Dual purpose wheat could be a good alternative for helping overcome the need to import this cereal in Brazil. To achieve this, development of cultivars with high yield is necessary. The contribution of genetics in defining traits is very important for directing breeding programs for the development of cultivars that provide the desired agronomic ideotype. We estimated heritability for 36 characters of agronomic importance in dual-purpose wheat. The inheritable genetic patterns were examined using linear trends, a Euclidean algorithm, factor analysis and artificial neural networks. The study was carried out during the crop seasons of 2011, 2012 and 2013. The experimental design was randomized block, arranged in a factorial scheme with three growing seasons (2011, 2012 and 2013) and five dual-purpose wheat genotypes (BRS Tarumã, BRS Umbu, BRS Figueira, BRS Guatambu and BRS 277) x three cuttings (first cutting, second cutting and third cutting), with three replicates. Deviance analysis or maximum likelihood was significant for the 36 characters. The length of the head of the main plant, plant height ©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 18 (3): gmr18266 I.R. Carvalho et al. 2 before the first second cutting and dry mass of the seedlings showed high variability. The 36 characters expressed linear genetic dependence based on the Euclidean Algorithm; similar to what was found with the Tocher Optimized Clustering and Artificial Neural Networks K-means methods. Similar genetic trends for heritability profiles were obtained with factor analysis and Artificial Neural Networks by the Kohonem method. The use of Artificial Neural Networks through the Kohonem method gave the greatest efficacy in the definition of the genetic profiles needed to develop the recommended agronomic ideotype for the improvement of dualpurpose wheat.

The hydric resources are primordial for plants growth and development, under conditions where the growing environment express hydric shortage. These conditions can directly or indirectly affect development, the formation of new organs, yield and quality seeds. The study aimed to evaluate the physiological quality of rice and soybean seeds, produced under hydric restriction. Experiment 1: for rice, the scheme was completely randomized with four repetitions, the treats of hydric restrictions were applied in the periods of 0, 24, 48, 72 hours at the phenological stage of filling seeds. Experiment 2: for soybean, the scheme was completely randomized, conducted in factorial scheme, four replicates with four hydric restriction periods of 0, 24, 48 and 72 hours, at the phenological stage of filling seeds. It was verified that as the hydric restriction hours increase, at the rice seeds filling, the physiologic quality is affected, the higher effect occurred at 72 hours of restriction. While at the soybean seeds production it was not verified such effects, only the thousand seeds mass was negatively affected. The physiological quality of rice seeds were more affected, when compared to soybean seeds submitted to the same treats of hydric stress.

The sensitivity of infiltration predictions by Hydrus‐1D and Green‐Ampt models to rainfall discretisation was investigated by assessing the accuracy of infiltration predictions with rainfall rate profiles at step sizes D between 2 and 1440 min. Five peak rainfall profiles and one sine‐wave rainfall profile, all with a cumulative rainfall amount of 28.8 cm and a duration of 24 h were used. Discrete rainfall profiles were generated based on the peak rainfall profiles for several step sizes. The rainfall profiles were evaluated in a sandy loam with a high saturated hydraulic conductivity and a silt loam with a low saturated hydraulic conductivity for two initial pressure heads. For both models, insensitivity was found below a critical step size Dcrit, whereas high sensitivity was observed above it, Dcrit depending on soil hydraulic conductivity and rainfall peak intensity, regardless of initial pressure head. In the sandy loam, Dcrit was 20–30 (high‐intensity peak) and 70 min (low‐intensity peak); in the silt loam, values were 100 and 200–300 min, respectively. Therefore, rainfall data from common weather station data at D = 60 min allow accurate estimates of infiltration only in low‐conductivity soils or for low‐intensity rainfall. The disaggregation of daily cumulative rainfall into sine‐wave profiles improved predictions in more conductive soils. Results indicate that higher saturated hydraulic conductivity and intensity peak rainfall rate require smaller values of D for the accurate modelling of infiltration with Hydrus‐1D and Green‐Ampt models. Highlights Temporal resolution of rainfall data is important in infiltration modelling. Temporal resolution of rainfall data affects Green‐Ampt and Hydrus‐1D predicted infiltration Green‐Ampt and Hydrus‐1D cumulative infiltration predictions are insensitive for rainfall resolution ≤20 min Predictions are more sensitive to rainfall resolution >20 min in soils with higher hydraulic conductivity.

The objective of this work was to apply the phenotypic multicarter selection and predictive genetic for the attributes of the yield of common black bean seeds in the segregating generations F2, F3 and F4.The experimental design was augmented blocks, where the BRS Esplendor (BE), BRS Supremo (BS) and IPR Tiziu (IT) genotypes were used as controls arranged in four replicates, the other treatments were organized in a unique way in the experiment, the F2 segregating generation being represented by 36 common black bean populations, F3 segregating generation composed of 72 families and the F4 segregating generation formed by 44 families. The multicarter phenotypic index provided the simultaneous selection for the number and mass of seeds per plant, independent of the segregating generation of common black bean.Multicarter genetic variation is superior for the F3 segregating generation, with pronounced environmental effects on the F4 generation.The F4 segregating families express superiority to the genetic gain and magnitude of superior genotypes in relation to the commercial controls, where high genetic increase is exposed between the F3 to F4selection.The use of the phenotypic index expresses applicability to the selection of common black bean genotypes to increase seed yield.

The aim of study is to estimate the variance components and genetic parameters (REML), as well as to predict the genetic value (BLUP) of F3 families of common black beans for the components of seed production. The experimental design was augmented blocks, where the 83 F3 families were arranged only in each block, and the commercial controls were organized in three replicates. The additive genetic effects were determinant for plant height and first pod insertion height. The pronounced effects of the environment are expressed for the number of pods, seeds and seed mass per plant. Potentiality in the selection of higher F3 families are revealed through the 2CBRS population for plant height and first pod insertion height, for the components of seed yield the selections should be directed to the populations 2CARS and 1FVRS. The number of seeds and seed mass per plant were potentiated in more than 28% of the selected F3 families, and pronounceable genetic gains are obtained by the selection of families 66, 65 and 67. The inferences obtained in this study present theoretical and practical foundation, and can be applied in future studies of breeding and production of common black bean seeds.

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oil were determined in intact soybeans by the technique of reflectance in the near infrared. There was genetic dissimilarity among the 54 soybean genotypes. The protein character was the most decisive factor for genetic variability, based on Singh's relative contribution. Using patterns such as standardized Euclidean mean distance, Tocher's optimized method and the UPGMA clustering method, it was possible to show patterns in the genotype clusters. Based on these results, we can define crosses between accessions with genetic potential for the formation of genotypes with superior centesimal characteristics.