Artificial neural networks optimize the establishment of a Brazilian germplasm core collection of winter squash (Cucurbita moschata D.).

With widespread cultivation, Cucurbita moschata stands out for the carotenoid content of its fruits such as ß and α-carotene, components with pronounced provitamin A function and antioxidant activity. C. moschata seed oil has a high monounsaturated fatty acid content and vitamin E, constituting a lipid source of high chemical-nutritional quality. The present study evaluates the agronomic and chemical-nutritional aspects of 91 accessions of C. moschata kept at the BGH-UFV and propose the establishment of a core collection based on multivariate approaches and on the implementation of Artificial Neural Networks (ANNs). ANNs was more efficient in identifying similarity patterns and in organizing the distance between the genotypes in the groups. The averages and variances of traits in the CC formed using a 15% sampling of accessions, were closer to those of the complete collection, particularly for accumulated degree days for flowering, the mass of seeds per fruit, and seed and oil productivity. Establishing the 15% CC, based on the broad characterization of this germplasm, will be crucial to optimize the evaluation and use of promising accessions from this collection in C. moschata breeding programs, especially for traits of high chemical-nutritional importance such as the carotenoid content and the fatty acid profile.

Selecting tropical wheat genotypes through combining ability analysis.

The selection of parents to originate promising base populations, as well as the knowledge of the gene effects controlling agronomic traits by means of diallel, are useful to drive genetic gains in Brazilian tropical wheat breeding programs. The goals of this study were to select tropical wheat parents with a high frequency of favorable alleles and segregating populations with high potential to originate superior progenies through partial diallel analysis. Thus, 14 parents were divided in two groups and crossed in a 7 × 7 partial diallel scheme to originate 49 F1 combinations. After obtaining F2 generation, the populations and the parents were evaluated in the field in the summer of 2021. Days for heading, plant height, rust and yellow spot resistance, and grain yield were evaluated. The data were subjected to partial diallel analysis. There were significant effects of general combining ability for all traits. The specific combining ability effect was significant for days for heading and plant height. The additive gene effects were predominant over the non-additive ones. The parents with the highest frequency of favorable alleles for the traits evaluated were selected in each group. Four populations with high genetic potential to originate superior progenies were selected.

Environmental implications of combustion of rice husk at high temperatures and for an extended period for energy generation.

The most common alternative for the management and valorization of rice processing waste is the combustion of rice husk (RH) for energy generation. The environmental risk assessment of the ash generated during the combustion of the RH to obtain energy has remained understudied. Disposal of rice husk ash (RHA) on agricultural land is the most common outcome, which could pose a risk to both natural ecosystems and human health. The objective of this study was to characterize the physicochemical composition and the phytotoxicity, cytotoxicity, and genotoxicity of RHA obtained from three distinct combustion processes. The evaluation processes were 800-900 °C in up to 5 min (I), 800-900 °C in 15-20 min (II), and 600-700 °C in 15-20 min (III). Furthermore, the content, pH, and concentrations of Al, Cd, Cu, Fe, Mg, Mn, Mo, Na, Ni, and Ti present in the ashes were determined. The germination index for two vegetable seeds was subsequently evaluated. By measuring the mitotic index and frequency of chromosomal aberrations, the cytotoxicity and genotoxicity were determined. It was observed that RHA produced by combustion of RH at higher combustion temperatures for an extended period exhibited different physicochemical properties, in addition to higher levels of phytotoxicity, cytotoxicity, and genotoxicity.

Multi-trait selection for mean performance and stability of maize hybrids in mega-environments delineated using envirotyping techniques.

Under global climate changes, understanding climate variables that are most associated with environmental kinships can contribute to improving the success of hybrid selection, mainly in environments with high climate variations. The main goal of this study is to integrate envirotyping techniques and multi-trait selection for mean performance and the stability of maize genotypes growing in the Huanghuaihai plain in China. A panel of 26 maize hybrids growing in 10 locations in two crop seasons was evaluated for 9 traits. Considering 20 years of climate information and 19 environmental covariables, we identified four mega-environments (ME) in the Huanghuaihai plain which grouped locations that share similar long-term weather patterns. All the studied traits were significantly affected by the genotype × mega-environment × year interaction, suggesting that evaluating maize stability using single-year, multi-environment trials may provide misleading recommendations. Counterintuitively, the highest yields were not observed in the locations with higher accumulated rainfall, leading to the hypothesis that lower vapor pressure deficit, minimum temperatures, and high relative humidity are climate variables that -under no water restriction- reduce plant transpiration and consequently the yield. Utilizing the multi-trait mean performance and stability index (MTMPS) prominent hybrids with satisfactory mean performance and stability across cultivation years were identified. G23 and G25 were selected within three out of the four mega-environments, being considered the most stable and widely adapted hybrids from the panel. The G5 showed satisfactory yield and stability across contrasting years in the drier, warmer, and with higher vapor pressure deficit mega-environment, which included locations in the Hubei province. Overall, this study opens the door to a more systematic and dynamic characterization of the environment to better understand the genotype-by-environment interaction in multi-environment trials.

Understanding drought response mechanisms in wheat and multi-trait selection.

Wheat crop is very sensitive to osmotic stress conditions. As an abiotic stress, drought may exert a considerable effect on the levels of specialized metabolites in plants. These metabolites may exert beneficial biological activities in the prevention or treatment of disorders linked to oxidative stress in plants and humans. Furthermore, osmoprotector accumulation helps wheat to increase the maintenance of osmotic balance. Therefore, identifying wheat genotypes with better drought tolerance is extremely important. In this sense, this research aimed to understand agronomic, physiological and biochemical responses of spring wheat strains and cultivars to drought stress, under field conditions, and jointly select strains via multi-trait index. We evaluated agronomic, physiological and biochemical variables in 18 genotypes under field condition. The results demonstrated that all variables were affected by the drought. Most genotypes were significantly reduced in grain yield, except VI_14774, VI_14668, VI_9007 and TBIO_ATON. The variables related to photosynthesis were also affected. An increase above 800% was observed in proline contents in genotypes under drought. Sodium and potassium also increased, mainly for VI_131313 (Na), while VI_130758 and VI_14774 presented increased K. We evaluated the antioxidant potential of the different strains and the total content of phenolic compounds. The most drought-responsive genotypes were BRS_264, VI_14050 and VI_14426. Reduced grain yield and photosynthetic variables, and increased specialized metabolism compounds are due to plant defense mechanisms against drought conditions. Furthermore, variation in genotypes can be explained by the fact that each plant presents a different defense and tolerance mechanism, which may also occur between genotypes of the same species. Four strains were selected by the multivariate index: VI_14055, VI_14001, VI_14426 and VI_1466. Such results allow us to predict which genotype(s) performed best in semi-arid environments and under climatic fluctuations.

MGIDI: toward an effective multivariate selection in biological experiments.

MOTIVATION: Multivariate data are common in biological experiments and using the information on multiple traits is crucial to make better decisions for treatment recommendations or genotype selection. However, identifying genotypes/treatments that combine high performance across many traits has been a challenger task. Classical linear multi-trait selection indexes are available, but the presence of multicollinearity and the arbitrary choosing of weighting coefficients may erode the genetic gains. RESULTS: We propose a novel approach for genotype selection and treatment recommendation based on multiple traits that overcome the fragility of classical linear indexes. Here, we use the distance between the genotypes/treatment with an ideotype defined a priori as a multi-trait genotype-ideotype distance index (MGIDI) to provide a selection process that is unique, easy-to-interpret, free from weighting coefficients and multicollinearity issues. The performance of the MGIDI index is assessed through a Monte Carlo simulation study where the percentage of success in selecting traits with desired gains is compared with classical and modern indexes under different scenarios. Two real plant datasets are used to illustrate the application of the index from breeders and agronomists' points of view. Our experimental results indicate that MGIDI can effectively select superior treatments/genotypes based on multi-trait data, outperforming state-of-the-art methods, and helping practitioners to make better strategic decisions toward an effective multivariate selection in biological experiments. AVAILABILITY AND IMPLEMENTATION: The source code is available in the R package metan (https://github.com/TiagoOlivoto/metan) under the function mgidi(). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Multivariate diallel analysis by factor analysis for establish mega-traits.

In plant breeding, the dialelic models univariate have aided the selection of parents for hybridization. Multivariate analyses allow combining and associating the multiple pieces of information of the genetic relationships between traits. Therefore, multivariate analyses might refine the discrimination and selection of the parents with greater potential to meet the goals of a plant breeding program. Here, we propose a method of multivariate analysis used for stablishing mega-traits (MTs) in diallel trials. The proposed model is applied in the evaluation of a multi-environment complete diallel trial with 90 F1's of simple maize hybrids. From a set of 14 traits, we demonstrated how establishing and interpreting MTs with agronomic implication. The diallel analyzes based on mega-traits present an important evolution in statistical procedures since the selection is based on several traits. We believe that the proposed method fills an important gap of plant breeding. In our example, three MTs were established. The first, formed by plant stature-related traits, the second by tassel size-related traits, and the third by grain yield-related traits. Individual and joint diallel analysis using the established MTs allowed identifying the best hybrid combinations for achieving F1's with lower plant stature, tassel size, and higher grain yield.

Phenotypic variance of black oat growing in crop seasons reveals genetic effects predominance.

This work aimed to determine variance components and genetic parameters, as well as phenotypic, genetic and environmental correlations among black oat (Avena strigosa) families grown in different crop season. Seventy-six black oat families and three controls (BRS Madrugada, BRS Centauro, BRS 139 Neblina) were evaluated in two crop seasons (2016 and 2017), using families with intercalary controls experimental design. The results reveled high potential of black oat families to compose a breeding program, due to families and controls variance were similar, variance components expressed greater genetic variance origin for crop season. Panicle weight and panicle grain weight presented high heritability and, these are correlated with panicle length. Thus, these traits can be used to select superior genotypes. Divergent meteorological conditions between crop seasons expressed few variations among phenotypic, genetic and environmental correlations, and it did not alter magnitude and sense of phenotypic and genetic correlations.

Association of secondary traits with yield in maize F 1 's / Associação de caracteres secundários com o rendimento em F 1 's de milho

ABSTRACT: The objective was to identify phenotypic and genotypic associations, and cause-and-effect relations of secondary components on primary components to establish criteria in the indirect selection process for maize. Partial diallel crosses were conducted in Clevelândia. F1's were evaluated in five environments. For the purpose of increasing the yield of corn grain, breeders should seek to reduce the characters distance from the last node to the first branch of the tassel, tassel length and number of branches. The indirect selection for distance from the last node to the first branch of the tassel would be effective to increase the grain yield. The selection for smaller leaf angle, larger stem diameter and thousand grain weight are favorable for increasing grain yield in maize.

RESUMO: O objetivo deste trabalho foi identificar associações fenotípicas, genotípicas e relações de causa e efeito de componentes secundários sobre componentes primários para se estabelecer critérios nos processos de seleção indireta para milho. Os cruzamentos do dialelo parcial foram conduzidos em Clevelândia. Os F1's foram avaliados em cinco ambientes. Para fins de aumento do rendimento de grãos de milho, os melhoristas devem buscar a redução dos caracteres distância do último nó até primeira ramificação do pendão, comprimento do pendão e número de ramificações. A seleção indireta para menor distância do último nó até a primeira ramificação do pendão seria eficiente para o aumento do rendimento de grãos. A seleção para menor ângulo de folha, maior diâmetro de colmo e massa de mil grãos mostram-se favoráveis para o aumento do rendimento de grãos em milho.

Desfolha em diferentes estádios fenológicos sobre características agronômicas em trigo / Defoliation at different growth stages on agronomic characteristics wheat

O trabalho teve o objetivo de avaliar a interferência da desfolha sobre caracteres de interesse agronômico na cultura do trigo. Foi utilizada a cultivar de trigo Mirante. Os níveis de desfolhamento iniciaram a partir da emissão da terceira folha até a folha bandeira, totalizando seis níveis de desfolha. Foram analisadas as seguintes variáveis: número de afilhos, número de afilhos férteis, altura de inserção de espigas, tamanho de espiga do afilho principal, número de grãos por espiga do afilho principal, massa de grãos por espiga do afilho principal, número de grãos por espiga dos afilhos, massa de grãos por espiga dos afilhos, peso hectolítrico, massa de mil grãos e rendimento. A análise de variância relevou efeitos significativos para interação entre tratamentos e anos de cultivo para as variáveis massa de mil grãos e altura da inserção da espiga. A desfolha na cultura do trigo influenciou negativamente a massa de mil grãos, o número de afilhos férteis, massa de grãos do afilho principal, peso hectolitrico e o rendimento.

The work aimed to evaluate the influence of defoliation on agronomically important traits in wheat. Was used to cultivate wheat Mirante. Defoliation levels started from the issuance of the third leaf to flag leaf, totaling six levels of defoliation. We analyzed the following variables: number of tillers, number of fertile tillers, ear insertion height, size of main tiller spike, number of grains per ear of the main tiller, grain weight per ear of the main tiller, number of grains per spike of ear, grain weight per ear of tillers, test weight, thousand grain weight and yield. The analysis of variance relented significant effects for interaction between treatments and years of cultivation to the variables thousand grain weight and height of the ear insertion. Defoliation in wheat influenced negatively the thousand grain weight, number of fertile tillers, grain weight of main tiller, test weight and yield in the evaluation of both years.