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High-throughput phenotyping (HTP) using vegetation indices (VIs) is an important data source for managing plant breeding programs and can be a promising tool in indirect selection. This study hypothesized that VIs are correlated with agronomic traits in corn, and therefore, HTP can be an auxiliary tool for selecting superior genotypes. The objectives were: i) to analyze the association between agronomic traits and VIs, and ii) to identify superior corn hybrids for the evaluated traits using multivariate techniques. Ten corn hybrids (AGRI 330, AGRI 340, FS575PWU, KTZ006VP3, MG545AW, MG580PW, MG711PW, MZ1780, MZ1952, and TROPI 102) were evaluated for plant height (PH), stem diameter (SD), and grain yield (GY). The VIs studied were NDVI, NDRE, EVI, GNDVI, SAVI, and MSAVI. Pearson’s correlation network was constructed to analyze the relationship between the variables, and a canonical analysis was performed to verify the inter-relationship between the variables and hybrids. The VIs evaluated are strongly positively correlated with each other and with PH. The most productive hybrids are MG545AW, FS575PWU and KTZ006VP3. Hybrid MZ1952 has higher correlations with VIs and PH. The findings reveal that VIs can be excellent auxiliary variables for selecting agronomically superior genotypes, being a promising alternative to increase corn breeding efficiency. [ABSTRACT FROM AUTHOR]

Grain yield is a constant concern in soybean breeding programs for being highly influenced by the environment. This trait can be significantly affected by the sowing times. Thus, for the correct cultivar recommendation, methods of stability and adaptability analysis are used to verify the genotype x environment interaction at different sowing times. In this study, ten soybean cultivars were evaluated in 2016/2017 and 2017/2018 seasons, at different sowing times. Each experiment was carried out in a randomized block design with three replications. The methods of Eberhart & Russel and Lin & Binns were used for cultivars recommendation for general, favorable, and unfavorable environments. Cultivars CS2728, BONUS, and BRS1074 show high yield and predictability and therefore are the most suitable for the region of Chapadão do Sul. [ABSTRACT FROM AUTHOR]

The current challenge of corn (Zea mays L.) crops is to reach high yield to supply the world's demand for food, especially under different fertilization regimes and using the latest technology. We hypothesized that wavelengths and vegetation indices have a linear relationship with agronomic variables in corn. Our objectives were to verify the formation of super-traits and to study the association between wavelengths and vegetation indices with agronomic traits in corn cultivated under high and low topdressing N. The experiments were carried out in two crop seasons using a randomized block design with three replicates in a factorial scheme (11 genotypes x 2 contrasting levels of N: low, 60 kg ha-1 and high, 180 kg ha-1). At full bloom, the spectral variables green (550 nm), red (660 nm), red-edge (735 nm), and near-infrared (790 nm) and the vegetation indices normalized difference vegetation index (NDVI), normalized difference red-edge index (NDRE), green normalized difference vegetation index (GNDVI), and soil-adjusted vegetation index (SAVI) were evaluated. Agronomic traits evaluated were leaf N, plant height, first pod height, stem diameter, cob length, rows per cob, grains per row, and grain yield. Results showed that SAVI, GNDVI, NDVI, and NDRE and red-edge and red were associated with agronomic traits in corn. The association between the agronomic traits evaluated here can be used to estimate the leaf N content and corn yield. [ABSTRACT FROM AUTHOR]

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Extraction of inbred lines is a very important step in maize breeding since these lines will be used to obtain hybrids intended for the market. However, this expensive process, hinders genotype evaluation in contrasting environments, especially regarding nitrogen (N) content. This study aimed to evaluate the potential of maize populations for line extraction and select partially inbred lines under different soil nitrogen (N) availability. Five populations were evaluated regarding their potential for line extraction. Fifty-five S1 partially inbred lines were extracted from these populations. The top-cross method was used to evaluate lines by crossing them with two testers. Hybrids evaluation used 110 top-cross hybrids, five base populations, and six checks. Two trials were carried out in Dourados and Caarapó. One trial had adequate fertilization (high N) while the other was under stress condition (low N). Hybrid DKB 789 showed potential for extraction of partially inbred lines, aiming at selecting N use efficiency. Base population BP (07) was the most suitable for the extraction of partially inbred lines aiming at N use efficiency. Partially inbred lines BP (07) 13, BP (07) 14, and BP (07) 17 are the most suitable for the extraction of top-cross hybrids with high grain yield, efficiency, and responsiveness to N. [ABSTRACT FROM AUTHOR]

Multiple-trait best linear unbiased prediction (BLUP) is generally the most appropriate method to predict genetic values because it considers the genetic and residual correlations among traits and leads to higher selective accuracy. Thus, the aim of the present study was to analyze the interrelationships among traits related to cotton fiber length through path analysis under multiple-trait BLUP. To that end, 36 elite lines were evaluated in three environments and phenotyped for fiber quality and agronomic traits. Variance components were estimated via residual maximum likelihood (REML). The genetic correlation coefficients among traits were obtained through the mixed model output, and a correlation network was constructed to graphically express these results. Subsequently, path analysis was performed considering fiber length as the main dependent variable. Genetic parameters indicate that the phenotypic variance for most traits is mainly composed of residual effects, which reinforces the need for more accurate statistical methods, such as multiple-trait BLUP. The results for genetic correlations and path analysis reveal the difficulty of selection based on important fiber quality traits, especially fiber length, since most traits show a low cause-and-effect relationship, while other important traits have an undesirable cause-and effect relationship. Path analysis under multiple-trait BLUP proved to be suitable and useful for studying interrelationships among traits related to cotton fiber length. [ABSTRACT FROM AUTHOR]

The objective of this study was to identify cowpea genotypes that fulfill the criteria of high grain yield, adaptability, and stability in the Mato Grosso do Sul (MS) region. Yield data from Value for Cultivation and Use (VCU) trials conducted in the municipalities of Dourados and Aquidauana/MS from March to August 2017 and 2018 were used, totaling four environments. A randomized block design with 14 treatments and four repetitions was adopted. Yield was evaluated by weighing the grains from the usable plot and converting the values to kilogram per hectare. After the analysis of variance, the interaction between genotypes and environments was evaluated by the methodologies of adaptability-stability analysis of Eberhart and Russell, Lin and Binns modified by Carneiro and GGE-Biplot. The genotypes Pingo-de-ouro 1-5-7, Pingo-de-ouro 1-5-5 and Bico-de-ouro 1-5-24 are stable, adaptable and productive for the state according to the complementary use of the methods. [ABSTRACT FROM AUTHOR]

In multi-environment trials (MET), large networks are assessed for results improvement. However, genotype by environment interaction plays an important role in the selection of the most adaptable and stable genotypes in MET framework. In this study, we tested different residual variances and measure the selection gain of cotton genotypes accounting for adaptability and stability, simultaneously. Twelve genotypes of cotton were bred in 10 environments, and fiber length (FL), fiber strength (FS), micronaire (MIC), and fiber yield (FY) were determined. Model selection for different residual variance structures (homogeneous and heterogeneous) was tested using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The variance components were estimated through restricted maximum likelihood and genotypic values were predicted through best linear unbiased prediction. The harmonic mean of relative performance of genetic values (HMRPGV) were applied for simultaneous selection for adaptability, stability, and yield. According to BIC heterogeneous residual variance was the best model fit for FY, whereas homogeneous residual variance was the best model fit for FL, FS, and MIC traits. The selective accuracy was high, indicating reliability of the prediction. The HMRPGV was capable to select for stability, adaptability and yield simultaneously, with remarkable selection gain for each trait. [ABSTRACT FROM AUTHOR]

Soybean is the most economically important oilseed in the world, being one of the main sources of oil and protein in human and animal food. The objective of this work was to select F3 segregating populations for agronomic and physiological traits and vegetation indices (VIs). The experiment was carried out in the 2018/2019 crop seasons in a randomized block design with three replicates and 10 F3 populations (P1, P2, P3, P4, P5, P6, P7, P8, P9, and P10). The evaluated traits were as fallows: number of days to maturity (NDM); number of pods per plant (NPP); number of nodes per plant (NNP); number of lateral stems per plant (NSP); grain yield (GY); photosynthesis (A); stomatal conductance (gs); internal CO2 concentration (Ci); transpiration (E); NIR, Red-edge, Red and Green wavelengths; and NDVI and NDRE vegetation indices. Regarding the physiological traits evaluated in soybean F3 populations, the P8 and P6 populations presented the highest averages for photosynthesis, while the P3, P10, and P9 populations presented the highest Ci, E, and gs. For VIs evaluated in soybean F3 populations, the populations P7, P2, and P1 presented higher averages for NIR and Red-edge wavelengths. P5 and P4 showed a higher NDRE, and P8 showed a higher red wavelength. For agronomic traits, population P2 showed better results for the traits NNP and NSP. Populations P1 and P3 had a higher NDM. The P7 population presented the highest NPP, and the P6 population presented the highest GY. [ABSTRACT FROM AUTHOR]

This study aimed to identify promising crosses to generate cowpea breeding populations for the Brazilian Cerrado region. The experiment was carried out during the two crop seasons. The experimental design used was a randomized block with four replications and 20 genotypes prostrate. The effect of genotypes was significant for all traits evaluated. The Mahalanobis distance and the Tocher's cluster were used to estimate the genetic diversity. Singh's criterion was used to quantify the contribution of each trait to genetic diversity. Mass of hundred grains and grain yield were the traits that most contributed to detect diversity among cowpea genotypes. The crosses between the G14 genotype with G2, G3, G4, G5, G6, G11, G16, and G20 are promising for the development of populations with variability and high genetic potential. [ABSTRACT FROM AUTHOR]