEEI-21 × USTEWI-76, TZEEI-50 × TZEEI-4 with mean grain yield of 3603.8, 3956.9, 3418.5, 3444.4, 4338.8, 3103.1, 3560.0, 2916.7, 3706.2, 3174.9, 3117.0 and 4350.5 kg/ha respectively were identified to be tolerant to low nitrogen stress. Yield loss was relatively higher in the susceptible hybrids than in the tolerant hybrids. The average yield loss of 19.1% was recorded for the hybrids ranging from 1.3% for TZEEI-6 × USTEWI-11 to 75.0% for Check-ARG 8900. Under the optimum condition, the mean grain yield of the hybrids ranged from 1325.5 kg/ha for TZEEI-4 × USTEEWI-1 to 6599.2 kg/ha for Check-DZIFOO with an overall mean of 3311.6 kg/ha (Table 4 ). The hybrid check, DZIFOO recorded the highest grain yield with an average yield of 6599.2 kg/ha which was significantly higher than the mean yield of other hybrids. Grain yield of hybrids across the two nitrogen environments varied from 1205.3 kg/ha for TZEEI-4 × USTEEWI-1 to 5693.9 kg/ha for DZIFOO with an overall mean of 2981.3kg/ha (Table 5 ). The best performing check (DZIFOO) differ significantly in grain yield when compared with the single cross hybrid TZEEI-50 × TZEEI-4 across nitrogen environment. Table 4 Grain yield and other agronomic traits of the maize hybrids (the best 15 and the worst 10 based on base index) evaluated under low and optimum nitrogen conditions Hybrids GY DA DS ASI PHT EHT PASP STGR % YL BI LN OPT LN OPT LN OPT LN OPT LN OPT LN OPT LN OPT LN Check-DZIFOO 4788.7 6599.2 63 65 64 66 1 1 195.9 201.6 92.1 89.1 4.2 3.0 3.2 27.4 12.0 Check-HONAMPA 4643.7 4730.1 59 62 61 64 2 2 184.2 200.9 84.0 82.8 4.2 3.0 3.2 1.8 10.9 Check-D778 4173.1 5829.7 63 59 64 59 0 0 163.3 172.0 69.4 68.2 4.2 4.4 3.5 28.4 9.0 TZEEI-15 × TZEEI-21 3603.8 3806.3 54 60 51 62 2 2 165.3 178.9 55.2 66.5 3.8 4.8 5.3 5.3 6.1 TZ EEI-6 × USTEWI-11 3956.9 4009.8 42 59 45 63 3 4 146.7 129.9 51.7 38.5 4.3 3.4 7.3 1.3 6.0 TZEEI-6 × USTEWI-76 3418.5 3857.5 48 50 50 51 1 1 161.0 132.6 65.8 42.6 4.1 3.6 3.7 11.4 5.5 USTEWI-11 × TZEEI-36 3444.4 3517.0 55 59 58 59 2 1 160.6 59.8 61.2 4.8 3.9 1.9 8.4 2.0 5.4 USTEWI-7 × USTEWI-11 4338.8 4478.4 55 55 58 57 1 2 140.4 147.0 53.9 57.5 5.0 2.9 3.3 3.1 5.2 TZEEI-6 × TZEEI-24 3103.1 3202.2 48 54 51 55 3 2 159.5 149.6 58.0 48.1 3.6 5.1 3.2 3.1 5.1 TZEEI-15 × USTEWI-11 3560.0 3994.0 47 58 49 60 2 2 146.2 158.0 51.3 47.6 3.8 5.8 7.7 10.9 5.0 TZEEI-21 × TZEEI-24 2916.7 4017.1 59 61 59 62 1 1 179.8 177.6 76.3 74.1 3.8 3.0 3.5 27.4 5.0 CML 126 × TZEEI-36 3706.2 4118.7 58 64 58 67 1 3 153.3 156.8 54.7 52.6 3.3 5.2 5.5 10.0 4.9 TZEEI-6 × TZEEI-21 3174.9 3620.1 45 55 46 55 2 1 168.8 133.3 70.7 48.4 3.8 3.9 2.8 12.3 4.9 TZEEI-21 × USTEWI-76 3117.0 3165.8 57 59 58 59 0 0 182.4 187.4 79.7 75.0 4.4 3.8 4.3 1.5 4.6 TZEEI-50 × TZEEI-4 4350.5 4534.9 55 59 60 59 4 1 136.0 135.8 43.9 36.3 4.9 3.2 4.9 4.0 4.5 TZEEI-6 × USTEWI-8 1760.3 2294.0 48 57 55 61 8 4 125.6 110.2 39.4 32.9 4.6 3.9 5.0 23.2 -5.6 USTEEWI-2 × TZEEI-36 1368.5 1734.8 57 64 61 66 4 2 127.6 124.1 42.9 52.5 4.1 4.0 6.5 21.1 -5.8 CML 126 × TZEEI-50 2534.6 4037.5 56 59 64 60 8 1 152.0 163.2 46.2 62.5 5.5 3.6 4.7 37.2 -5.8 USTEWI-7 × TZEEI-36 1319.6 3204.2 55 60 56 62 3 3 128.9 156.2 38.6 54.4 5.5 5.0 6.4 58.8 -5.9 TZEEI-4 × USTEWI-76 2254.8 2286.9 59 49 58 52 1 3 121.8 136.5 33.7 36.5 5.9 5.5 7.1 8.9 -5.9 USTEWI-8 × USTEEWI-1 1216.6 2452.6 50 52 50 56 0 4 138.9 154.1 40.9 45.4 5.7 4.3 6.2 50.4 -5.9 USTEWI-7 × USTEEWI-1 1190.4 2911.7 48 53 50 56 1 3 125.1 153.5 28.5 38.7 5.5 5.5 6.4 59.1 -6.3 TZEEI-4 × TZEEI-36 1442.6 3220.1 50 54 51 57 1 3 128.9 158.9 38.8 56.6 5.4 4.0 6.6 55.2 -6.3 TZEEI-4 × USTEEWI-1 1085.1 1325.5 46 54 47 61 1 7 113.0 149.9 20.2 40.6 6.9 4.5 7.6 18.1 -10.7 USTEEWI-1 × TZEEI-36 1217.2 1368.4 56 59 60 61 6 3 118.9 119.9 30.6 30.4 6.7 4.4 6.0 11.1 -11.5 MEAN 2651.0 3311.6 54 59 57 61 3 2 150.1 154.0 52.3 55.0 4.8 4.4 4.9 19.1 LSD 666.7 538.7 8 7 9 8 4 3 18.5 26.3 13.7 17.9 1.6 1.2 1.7 GY = Grain yield; DA = Days to 50% anthesis; DS = Days to 50% silking; ASI = Anthesis silking interval; PHT = Plant height; EHT = Ear height; PASP = Plant aspect; STGR = Stay green characteristics; YL = Yield loss; BI = Base index; LN = Low nitrogen; OPT = Optimum nitrogen; LSD = Least significant difference Table 5 Grain yield and other agronomic traits of the maize hybrids (the best 15 and the worst 10 based on base index) evaluated across environments Hybrids GY DA DS ASI PHT EHT PASP Check-DZIFOO 5693.9 64 65 1 198.7 90.6 3.6 Check-HONAMPA 4686.9 61 62 1 192.5 83.4 3.6 Check-D778 5001.4 61 62 1 167.7 69.0 4.3 TZEEI-15 × TZEEI-21 3705.0 57 57 0 172.1 60.8 4.3 TZ EEI-6 × USTEWI-11 3983.4 51 54 3 138.3 45.1 3.9 TZEEI-6 × USTEWI-76 3638.0 49 50 1 146.8 54.2 3.9 USTEWI-11 × TZEEI-36 3480.7 57 59 2 163.7 60.5 4.4 USTEWI-7 × USTEWI-11 4408.6 55 58 2 143.7 55.7 4.0 TZEEI-6 × TZEEI-24 3466.9 60 61 1 178.7 75.2 3.4 TZEEI-15 × USTEWI-11 3777.0 53 54 2 152.1 49.5 4.8 TZEEI-21 × TZEEI-24 3411.1 56 55 1 169.1 68.2 4.6 CML 126 × TZEEI-36 3912.5 61 63 2 155.1 53.7 4.2 TZEEI-6 × TZEEI-21 3397.5 51 50 2 151.1 59.5 3.9 TZEEI-21 × USTEWI-76 3141.4 58 59 0 184.9 77.4 4.1 TZEEI-50 × TZEEI-4 4442.7 57 59 3 135.9 40.1 4.1 TZEEI-6 × USTEWI-8 2026.2 53 58 6 117.9 36.1 4.3 USTEEWI-2 × TZEEI-36 1551.7 61 63 3 125.9 47.7 4.0 CML 126 × TZEEI-50 3286.0 57 62 4 157.6 54.3 4.5 USTEWI-7 × TZEEI-36 2261.9 57 61 3 142.5 45.0 5.3 TZEEI-4 × USTEWI-76 2365.3 57 58 1 133.1 40.3 5.7 USTEWI-8 × USTEEWI-1 1834.6 51 53 2 146.5 43.2 5.1 USTEWI-7 × USTEEWI-1 2051.0 51 53 2 139.3 33.6 5.5 TZEEI-4 × TZEEI-36 2331.4 52 54 3 143.9 47.7 4.7 TZEEI-4 × USTEEWI-1 1205.3 51 54 4 131.5 30.4 5.7 USTEEWI-1 × TZEEI-36 1292.8 57 61 4 119.4 30.5 5.5 MEAN 2981.3 56 59 2 152.0 53.7 4.6 LSD 425.4 5 6 2 15.9 11.2 1.1 GY = Grain yield; DA = Days to 50% anthesis; DS = Days to 50% silking; ASI = Anthesis silking interval; PHT = Plant height; EHT = Ear height; PASP = Plant aspect; LSD = Least significant difference General combining ability effect for grain yield and other traits and cluster analysis for the identification of heterotic groups under the test environments The estimates of the GCA effect of the inbred lines for grain yield are presented in Table 6 . Inbreds CML 126, USTEWI-7, TZEEI-15, TZEEI-4, USTEWI-11, TZEEI-21, TZEEI-76 and TZEEI-24 had positive and highly significant (P < 0.01) GCA effect for grain yield under low nitrogen condition. Also, inbred lines CML 126, USTEWI-7, TZEEI-15, USTEWI-11, TZEEI-21 and TZEEI-76 exhibited positive and highly significant GCA effects for grain yield under optimum conditions. On the contrary, inbred lines TZEEI-4 and TZEEI-24 showed positive and highly significant (P < 0.01) GCA effects for grain yield under stress conditions but had negative and highly significant GCA effects for grain yield under optimum conditions. Inbred lines CML 126, USTEWI-7, TZEEI-15, USTEWI-11, TZEEI-21, TZEEI-76 and TZEEI-24 had positive and significant GCA effects for grain yield across environments. Negative significant GCA effect is desirable for anthesis silking interval, plant and ear height, and plant aspect. The results of the dendrogram constructed based on HGCAMT (Fig. 1 ) revealed three clusters. Cluster 1consist of CML 126, USTEEWI-2, TZEEI-24, TZEEI-15 and TZEEI-21; cluster 2 includes USTEWI-8, TZEEI-76 and USTEWI-11 while TZEEI-6, TZEEI-36, TZEEI-50, TZEEI-7, TZEEI-4 and USTEEWI-1 constituted cluster 3. Pswarayi and Vivek ( 2008 ) emphasized three key factors for selecting potential lines as testers for classifying other lines into heterotic groups. The factors include high GCA effect, heterotic group classification, and grain yield. Based on these criteria, CML 126 was the highest-yielding inbred line under low nitrogen conditions and across environments, had a high positive GCA effect for grain yield, and was placed in the first cluster and was, therefore, the best tester for cluster 1. Also, TZEEI-76 recorded the highest positive GCA effect, moderately high grain yield, was classified into the second cluster, and was therefore classified as the best tester for cluster 2. Furthermore, USTEWI-7 recorded the highest positive GCA effect, high grain yield under low nitrogen conditions, was classified into the third cluster, and was, therefore, the best tester for cluster 3. Table 6 Estimates of general combining ability effect of 14 white maize inbred lines for grain yield and other traits under low, optimum, and across nitrogen environments Parents GY ASI PHT EHT PASP LN OPT AC LN OPT AC LN OPT AC LN OPT AC LN OPT AC CML 126 142.9** 858.9** 500.0** 0.5 0.4 0.4* 17.8** 22.6** 20.1** 7.7** 10.3** 8.9** -0.1 -0.3** -0.2* USTEEWI-2 -523.9** -453.6** -489.7** -0.7** -0.9** -0.8** 4.6** 5.9** 5.2** 2.1* 6.3** 4.2** -0.4** 0.0 -0.2 TZEEI-6 -212.6** -9.5 -111.9** 0.1 0.9** 0.5** -9.3** -22.8** -16.1** -9.6** -14.6** -12.2** -0.1 0.6** 0.3** TZEEI-50 -254.1** -206.7** -231.3** -0.1 -0.1 -0.1 -5.5** -3.6** -4.7** -8.0** -5.2** -6.6** 0.1 -0.4** -0.1 USTEWI-7 264.2** 394.6** 328.4** 0.0 0.1 0.0 -4.2** 10.3** 2.9* -0.8 4.6** 1.8* 0.2 -0.2 0.0 TZEEI-15 404.7** 283.6** 343.2** -0.8** -0.9** -0.8** -1.4 7.1** 2.7* 0.2** 2.4* 1.3 -0.2 0.3** 0.1 TZEEI-4 42.8** -129.7** -44.4** -0.7** -0.5** -0.6** -8.8** -6.0** -7.5** -4.6 -1.7 -3.2** 0.2 0.1 0.1 USTEWI-8 -197.1 -256.0** -227.5 0.7** 0.8** 0.7** -0.1 1.4 0.6 -0.5** -1.9** -1.2 -0.1 -0.4** -0.2** USTEWI-11 707.6** 476.0** 590.9** 0.9** 0.2 0.6** 1.7 3.7* 2.6* 5.1** 3.7** 4.3** -0.1 -0.4** -0.2** TZEEI-21 388.2** 167.2** 276.8** -0.7** -0.6* -0.6** 16.4** 10.6** 13.4** 10.7** 8.1 9.4** -0.1 -0.2 -0.1 TZEEI-76 222.9** 198.5** 209.8** -0.2 -0.4* -0.3 2.8* -3.7* -0.6 7.3** 1.3 4.3** 0.3* 0.0 0.2* TZEEI-24 76.2** -6.4** 34.0** 0.0 -0.5* -0.2 9.9** 6.5** 8.1** 5.9** 7.4** 6.6** -0.3** -0.2* -0.3** USTEEWI-1 -820.1 -1041.2 -925.1 0.7** 1.4** 1.0** -16.1** -20.1** -17.4** -13.3** -17.2** -14.9** 0.6** 0.7** 0.6** TZEEI-36 -241.8** -275.6** -253.1** 0.4 0.0 0.1 -7.8** -12.0** -9.2** -2.3* -3.4** -2.5** -0.1 0.3* 0.1 SE 46.4 38.8 30.4 0.3 0.2 0.2 1.3 1.8 1.1 0.9 1.2 0.8 0.1 0.1 0.1 GY = Grain yield; ASI = Anthesis silking interval; PHT = Plant height; EHT = Ear height; PASP = Plant aspect; LN = Low nitrogen; OPT = Optimum nitrogen; AC = Across nitrogen environments; SE = standard error Discussion Highly significant differences (P < 0.01) detected among the hybrids and environment for grain yield and other traits under low nitrogen, optimal, and across environments indicated the presence of genetic variation among the hybrids and that the test environments were unique and highly variable (Obeng-Bio et al., 2019 ). Hybrid × environment interaction observed in this study for most measured traits across the test environments indicates that the hybrids responded differently under each nitrogen environment. This result is consistent with findings reported by Aboderin et al., ( 2023 ). The significant GCA and SCA effects for grain yield and other traits observed across the research conditions indicate that both additive and non-additive gene action was involved in the inheritance of the traits. These results are consistent with the findings reported by Habiba et al., ( 2022 ). The significant mean squares for both Env × GCA and Env × SCA interaction for all measured traits across environments except anthesis silking interval and ear per plant, and ear aspect and ear rot for Env × SCA confirmed that the parental lines expressed diverse performance in hybrid combinations under different environments. These results agree with Makinde et al., ( 2023 ). The significant Env × GCA interaction implies a need to select different parental lines for hybrid development under various environments. The significant Env × SCA interaction also implied that the single-cross hybrids' response differed under each environment. These findings agree with Ige et al., ( 2020 ). Heritability serves as an important metric in crop genetic enhancement as it quantifies the proportion of phenotypic variance that can be inherited from parents to progenies (Falconer, 1989). Additionally, it offers insights into the most suitable breeding approaches to employ and the potential degree of trait enhancement achievable through selective breeding. This study found moderate to high heritability for grain yield and other traits, meaning the parent plants have a strong genetic ability to pass these traits to their offspring. Abu et al. ( 2021 ) observed that traits with moderate to high heritability are more influenced by genetic factors than by environmental conditions. Ilyas et al. ( 2019 ) similarly reported that a high heritability estimate signifies the presence of additive gene action, ensuring the potential for crop improvement through selective breeding. The ratio of GCA/SCA was more than unity for most measured traits under stress and optimum nitrogen conditions. This shows that the GCA effect is stronger than the SCA effect for the traits studied, meaning the traits are mainly controlled by additive gene action and can be improved effectively through recurrent selection. Fasahat et al., ( 2016 ) reported that the preponderance of the GCA effect over SCA makes early-generation testing of genotypes more efficient, and promising hybrids can be identified and selected based on their predictions from the GCA effect. This result is consistent with the findings of several workers (Badu-Apraku et al., 2015 ; Ifie et al., 2015 ; Badu-Apraku et al., 2016 ). The mean grain yield reduction of the hybrids was 19.1%. This grain yield reduction is lower than that reported by other Authors. Meseka et al. ( 2006 ) found a 52% decrease in grain yield in hybrids under low nitrogen conditions. Makumbi et al. ( 2011 ) reported a 51% reduction in grain yield in hybrids under nitrogen stress. In comparison, the 19.1% reduction observed in this study suggests moderate nitrogen stress. This falls within the 10–50% range reported by Wolfe et al . (1988), indicating that the level of nitrogen stress applied was sufficient to identify hybrids tolerant or susceptible to low nitrogen conditions. The 12 most promising hybrids identified out of the best 15 and the 10 worst performing hybrids under low nitrogen conditions using the base index were TZEEI-15 × TZEEI-21, TZEEI-6 × USTEWI-11, TZEEI-6 × USTEWI-76, USTEWI-11 × TZEEI-36, USTEWI-7 × USTEWI-11, TZEEI-6 × TZEEI-24, TZEEI-15 × USTEWI-11, TZEEI-21 × TZEEI-24, CML 126 × TZEEI-36, TZEEI-6 × TZEEI-21, TZEEI-21 × USTEWI-76, and TZEEI-50 × TZEEI-4. The hybrids USTEWI-7 × USTEWI-11 and TZEEI-50 × TZEEI-4 were the highest yielding and stress-tolerant genotypes suggesting the presence of low nitrogen tolerant alleles in the parental lines. The hybrid check-DZIFOO was identified as the highest-yielding and most stable hybrid under low and optimum nitrogen conditions. This suggests that additional breeding programs are needed to develop crosses that can produce high yields under low nitrogen conditions. Inbred lines with a desirable GCA effect could be effectively used as parents to generate synthetic varieties and could be improved to tolerate stress. The significant positive GCA effect for grain yield detected for inbreds CML 126, USTEWI-7, TZEEI-15, TZEEI-4, USTEWI-11, TZEEI-21, TZEEI-76, TZEEI-24 under low nitrogen condition, CML 126, USTEWI-7, TZEEI-15, USTEWI-11, TZEEI-21, TZEEI-76 under optimum condition, and CML 126, USTEWI-7, TZEEI-15, USTEWI-11, TZEEI-21, TZEEI-76, TZEEI-24 across environment, indicate their usefulness in breeding for higher grain yield under contrasting environment. This also implies that the inbred lines could be good combiners for increasing grain yield by donating desirable alleles when crossed with other genetically variable lines to develop superior hybrids. The present study on cluster analysis of the maize inbred lines under low nitrogen conditions aimed at identifying distinct groups among the parental lines. The clustering technique in data analysis from breeding trials is to group inbred lines into several homogeneous groups such that those inbred lines within a group have similar response patterns (Wedwenssen, 2023). The cluster dendrogram constructed for data across the test environments using the HGCAMT method placed the inbred lines into three clusters. Cluster 1 was characterized by high grain yield, cluster 2 was also characterized by a high positive GCA effect for grain yield, while cluster 3 exhibited high grain yield and high positive GCA effect. Inbred lines CML 126, TZEEI-76, and USTEWI-7 were identified as the best testers for clusters 1, 2, and 3 respectively. This indicates that the crossing between superior genetic materials of the above diverse clusters might provide desirable recombinants for developing high-yielding genotypes under low soil nitrogen. This is because cluster analysis separates inbred lines into clusters that portray high homogeneity within a cluster and high heterogeneity between clusters (Hafiz et al., 2015 ). Conclusion In conclusion, grain yield and all other traits measured were controlled by additive gene action across the research environments. The HGCAMT method revealed three clusters for the inbred lines with CML 126, TZEEI-76, and USTEWI-7 emerging as best testers for clusters 1, 2, and 3 respectively. The hybrids USTEWI-7 × USTEWI-11 and TZEEI-50 × TZEEI-4 were identified as stress-tolerant genotypes with the highest grain yield. They should be tested on-farm in multiple locations to confirm their stability in performance and recommendation for release and commercialization in sub-Saharan Africa. Declarations Acknowledgment I am profoundly grateful to the Department of Crop and Soil Sciences field staff, Kwame Nkrumah University of Science and Technology, Ghana, for their invaluable technical assistance. I extend my heartfelt appreciation to Mr. Dennis Boama Darko, Mr. Clement Gyeabour Kyere, and Ms. Naomi Adoma for their diverse and significant contributions to this research. Financial support This research was partially funded by the Department of Crop and Soil Sciences, Kwame Nkrumah University of Science and Technology, Ghana. Conflict of interest I hereby declare that the study was carried out without any financial or commercial relationship that could result in a potential conflict of interest. Ethics Statement Not applicable Consent to Publish Not applicable Consent to Participate Not applicable Clinical Trial Not applicable References Abu P, Badu-Apraku B, Ifie BE, Tongoona P, Melomey LD and Offei SK (2021) Genetic diversity and inter-trait relationship of tropical extra-early maturing quality protein maize inbred lines under low soil nitrogen stress, PLos one, 16(6). 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Ogunniyan DJ, Ojo DK, Olakojo SA and Talabi OA (2019) Diallel analysis of maize inbred lines for agronomic traits in nitrogen stress and optimal condition, Ghana Jnl Agric. Sci. 54(1), 10-23. Pswarayi A and Vivek BS (2008) Combining ability amongst CIMMYT‟s early maturing maize ( Zea mays L.) germplasm under stress and non-stress conditions and identification of testers. Euphytica 162 :353–362 Ribeiro RP, Silva JM, and Costa LR (2022) Impact of nitrogen deficiency on yield loss in maize, Field Crops Research , 276, 108346 Rodriguez GA, Gregorio A, Agela P, Jose C and Juan B (2018) AGD-R (Genetic Analysis Design with R), version 5.0, Statistical Analysis System (SAS) (2002) SAS/STAT® User’s Guide, Version 9.1 . SAS Institute Inc. Steel RGD. and Torrie JH (1980) Principles and procedures of statistics. 2nd edn. Tajamul RS, Kamlesh P and Pradyuman K (2016) Maize - A potential source of human nutrition and health: A review, Cogent Food and Agriculture, 2(1). https:// doi.org/10.1080/23311932.2016.1166995 Wendwessen T (2023) Cluster and principal component analysis of maize inbred lines in low moisture stress areas in Ethiopia . Int J Agric Sc Food Technol , 9(3): 059-063. Yadesa L and Diro D (2023) Nutritional and specialty maize production, consumption and promising impact of Ethiopia’s food and nutrition security, EAS J nutr food sci, 5(5): 2663- 708. Zingore S, Njoroge S (2022) Soil Organic Matter Regulates Maize Productivity and Fertilizer Response in Maize Production. Growing Africa 1(1), 8-11. Additional Declarations No competing interests reported. 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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-6379832","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":452142095,"identity":"307a77a0-7ac9-46dd-a943-45fce18b22c6","order_by":0,"name":"George Obeng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBElEQVRIiWNgGAWjYDACCSQ24wcDG1QRglqYJQrSSNTCwPPhMGEt/NLNxx5+YaiV45c+fvGBhMH5xP7ZzQcfMNTYROPSIjnnWLqxDMNxY8m+nGKDAoPbiTPuHEs2YDiWltuAQ4vBjRwzaQmGY4kbzvCkSUgAtTQARSQYGw7j0ZL/DaSlHqgl/QePwbnE+YS15LBJfmCoSTA4w36MgcfgQOIGQlqAfjGTZjA4YDizh4dZWsIg2XjjjbRkgwQ8fgGG2DPJHxV18vw87A8/fvhjJzvvRvLBBx9qbHBqAQFmHgNgdABdBeI4glUm4FEOAow/GOqAFPsDEMeegOJRMApGwSgYgQAAuc5cFUnFDzwAAAAASUVORK5CYII=","orcid":"","institution":"Kwame Nkrumah University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"George","middleName":"","lastName":"Obeng","suffix":""},{"id":452142097,"identity":"03387cb5-bd78-4f9a-93a6-e9a0391889ef","order_by":1,"name":"Benjamin Annor","email":"","orcid":"","institution":"Kwame Nkrumah University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"","lastName":"Annor","suffix":""},{"id":452142098,"identity":"f2597a37-f443-47b4-aeea-c769b0914f11","order_by":2,"name":"Alexander Wireko Kena","email":"","orcid":"","institution":"Kwame Nkrumah University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"Wireko","lastName":"Kena","suffix":""}],"badges":[],"createdAt":"2025-04-05 05:08:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6379832/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6379832/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82182444,"identity":"597b896e-376a-4d17-8aad-c5c7b62de634","added_by":"auto","created_at":"2025-05-07 12:17:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":49606,"visible":true,"origin":"","legend":"\u003cp\u003eDendrogram of 14 maize inbred lines constructed from GCA effect of grain yield and other traits (HGCAMT) using Ward’s minimum variance cluster analysis across the test environments\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6379832/v1/3c30a9e40186415b8dd1b2bf.png"},{"id":88602949,"identity":"af358446-dd4e-4b64-8d58-1aa97b9f8a7c","added_by":"auto","created_at":"2025-08-08 08:10:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1762318,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6379832/v1/00b0652f-782c-4988-a824-f0515355ef66.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eGenetic Analysis of White Maize (Zea Mays L.) Inbred Lines Under Low Soil Nitrogen\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMaize (Zea mays) holds a paramount status as one of the world's key cereal crops, ranking third in global production following wheat and rice. Its remarkable adaptability enables widespread cultivation across various agroecological zones in West and Central Africa (Yadesa and Diro, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The economic significance of maize has been on a steady rise, with forecasts indicating its trajectory to surpass other cereal crops and emerge as the foremost crop by 2025 (FAOSTAT, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Maize serves multiple purposes, being utilized as a staple food for humans, fodder for livestock, and a versatile resource for producing biofuel, edible oil, and various industrial goods (Tajamul et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Maize contributes significantly to dietary needs, providing approximately one-fifth of the total daily calorie intake and contributing between 17 and 60% of the daily protein supply across Africa (Yadesa and Diro, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe annual worldwide land area dedicated to growing maize is approximately 197\u0026nbsp;million hectares (FAOSTAT, 2021). In sub-Saharan Africa (SSA), approximately 30\u0026nbsp;million hectares of arable land are allocated to maize cultivation (Annor et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, although there is considerable potential for boosting maize production in Ghana, the grain yield on farmers' fields has declined, averaging only 1.95 t/ha. This starkly contrasts the significantly higher yields observed in countries like the United States of America and China, where yields reach 11.07 t/ha and 10.53 t/ha respectively (FAOSTAT, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The low grain yield across sub-Saharan Africa (SSA) can be partly attributed to the surge in biotic and abiotic stresses such as heat, drought, and inadequate soil fertility (Badu-Apraku et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Biotic stresses encompass a range of challenges such as diseases like leaf blight and maize lethal necrosis, contamination by aflatoxins, and the presence of pests such as striga, weevils, armyworms, and stem borers (Njeru et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Contributing to this scenario are factors like the slow adoption of improved maize varieties and socioeconomic constraints like limited financial resources, inadequate processing and marketing infrastructure, and challenges in post-harvest handling (Mutungi et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Among the abiotic stresses, nitrogen deficiency is a critical issue constraining maize production in tropical regions. This deficiency worsens due to nutrient loss and low soil organic matter, making it difficult for smallholder farmers in Africa to grow maize sustainably (Zingore and Njoroge, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Notably, nitrogen inadequacy alone incurs substantial yield losses in maize, ranging from 10\u0026ndash;50% in West Africa (Badu-Apraku et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Ribeiro et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The productivity of maize exhibits variability across different soil fertility levels and nitrogen utilization efficiencies due to differences in gene expression related to maize's tolerance to low nitrogen conditions within various varieties (Ogunniyan et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUnderstanding the combining abilities, heritability, and heterotic patterns of parental lines under nitrogen stress is important for identifying high-yielding hybrids suitable for commercial cultivation. Additionally, insights into the genetic diversity and population structure of inbred lines within hybrid breeding programs enable breeders to develop hybrids exhibiting strong heterosis and enhanced adaptation to varied environmental conditions (Abu et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Ultimately, the ability to meet the rising need for resilient maize cultivars amidst shifting environmental challenges hinges on harnessing the wealth of genetic variability within maize populations.\u003c/p\u003e \u003cp\u003eThis study aims to contribute to the improvement of maize production in Ghana through increasing productivity by developing hybrids with high-yielding and low nitrogen tolerance potentials. The specific objectives of the study are to; (i) determine the level of tolerance of the hybrids under low soil nitrogen conditions, (ii) examine the mode of inheritance of grain yield and other traits of the inbred lines under low and optimum nitrogen conditions and (iii) assess the genetic diversity of the inbred lines under low and optimum nitrogen conditions.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy site\u003c/h2\u003e \u003cp\u003eThe study was conducted at the Maize Breeding Pipeline (Animal Science Department) of the Kwame Nkrumah University of Science and Technology, Kumasi-Ghana. The site is situated at a latitude of N 6\u0026deg;40'52.34952\" and a longitude of W 1\u0026deg;33'25.45812\" within the tropical rainforest climate zone. The area experiences a bimodal rainfall pattern with two main rainy seasons, the major season from March to July and the minor season from September to November. The average annual rainfall is around 1,448 mm and an average temperature of 24\u0026deg;C. The soil type is haplic alisols (Jones et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGenetic Materials\u003c/h3\u003e\n\u003cp\u003eFourteen (14) white maize inbred lines (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) used in the present study were sourced from KNUST Maize Improvement Program of the Crop and Soil Sciences Department, KNUST.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of inbred lines\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEntry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInbred lines\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEntry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInbred lines\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCML 126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSTEWI-8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSTEEWI-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSTEWI-11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTZEEI-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTZEEI-21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTZEEI-50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTZEEI-76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSTEWI-7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTZEEI-24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTZEEI-15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSTEEWI-1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTZEEI-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTZEEI-36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eGeneration of Diallel Crosses\u003c/h3\u003e\n\u003cp\u003eThe 14 parental lines were crossed using a diallel mating design to generate ninety-one (91) single-cross hybrids. The inbred lines were crossed in all possible hybrid combinations without reciprocals and self, assuming no reciprocal effect of low nitrogen tolerance in maize, following Griffing\u0026rsquo;s (1956) diallel method four.\u003c/p\u003e\n\u003ch3\u003eField evaluation\u003c/h3\u003e\n\u003cp\u003eThe hybrids were evaluated under low (30 N kg/ha) and optimum (90 kg/ha) nitrogen conditions within the 2022 major cropping season. The experimental field was depleted of nitrogen due to continuous cultivation of densely populated maize and removal of all crop residues after harvest for many seasons. Before field preparation, soil samples from 0 to 15 cm depth were taken for analysis at the Soil Research Institute (SRI), Kwadaso-Kumasi. The Kjeldahl digestion and distillation procedure (Bremner and Mulvaney, 1982) was used for the analysis of the soil samples to determine the levels of Nitrogen (N), Phosphorus (P), and potassium (K). The soil contained 0.10% of N, 38.66 ppm of P, and 0.30 me/100g of K. Based on the soil test, urea was applied on the low nitrogen field immediately after thinning to bring the nitrogen content to 30kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at 2 weeks after planting (WAP). In addition, 60kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e each of P and K in the form of single superphosphate (P\u003csub\u003e2\u003c/sub\u003e0\u003csub\u003e5\u003c/sub\u003e) and muriate of potash (K\u003csub\u003e2\u003c/sub\u003eO) fertilizers were applied. For the experiment under optimal conditions, NPK (15:15:15) was applied at 2 WAP to supply 60kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e each of N, P, and K and top-dressed with an additional 30kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at 4 WAP.\u003c/p\u003e\n\u003ch3\u003eField Layout\u003c/h3\u003e\n\u003cp\u003eThe hybrid experiment (91 diallel crosses plus 9 hybrid checks) was laid out using a 10 \u0026times; 10 alpha lattice design with two replications. Each experimental unit was a single-row plot, 4 m long with a row spacing of 0.75 m and intra-row spacing of 0.4 m. Three seeds were planted and the seedlings were thinned to two per hill at 2 WAP to give a final plant population density of about 66,666 plants ha\u003csup\u003e\u0026ndash;1\u003c/sup\u003e. Weeds were controlled manually.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Collection\u003c/h2\u003e \u003cp\u003eDays to 50% anthesis (DA) was recorded as the number of days from planting to when 50% of the plants in a plot had shed pollen. Days to 50% silking (DS) was obtained as the number of days from planting to when 50% of the plants in a plot had silks. Anthesis silking interval (ASI) was determined as the difference between DS and DA. The low nitrogen trial was assessed for stay green characteristic (STGR) at 65 days after planting based on leaf senescence on a scale of 1\u0026ndash;9; where 1\u0026thinsp;=\u0026thinsp;0\u0026ndash;10% dead leaf area and 9\u0026thinsp;=\u0026thinsp;81\u0026ndash;100% dead leaf area, respectively. Plant height (PHT) and ear height (EHT) were scored as the distance from the base of the plant to the height of the first tassel branch and the node bearing the upper ear, respectively. Husk cover (HC) was recorded on a scale of 1\u0026ndash;9; where 1\u0026thinsp;=\u0026thinsp;tightly arranged husks extending beyond the tip of the ear and 9\u0026thinsp;=\u0026thinsp;completely exposed ear tip. The number of ears per plant (EP) was calculated as the number of ears harvested per plot divided by the number of plants harvested. Plant aspect (PASP) was examined on a plot basis after flowering when plants were still green and ears fully developed on a scale of 1 to 9 where 1\u0026thinsp;=\u0026thinsp;excellent and 9\u0026thinsp;=\u0026thinsp;very poor. The PASP was the general appeal of the whole plant, based on the uniformity of the plant stands, plant and ear heights, reaction to diseases and insects as well as lodging. Ear aspect (EASP) was recorded on a scale of 1\u0026ndash;9; where 1\u0026thinsp;=\u0026thinsp;uniform, well-filled, large, and disease-free ears and 9\u0026thinsp;=\u0026thinsp;undesirable ear features. Ear rot (ERT) was determined by counting the rotted ears per plot. Field weight (FW) was determined by weighing the ears harvested per plot after de-husking. Grain weight was determined by weighing the grains shelled per plot in kilograms using a digital weighing balance. The moisture content in the grains was determined using a grain moisture meter. Grain yield was determined in kilogram per hectare from the grain weight, adjusted to 15% moisture content under low nitrogen conditions. Under optimum conditions, a shelling percentage of 80 was assumed for all plots, and grain yield was calculated using ear weight adjusted to 15% moisture content.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eAnalysis of Variance\u003c/h2\u003e \u003cp\u003eAnalysis of variance (ANOVA) was performed on plot means for grain yield and other agronomic traits collected for each and across the environment using the Procedure for Generalized Linear Model (PROC GLM) in Statistical Analysis System (SAS) (SAS Institute, 2002). The genotypes were considered fixed effects while environments, replications, and blocks within replications were random effects. The least significant difference (LSD) according to Steel and Torrie (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1980\u003c/span\u003e) was used to separate the means. The statistical models for each and across the environments were denoted as equations 1 and 2 respectively:\u003c/p\u003e \u003cp\u003eY\u003cem\u003eijk\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026micro;\u0026thinsp;+\u0026thinsp;G\u003cem\u003ei\u003c/em\u003e\u0026thinsp;+\u0026thinsp;R\u003cem\u003ej\u003c/em\u003e\u0026thinsp;+\u0026thinsp;B\u003cem\u003ek (j)\u003c/em\u003e + Ɛ\u003cem\u003eijk\u003c/em\u003e \u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;Eqn 1\u003c/p\u003e \u003cp\u003eY\u003cem\u003eijlk\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026micro;\u0026thinsp;+\u0026thinsp;E\u003cem\u003el\u003c/em\u003e\u0026thinsp;+\u0026thinsp;R\u003cem\u003ej (l)\u003c/em\u003e\u0026thinsp;+\u0026thinsp;B\u003cem\u003ek (lj)\u003c/em\u003e\u0026thinsp;+\u0026thinsp;G\u003cem\u003ei\u003c/em\u003e\u0026thinsp;+\u0026thinsp;EG\u003cem\u003eli\u003c/em\u003e + Ɛ\u003cem\u003eijlk\u003c/em\u003e \u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;.... Eq.\u0026nbsp;2\u003c/p\u003e \u003cp\u003eWhere Y\u0026thinsp;=\u0026thinsp;observation, \u0026micro;\u0026thinsp;=\u0026thinsp;overall mean, G\u0026thinsp;=\u0026thinsp;genotype effect, E\u0026thinsp;=\u0026thinsp;environment effect, Block\u0026thinsp;=\u0026thinsp;effect of the block, R\u0026thinsp;=\u0026thinsp;replicate effect, EG\u0026thinsp;=\u0026thinsp;interaction effect between environment and genotype and Ɛ = error\u003c/p\u003e \u003cp\u003eExcluding the checks, the GCA effects of the parents and the SCA of the crosses for grain yield, days to 50% silking, days to 50% anthesis, anthesis silking interval, plant height, ear height, ear aspect, ear per plant, plant aspect and low nitrogen environment for stay green characteristics were estimated using AGD-R statistical package, version 5.0 developed by Rodriquez \u003cem\u003eet al\u003c/em\u003e., (2018). The GCA and SCA effects were tested for significance using the t-test and the standard errors were estimated as the square root of the GCA and SCA variances. The statistical models for diallel analysis of each and across environment were as follows;\u003c/p\u003e \u003cp\u003eY\u003cem\u003eijlk\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026micro;\u0026thinsp;+\u0026thinsp;R\u003cem\u003ei\u003c/em\u003e\u0026thinsp;+\u0026thinsp;Gj\u0026thinsp;+\u0026thinsp;Gk\u0026thinsp;+\u0026thinsp;S\u003cem\u003ejk\u003c/em\u003e + Ɛ\u003cem\u003eijlk \u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;..\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u003c/em\u003e Eq.\u0026nbsp;1\u003c/p\u003e \u003cp\u003eY\u003cem\u003eijlk\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026micro;\u0026thinsp;+\u0026thinsp;E\u003cem\u003ep\u003c/em\u003e\u0026thinsp;+\u0026thinsp;R\u003cem\u003ei\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e)\u0026thinsp;+\u0026thinsp;Gj\u0026thinsp;+\u0026thinsp;Gk\u0026thinsp;+\u0026thinsp;S\u003cem\u003ejk\u003c/em\u003e\u0026thinsp;+\u0026thinsp;E\u003cem\u003ep\u003c/em\u003e*G\u0026thinsp;+\u0026thinsp;Ep*S\u003cem\u003ejk\u003c/em\u003e + Ɛ\u003cem\u003eijlpk\u003c/em\u003e \u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;.\u0026hellip;. Eq.\u0026nbsp;2\u003c/p\u003e \u003cp\u003eWhere; Y\u003cem\u003eijlk\u003c/em\u003e\u0026thinsp;=\u0026thinsp;the observation of parents, \u0026micro;\u0026thinsp;=\u0026thinsp;the overall mean, Ri\u0026thinsp;=\u0026thinsp;replication effect, E\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;effect of the environment, Gj and Gk\u0026thinsp;=\u0026thinsp;the general combining ability (GCA) effect of the \u003cem\u003ej\u003c/em\u003eth and \u003cem\u003ek\u003c/em\u003eth parents, S\u003cem\u003ejk\u003c/em\u003e\u0026thinsp;=\u0026thinsp;specific combining ability effect (interaction effect) of the \u003cem\u003ej\u003c/em\u003eth and \u003cem\u003ek\u003c/em\u003eth parent and Ɛ\u003cem\u003eijk\u003c/em\u003e is the error associated with the observations \u003cem\u003eijk\u003c/em\u003eth\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eHeritability estimates\u003c/h2\u003e \u003cp\u003eBroad sense heritability was estimated from the mean square values of the grain yield and other agronomic traits.\u003c/p\u003e \u003cp\u003eBroad sense heritability (\u003cem\u003eH\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e) = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{{{\\sigma\\:}}_{A}^{2}\\:+{\\:{\\sigma\\:}}_{D}^{2}}{{{\\sigma\\:}}_{A}^{2}+{{\\sigma\\:}}_{D}^{2}+{{\\sigma\\:}}_{E}^{2}\\:}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSelection of inbred lines under nitrogen stress using low-N base index\u003c/h2\u003e \u003cp\u003eThe low nitrogen base index (LNBI) proposed by Badu-Apraku \u003cem\u003eet al.\u003c/em\u003e, (2011) that combined grain yield (GY) under nitrogen stress with plant aspect (PASP), ear aspect (EASP), anthesis-silking interval (ASI), number of ears per plant (EPP) and the stay-green characteristic (STGR) was adopted to identify low nitrogen tolerant genotypes. Before the analysis, each trait was standardized to achieve a mean of zero and a standard deviation of 1 to reduce the effects of different scales used for measuring various traits. A positive value of LNBI was an indicator of tolerance to nitrogen stress while a negative value indicated susceptibility. The base index was estimated using the following equation:\u003c/p\u003e \u003cp\u003eLNBI = [(2 \u0026times; GY)\u0026thinsp;+\u0026thinsp;EPP - ASI - PASP - EASP - STGR].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of genetic diversity\u003c/h2\u003e \u003cp\u003eThe clustering of inbred lines into heterotic groups was based on the GCA effect of multiple traits of inbreds (HGCAMT) method as suggested by Badu-Apraku et al., (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This method was employed by identifying the traits with significant mean squares across the test environment and standardizing their GCA effects to reduce the effect of different rating scales used to measure the traits. Thereafter, the standardized GCA values were used for cluster analysis based on Ward\u0026rsquo;s minimum variance method implemented in SAS (SAS Institute, 2002).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of variance and heritability estimates of the hybrids evaluated under the test environments\u003c/h2\u003e \u003cp\u003eThe analysis of variance for the hybrids showed highly significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) for grain yield and other measured traits under low nitrogen conditions except for anthesis silking interval, plant aspect, and ear per plant (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). General combining ability (GCA) was highly significant for grain yield and all other traits except ear per plant. Specific combining ability (SCA) was highly significant for grain yield, ear height, ear rot, and plant height, all other traits were not significant. Moderate to high broad sense heritability estimates were revealed for the measured traits ranging from 56% for plant aspect to 96% for grain yield. The ratio of GCA/SCA was more than unity for all measured traits.\u003c/p\u003e \u003cp\u003eUnder optimum conditions, highly significant differences were observed among the hybrids for grain yield and other traits except ear per plant and ear rot (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). GCA was highly significant for grain yield and other traits except ear rot. SCA was highly significant for all measured traits except husk cover, ear per plant, and ear rot. Broad sense heritability estimates ranged from 49% for ear per plant to 97% for grain yield. In general, moderate to high heritability estimates were observed for the measured traits. The ratio of GCA/SCA was more than unity for all measured traits except ear rot.\u003c/p\u003e \u003cp\u003eThe combined analysis of variance of the hybrids across the test environments revealed highly significant mean squares for grain yield and other traits except ear per plant (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Highly significant differences were observed for the environments for all measured traits except anthesis silking interval, husk cover, ear per plant, and ear aspect. Hybrid \u0026times; environment interactions were significantly different for grain yield, plant aspect, days to 50% anthesis, and plant height, all other traits were not significant. Mean squares due to GCA were highly significant for grain yield and other traits except ear per plant. Highly significant differences in SCA effect were observed for grain yield and all other characters except plant aspect and ear per plant. The environment \u0026times; GCA interaction showed highly significant differences for grain yield and all other traits except anthesis silking interval and ear per plant. Mean squares due to environment \u0026times; SCA interaction were highly significant for grain yield, days to 50% silking, plant height, and plant aspect. Anthesis silking interval, ear per plant, ear aspect, and ear rot were not significant. Moderate to high broad sense heritability estimates were revealed for the measured traits ranging from 53% for ear per plant to 98% for grain yield. The ratio of GCA/SCA was more than unity for all measured traits\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean squares from the analysis of variance, heritability estimates and GCA/SCA ratio for grain yield and other traits of the hybrids evaluated under low and optimum nitrogen conditions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource of variation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGY\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eASI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePHT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eEHT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePASP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eEPP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eEASP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEROT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eSTGR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"14\" nameend=\"c14\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLow Nitrogen\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e216.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1010.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e988.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e353.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e6.1**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlock (Rep)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e281240.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.5**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.5**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e496.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e256.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.9**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHybrid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1294450.0**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.5**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e401.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e248.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e6.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.1*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3907877.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e134.0**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e109.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.0**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2306.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1204.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e18.5**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2.5**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e873234.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e135.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e87.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e6.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eError\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111326.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eH\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGCA/SCA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"14\" nameend=\"c14\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOptimum Nitrogen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99210.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.7*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e188.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e71.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4.5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e35.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlock (Rep)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71807.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e102.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1067**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e480.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3.5**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHybrid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1535868**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e595.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e333.5**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5092919.5**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e140.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3694.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1600.0**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e9.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e655313.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e374.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e180.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eError\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77875.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e159.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e73.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eH\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGCA/SCA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"14\"\u003e*, ** = 0.05 and 0.01 probability levels, respectively; Rep\u0026thinsp;=\u0026thinsp;replication; DF\u0026thinsp;=\u0026thinsp;degree of freedom; GY\u0026thinsp;=\u0026thinsp;grain yield; DA\u0026thinsp;=\u0026thinsp;days to 50% anthesis; DS\u0026thinsp;=\u0026thinsp;days to 50% silking; ASI\u0026thinsp;=\u0026thinsp;anthesis silking interval; PHT\u0026thinsp;=\u0026thinsp;plant height; EHT\u0026thinsp;=\u0026thinsp;ear height; PASP\u0026thinsp;=\u0026thinsp;plant aspect; HC\u0026thinsp;=\u0026thinsp;husk cover; EPP\u0026thinsp;=\u0026thinsp;ear per plant; EASP\u0026thinsp;=\u0026thinsp;ear aspect; EROT\u0026thinsp;=\u0026thinsp;ear rot; GCA\u0026thinsp;=\u0026thinsp;General combining ability; SCA\u0026thinsp;=\u0026thinsp;Specific combining ability; H\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;Broad sense heritability\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean squares from the analysis of variance, heritability estimates and GCA/SCA ratio for grain yield and other traits for the hybrids evaluated across the environments\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource of variation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGY\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eASI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePHT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eEHT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePASP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eEPP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eEASP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eEROT\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnv\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43636768.0**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1918.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1879.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1496.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e721.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e11.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e475.2**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRep (Env)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49713.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e51.7*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e599.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e529.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e194.5**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlock (Env \u0026times; Rep)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e176524.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e75.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e781.5**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e368.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e6.8**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHybrid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2390266.0**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e821.5**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e493.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.0**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e6.8**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnv \u0026times; Hybrid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e440051.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e176.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e88.8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8218635.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e239.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e173.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.5**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5261.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2597.0**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e9.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e16.3**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1164539.0**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e29.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e330.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e163.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e6.1*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnv \u0026times; GCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e745122.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e591.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e162.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.6*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e4.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e7.7*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnv \u0026times; SCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e361478.5**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e180.3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e102.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95712.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e121.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e59.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eH\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGCA/SCA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e15.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e15.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e*, ** = 0.05 and 0.01 probability levels, respectively; Rep\u0026thinsp;=\u0026thinsp;replication; DF\u0026thinsp;=\u0026thinsp;degree of freedom; GY\u0026thinsp;=\u0026thinsp;grain yield; DA\u0026thinsp;=\u0026thinsp;days to 50% anthesis; DS\u0026thinsp;=\u0026thinsp;days to 50% silking; ASI\u0026thinsp;=\u0026thinsp;anthesis silking interval; PHT\u0026thinsp;=\u0026thinsp;plant height; EHT\u0026thinsp;=\u0026thinsp;ear height; PASP\u0026thinsp;=\u0026thinsp;plant aspect; HC\u0026thinsp;=\u0026thinsp;husk cover; EPP\u0026thinsp;=\u0026thinsp;ear per plant; EASP\u0026thinsp;=\u0026thinsp;ear aspect; EROT\u0026thinsp;=\u0026thinsp;ear rot; GCA\u0026thinsp;=\u0026thinsp;General combining ability; SCA\u0026thinsp;=\u0026thinsp;Specific combining ability; H\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;Broad sense heritability\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003ePerformance of the hybrids under stress and optimum conditions\u003c/h2\u003e \u003cp\u003eThe mean grain yield of the hybrids under low nitrogen conditions ranged from 1085 kg/ha for TZEEI-4 \u0026times; USTEEWI-1 to 4788.7 kg/ha for Check-DZIFOO with an overall mean yield of 2651.0 kg/ha (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The performance of hybrids check-DZIFOO, check-HONAMPA, TZEEI-50 \u0026times; TZEEI-4 and USTEWI-7 \u0026times; USTEWI-11 with their respective mean grain yield of 4788.7, 4643.7, 4350.5 and 4338.8 kg/ha were significantly higher than the average grain yield of the other hybrids. Among the best 15 and worst 10 of the 100 maize hybrids selected based on their performance under stress condition using base index, hybrids TZEEI-15 \u0026times; TZEEI-21, TZEEI-6 \u0026times; USTEWI-11, TZEEI-6 \u0026times; USTEWI-76, USTEWI-11 \u0026times; TZEEI-36, USTEWI-7 \u0026times; USTEWI-11, TZEEI-6 \u0026times; TZEEI-24, TZEEI-15 \u0026times; USTEWI-11, TZEEI-21 \u0026times; TZEEI-24, CML 126 \u0026times; TZEEI-36, TZEEI-6 \u0026times; TZEEI-21, TZEEI-21 \u0026times; USTEWI-76, TZEEI-50 \u0026times; TZEEI-4 with mean grain yield of 3603.8, 3956.9, 3418.5, 3444.4, 4338.8, 3103.1, 3560.0, 2916.7, 3706.2, 3174.9, 3117.0 and 4350.5 kg/ha respectively were identified to be tolerant to low nitrogen stress. Yield loss was relatively higher in the susceptible hybrids than in the tolerant hybrids. The average yield loss of 19.1% was recorded for the hybrids ranging from 1.3% for TZEEI-6 \u0026times; USTEWI-11 to 75.0% for Check-ARG 8900.\u003c/p\u003e \u003cp\u003eUnder the optimum condition, the mean grain yield of the hybrids ranged from 1325.5 kg/ha for TZEEI-4 \u0026times; USTEEWI-1 to 6599.2 kg/ha for Check-DZIFOO with an overall mean of 3311.6 kg/ha (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The hybrid check, DZIFOO recorded the highest grain yield with an average yield of 6599.2 kg/ha which was significantly higher than the mean yield of other hybrids.\u003c/p\u003e \u003cp\u003eGrain yield of hybrids across the two nitrogen environments varied from 1205.3 kg/ha for TZEEI-4 \u0026times; USTEEWI-1 to 5693.9 kg/ha for DZIFOO with an overall mean of 2981.3kg/ha (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The best performing check (DZIFOO) differ significantly in grain yield when compared with the single cross hybrid TZEEI-50 \u0026times; TZEEI-4 across nitrogen environment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGrain yield and other agronomic traits of the maize hybrids (the best 15 and the worst 10 based on base index) evaluated under low and optimum nitrogen conditions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"19\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHybrids\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eGY\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eDA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eDS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eASI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003ePHT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003eEHT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003ePASP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003eSTGR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c18\"\u003e \u003cp\u003e% YL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c19\"\u003e \u003cp\u003eBI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eLN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eOPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eLN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eOPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eLN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eOPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eLN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eOPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003eLN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCheck-DZIFOO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4788.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6599.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e195.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e201.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e92.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e89.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e27.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e12.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCheck-HONAMPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4643.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4730.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e184.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e200.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e84.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e82.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCheck-D778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4173.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5829.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e163.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e172.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e69.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e68.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e28.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-15 \u0026times; TZEEI-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3603.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3806.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e165.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e178.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e55.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e66.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZ EEI-6 \u0026times; USTEWI-11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3956.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4009.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e146.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e129.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e51.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e38.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e 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align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e161.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e132.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e65.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e42.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e 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colname=\"c11\"\u003e \u003cp\u003e160.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e59.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e61.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSTEWI-7 \u0026times; USTEWI-11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4338.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4478.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e140.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e147.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e 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\u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-15 \u0026times; USTEWI-11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3560.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3994.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e146.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e158.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e51.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e47.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e 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colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e179.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e177.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e76.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e74.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e27.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCML 126 \u0026times; TZEEI-36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3706.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4118.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e153.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e156.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e54.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e52.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-6 \u0026times; TZEEI-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3174.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3620.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e168.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e133.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e70.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e48.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e12.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-21 \u0026times; USTEWI-76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3117.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3165.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e182.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e187.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e79.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e75.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e 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namest=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e136.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e135.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e43.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e36.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-6 \u0026times; USTEWI-8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1760.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2294.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e125.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e110.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e39.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e32.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e23.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e-5.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSTEEWI-2 \u0026times; TZEEI-36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1368.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1734.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e127.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e124.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e42.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e52.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e-5.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCML 126 \u0026times; TZEEI-50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2534.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4037.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e152.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e163.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e46.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e62.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e37.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e-5.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSTEWI-7 \u0026times; TZEEI-36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1319.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3204.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e128.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e156.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e38.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e54.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e58.8\u003c/p\u003e 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USTEEWI-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1216.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2452.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e138.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e154.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e40.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e45.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e50.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e-5.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSTEWI-7 \u0026times; USTEEWI-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1190.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2911.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e125.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e153.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e28.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e38.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e 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\u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e128.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e158.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e38.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e56.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e55.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e-6.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-4 \u0026times; USTEEWI-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1085.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1325.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e 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\u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSTEEWI-1 \u0026times; TZEEI-36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1217.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1368.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e118.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e119.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e-11.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMEAN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e 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\u003cp\u003e\u003cb\u003e150.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e154.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e52.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e55.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e4.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e4.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cb\u003e4.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u003cb\u003e19.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLSD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e666.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e538.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e18.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e26.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e13.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e17.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e1.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e1.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cb\u003e1.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"19\"\u003eGY\u0026thinsp;=\u0026thinsp;Grain yield; DA\u0026thinsp;=\u0026thinsp;Days to 50% anthesis; DS\u0026thinsp;=\u0026thinsp;Days to 50% silking; ASI\u0026thinsp;=\u0026thinsp;Anthesis silking interval; PHT\u0026thinsp;=\u0026thinsp;Plant height; EHT\u0026thinsp;=\u0026thinsp;Ear height; PASP\u0026thinsp;=\u0026thinsp;Plant aspect; STGR\u0026thinsp;=\u0026thinsp;Stay green characteristics; YL\u0026thinsp;=\u0026thinsp;Yield loss; BI\u0026thinsp;=\u0026thinsp;Base index; LN\u0026thinsp;=\u0026thinsp;Low nitrogen; OPT\u0026thinsp;=\u0026thinsp;Optimum nitrogen; LSD\u0026thinsp;=\u0026thinsp;Least significant difference\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGrain yield and other agronomic traits of the maize hybrids (the best 15 and the worst 10 based on base index) evaluated across environments\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHybrids\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGY\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eASI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePHT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEHT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePASP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCheck-DZIFOO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5693.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e198.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCheck-HONAMPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4686.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e192.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCheck-D778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5001.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e167.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e69.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-15 \u0026times; TZEEI-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3705.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e172.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZ EEI-6 \u0026times; USTEWI-11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3983.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e138.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-6 \u0026times; USTEWI-76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3638.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e146.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e54.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSTEWI-11 \u0026times; TZEEI-36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3480.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e163.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSTEWI-7 \u0026times; USTEWI-11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4408.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e143.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-6 \u0026times; TZEEI-24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3466.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e178.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-15 \u0026times; USTEWI-11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3777.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e152.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e49.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-21 \u0026times; TZEEI-24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3411.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e169.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e68.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCML 126 \u0026times; TZEEI-36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3912.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e155.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-6 \u0026times; TZEEI-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3397.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e151.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e59.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-21 \u0026times; USTEWI-76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3141.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e 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\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1551.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e125.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e47.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCML 126 \u0026times; TZEEI-50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3286.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e157.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e54.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSTEWI-7 \u0026times; TZEEI-36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2261.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e142.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-4 \u0026times; USTEWI-76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2365.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e133.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSTEWI-8 \u0026times; USTEEWI-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1834.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e146.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSTEWI-7 \u0026times; USTEEWI-1\u003c/p\u003e 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colname=\"c6\"\u003e \u003cp\u003e131.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSTEEWI-1 \u0026times; TZEEI-36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1292.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e119.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMEAN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2981.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e56\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e59\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e152.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e53.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e4.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLSD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e425.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e15.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e11.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eGY\u0026thinsp;=\u0026thinsp;Grain yield; DA\u0026thinsp;=\u0026thinsp;Days to 50% anthesis; DS\u0026thinsp;=\u0026thinsp;Days to 50% silking; ASI\u0026thinsp;=\u0026thinsp;Anthesis silking interval; PHT\u0026thinsp;=\u0026thinsp;Plant height; EHT\u0026thinsp;=\u0026thinsp;Ear height; PASP\u0026thinsp;=\u0026thinsp;Plant aspect; LSD\u0026thinsp;=\u0026thinsp;Least significant difference\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eGeneral combining ability effect for grain yield and other traits and cluster analysis for the identification of heterotic groups under the test environments\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe estimates of the GCA effect of the inbred lines for grain yield are presented in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. Inbreds CML 126, USTEWI-7, TZEEI-15, TZEEI-4, USTEWI-11, TZEEI-21, TZEEI-76 and TZEEI-24 had positive and highly significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) GCA effect for grain yield under low nitrogen condition. Also, inbred lines CML 126, USTEWI-7, TZEEI-15, USTEWI-11, TZEEI-21 and TZEEI-76 exhibited positive and highly significant GCA effects for grain yield under optimum conditions. On the contrary, inbred lines TZEEI-4 and TZEEI-24 showed positive and highly significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) GCA effects for grain yield under stress conditions but had negative and highly significant GCA effects for grain yield under optimum conditions. Inbred lines CML 126, USTEWI-7, TZEEI-15, USTEWI-11, TZEEI-21, TZEEI-76 and TZEEI-24 had positive and significant GCA effects for grain yield across environments. Negative significant GCA effect is desirable for anthesis silking interval, plant and ear height, and plant aspect.\u003c/p\u003e \u003cp\u003eThe results of the dendrogram constructed based on HGCAMT (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) revealed three clusters. Cluster 1consist of CML 126, USTEEWI-2, TZEEI-24, TZEEI-15 and TZEEI-21; cluster 2 includes USTEWI-8, TZEEI-76 and USTEWI-11 while TZEEI-6, TZEEI-36, TZEEI-50, TZEEI-7, TZEEI-4 and USTEEWI-1 constituted cluster 3. Pswarayi and Vivek (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) emphasized three key factors for selecting potential lines as testers for classifying other lines into heterotic groups. The factors include high GCA effect, heterotic group classification, and grain yield. Based on these criteria, CML 126 was the highest-yielding inbred line under low nitrogen conditions and across environments, had a high positive GCA effect for grain yield, and was placed in the first cluster and was, therefore, the best tester for cluster 1. Also, TZEEI-76 recorded the highest positive GCA effect, moderately high grain yield, was classified into the second cluster, and was therefore classified as the best tester for cluster 2. Furthermore, USTEWI-7 recorded the highest positive GCA effect, high grain yield under low nitrogen conditions, was classified into the third cluster, and was, therefore, the best tester for cluster 3.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimates of general combining ability effect of 14 white maize inbred lines for grain yield and other traits under low, optimum, and across nitrogen environments\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParents\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eGY\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eASI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003ePHT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c13\" namest=\"c11\"\u003e \u003cp\u003eEHT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c16\" namest=\"c14\"\u003e \u003cp\u003ePASP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eOPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eAC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eLN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eOPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eAC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eLN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eOPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eAC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCML 126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e858.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e500.0**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e20.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e10.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-0.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-0.2*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSTEEWI-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-523.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-453.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-489.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e4.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-212.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-111.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.5**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-9.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-22.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-16.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-9.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-14.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-12.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.1\u003c/p\u003e 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align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-0.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-0.3**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUSTEEWI-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-820.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1041.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-925.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.0**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-16.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-20.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-17.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-13.3**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-17.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-14.9**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.6**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTZEEI-36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-241.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-275.6**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-253.1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-7.8**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-12.0**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-9.2**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-2.3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-3.4**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-2.5**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e46.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e38.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e30.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e1.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e0.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e0.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e0.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e0.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"16\"\u003eGY\u0026thinsp;=\u0026thinsp;Grain yield; ASI\u0026thinsp;=\u0026thinsp;Anthesis silking interval; PHT\u0026thinsp;=\u0026thinsp;Plant height; EHT\u0026thinsp;=\u0026thinsp;Ear height; PASP\u0026thinsp;=\u0026thinsp;Plant aspect; LN\u0026thinsp;=\u0026thinsp;Low nitrogen; OPT\u0026thinsp;=\u0026thinsp;Optimum nitrogen; AC\u0026thinsp;=\u0026thinsp;Across nitrogen environments; SE\u0026thinsp;=\u0026thinsp;standard error\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eHighly significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) detected among the hybrids and environment for grain yield and other traits under low nitrogen, optimal, and across environments indicated the presence of genetic variation among the hybrids and that the test environments were unique and highly variable (Obeng-Bio et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Hybrid \u0026times; environment interaction observed in this study for most measured traits across the test environments indicates that the hybrids responded differently under each nitrogen environment. This result is consistent with findings reported by Aboderin et al., (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe significant GCA and SCA effects for grain yield and other traits observed across the research conditions indicate that both additive and non-additive gene action was involved in the inheritance of the traits. These results are consistent with the findings reported by Habiba et al., (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The significant mean squares for both Env \u0026times; GCA and Env \u0026times; SCA interaction for all measured traits across environments except anthesis silking interval and ear per plant, and ear aspect and ear rot for Env \u0026times; SCA confirmed that the parental lines expressed diverse performance in hybrid combinations under different environments. These results agree with Makinde et al., (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The significant Env \u0026times; GCA interaction implies a need to select different parental lines for hybrid development under various environments. The significant Env \u0026times; SCA interaction also implied that the single-cross hybrids' response differed under each environment. These findings agree with Ige et al., (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHeritability serves as an important metric in crop genetic enhancement as it quantifies the proportion of phenotypic variance that can be inherited from parents to progenies (Falconer, 1989). Additionally, it offers insights into the most suitable breeding approaches to employ and the potential degree of trait enhancement achievable through selective breeding. This study found moderate to high heritability for grain yield and other traits, meaning the parent plants have a strong genetic ability to pass these traits to their offspring. Abu et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) observed that traits with moderate to high heritability are more influenced by genetic factors than by environmental conditions. Ilyas et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) similarly reported that a high heritability estimate signifies the presence of additive gene action, ensuring the potential for crop improvement through selective breeding.\u003c/p\u003e \u003cp\u003eThe ratio of GCA/SCA was more than unity for most measured traits under stress and optimum nitrogen conditions. This shows that the GCA effect is stronger than the SCA effect for the traits studied, meaning the traits are mainly controlled by additive gene action and can be improved effectively through recurrent selection. Fasahat et al., (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) reported that the preponderance of the GCA effect over SCA makes early-generation testing of genotypes more efficient, and promising hybrids can be identified and selected based on their predictions from the GCA effect. This result is consistent with the findings of several workers (Badu-Apraku et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ifie et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Badu-Apraku et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe mean grain yield reduction of the hybrids was 19.1%. This grain yield reduction is lower than that reported by other Authors. Meseka et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) found a 52% decrease in grain yield in hybrids under low nitrogen conditions. Makumbi et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) reported a 51% reduction in grain yield in hybrids under nitrogen stress. In comparison, the 19.1% reduction observed in this study suggests moderate nitrogen stress. This falls within the 10\u0026ndash;50% range reported by Wolfe \u003cem\u003eet al\u003c/em\u003e. (1988), indicating that the level of nitrogen stress applied was sufficient to identify hybrids tolerant or susceptible to low nitrogen conditions. The 12 most promising hybrids identified out of the best 15 and the 10 worst performing hybrids under low nitrogen conditions using the base index were TZEEI-15 \u0026times; TZEEI-21, TZEEI-6 \u0026times; USTEWI-11, TZEEI-6 \u0026times; USTEWI-76, USTEWI-11 \u0026times; TZEEI-36, USTEWI-7 \u0026times; USTEWI-11, TZEEI-6 \u0026times; TZEEI-24, TZEEI-15 \u0026times; USTEWI-11, TZEEI-21 \u0026times; TZEEI-24, CML 126 \u0026times; TZEEI-36, TZEEI-6 \u0026times; TZEEI-21, TZEEI-21 \u0026times; USTEWI-76, and TZEEI-50 \u0026times; TZEEI-4. The hybrids USTEWI-7 \u0026times; USTEWI-11 and TZEEI-50 \u0026times; TZEEI-4 were the highest yielding and stress-tolerant genotypes suggesting the presence of low nitrogen tolerant alleles in the parental lines. The hybrid check-DZIFOO was identified as the highest-yielding and most stable hybrid under low and optimum nitrogen conditions. This suggests that additional breeding programs are needed to develop crosses that can produce high yields under low nitrogen conditions. Inbred lines with a desirable GCA effect could be effectively used as parents to generate synthetic varieties and could be improved to tolerate stress. The significant positive GCA effect for grain yield detected for inbreds CML 126, USTEWI-7, TZEEI-15, TZEEI-4, USTEWI-11, TZEEI-21, TZEEI-76, TZEEI-24 under low nitrogen condition, CML 126, USTEWI-7, TZEEI-15, USTEWI-11, TZEEI-21, TZEEI-76 under optimum condition, and CML 126, USTEWI-7, TZEEI-15, USTEWI-11, TZEEI-21, TZEEI-76, TZEEI-24 across environment, indicate their usefulness in breeding for higher grain yield under contrasting environment. This also implies that the inbred lines could be good combiners for increasing grain yield by donating desirable alleles when crossed with other genetically variable lines to develop superior hybrids.\u003c/p\u003e \u003cp\u003eThe present study on cluster analysis of the maize inbred lines under low nitrogen conditions aimed at identifying distinct groups among the parental lines. The clustering technique in data analysis from breeding trials is to group inbred lines into several homogeneous groups such that those inbred lines within a group have similar response patterns (Wedwenssen, 2023). The cluster dendrogram constructed for data across the test environments using the HGCAMT method placed the inbred lines into three clusters. Cluster 1 was characterized by high grain yield, cluster 2 was also characterized by a high positive GCA effect for grain yield, while cluster 3 exhibited high grain yield and high positive GCA effect. Inbred lines CML 126, TZEEI-76, and USTEWI-7 were identified as the best testers for clusters 1, 2, and 3 respectively. This indicates that the crossing between superior genetic materials of the above diverse clusters might provide desirable recombinants for developing high-yielding genotypes under low soil nitrogen. This is because cluster analysis separates inbred lines into clusters that portray high homogeneity within a cluster and high heterogeneity between clusters (Hafiz et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, grain yield and all other traits measured were controlled by additive gene action across the research environments. The HGCAMT method revealed three clusters for the inbred lines with CML 126, TZEEI-76, and USTEWI-7 emerging as best testers for clusters 1, 2, and 3 respectively. The hybrids USTEWI-7 \u0026times; USTEWI-11 and TZEEI-50 \u0026times; TZEEI-4 were identified as stress-tolerant genotypes with the highest grain yield. They should be tested on-farm in multiple locations to confirm their stability in performance and recommendation for release and commercialization in sub-Saharan Africa.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI am profoundly grateful to the Department of Crop and Soil Sciences field staff, Kwame Nkrumah University of Science and Technology, Ghana, for their invaluable technical assistance.\u0026nbsp;I extend my heartfelt appreciation to Mr. Dennis Boama Darko, Mr. Clement Gyeabour Kyere, and Ms. Naomi Adoma for their diverse and significant contributions to this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial support\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was partially funded by the Department of Crop and Soil Sciences, Kwame Nkrumah University of Science and Technology, Ghana.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI hereby declare that the study was carried out without any financial or commercial relationship that could result in a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbu P, Badu-Apraku B, Ifie BE, Tongoona P, Melomey LD and Offei SK (2021) Genetic diversity and inter-trait relationship of tropical extra-early maturing quality protein maize inbred lines under low soil nitrogen stress, PLos one, 16(6).\u003c/li\u003e\n \u003cli\u003eAboderin OS, Bankole FA, Oyekunle M, and Olaoye G (2023) Yield stability and inter- traits relationships of maize hybrids under low- and optimum-nitrogen conditions. 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Growing Africa 1(1), 8-11.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Maize, Combining ability, Low soil nitrogen, Genetic diversity","lastPublishedDoi":"10.21203/rs.3.rs-6379832/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6379832/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLow soil nitrogen (N) is among the major constraints causing low grain yield of maize in sub-Saharan Africa. This study was conducted to (i) determine the level of tolerance of the hybrids under low-N, (ii) examine the mode of inheritance of grain yield and other traits of the inbreds, and (iii) assess the genetic diversity of the inbreds. Ninety-one hybrids developed from fourteen inbred lines using diallel mating design together with nine hybrid checks were evaluated under low (30 kg N ha-1) and optimum (90 kg N ha-1) nitrogen conditions at the KNUST Maize Breeding Pipeline in 2024. The results revealed a preponderance of the general combining ability (GCA) effect over specific combining ability (SCA) effects for the traits under low-N, optimum, and across environments, indicating that additive gene action is more important in the inheritance of the traits. The inbreds were classified into three clusters based on the GCA effect of multiple traits of inbreds (HGCAMT). Inbred lines CML 126, TZEEI-76, and USTEWI-7 were identified as the best testers for clusters 1, 2, and 3 respectively. Out of the best 15 and the worst 10 performing hybrids selected based on the base index, USTEWI-7 \u0026times; USTEWI-11 and TZEEI-50 \u0026times; TZEEI-4 were identified as the highest yielding and low nitrogen tolerant hybrids. The tolerant hybrids identified should be extensively evaluated to verify their consistency in performance under low nitrogen conditions. Inbred lines with desirable traits could be utilized to develop low nitrogen tolerant hybrids in maize breeding programs.\u003c/p\u003e","manuscriptTitle":"Genetic Analysis of White Maize (Zea Mays L.) Inbred Lines Under Low Soil Nitrogen","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 12:17:17","doi":"10.21203/rs.3.rs-6379832/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"04f99855-5201-4f77-8c0d-5ae51293f87e","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-08T08:10:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-07 12:17:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6379832","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6379832","identity":"rs-6379832","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}