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Parental selection is perhaps the most critical decision a breeder makes, establishing the foundation of the entire program for years to come. Cross selection based on predicted mean and genetic variance can be further expanded to multiple-trait improvement by predicting the genetic correlation ( r G ) between pairs of traits. Our objective was to empirically assess the ability to predict the family mean, genetic variance, superior progeny mean and genetic correlation through genomic prediction in a soybean population. Data made available through the Soybean Nested Association Mapping project included phenotypic data on seven traits (days to maturity, lodging, oil, plant height, protein, seed size, and seed yield) for 39 families. Training population composition followed a leave-one-family-out cross-validation scheme, with the validation family genetic parameters predicted using the remaining families as the training set. The predictive abilities for family mean and superior progeny mean were significant for all traits while predictive ability of genetic variance was significant for four traits. We were able to validate significant predictive abilities of r G for 18 out of 21 (86%) pairwise trait combinations (P < 0.05). The findings from this study support the use of genome-wide marker effects for predicting r G in soybean biparental crosses. If successfully implemented in breeding programs, this methodology could help to increase the rate of genetic gain for multiple correlated traits., (© 2024. The Author(s).)

Identifying compounds present in the sugarcane epicuticular wax and using these compounds to classify the genotypes susceptible and resistant to the initial attack of sugarcane borer (Diatraea saccharalis) was the aim of this study. A greenhouse experiment was performed in a factorial scheme with and without borer infestation using genotypes previously characterized as resistant or susceptible in field-based experiments. Sugarcane whorls of six-month-old plants were collected before (BI) and after (AI) 72 h of sugarcane borer infestation. The sugarcane epicuticular wax was extracted in both times, i.e., BI and AI and its chemical composition was assessed by gas chromatography coupled to mass spectrometry (GC-MS). Twenty-five compounds were identified for both BI and AI. Classification models were built using partial least squares for discriminant analysis (PLS-DA) and linear discriminant analysis (LDA). Variable selection methods were used to improve the classification models. Ordered predictors selection for discriminant analysis (OPSDA) selected compounds that correctly classified all the test samples before borer infestation (Error = 0.000), and exhibited the most suitable classification parameters for the test set after borer infestation (Error = 0.111). The C30 pentacyclic triterpene friedelin and a high alcohol/aldehyde ratio were associated with the classification of resistant genotypes. Our findings have applicability in developing a screening methodology for breeding programs interested in identifying genotypes resistant to the initial feeding of sugarcane borer., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The aim of this work was to use spectroscopic methods and partial least squares discriminant analysis (PLS-DA) for the early prediction of genotype resistance or susceptibility to sugarcane borer. The sugarcane leaf +1 was directly analyzed with no sample preparation by ultraviolet-visible-near-infrared (UV-VIS-NIR), middle-infrared (MID), and near-infrared (NIR) spectroscopies. Also, laser-induced breakdown spectroscopy (LIBS) was used to analyze pellets of dried and ground leaves and stalks of sugarcane. Classification models were built using PLS-DA. The models built using UV-VIS-NIR, MID or NIR spectra exhibited ideal sensitivity, specificity, and classification errors, i.e., 1 for both sensitivity and specificity and 0 for classification errors. Regarding the models built using LIBS spectra, those using spectra of pellets made from dried and ground leaves also presented ideal sensitivity, specificity, and classification errors; on the other hand, models built using the spectra of pellets made of dried and ground stalks did not present ideal values for these parameters. Thus, the models built, except for the one using LIBS of pellets made of stalks, showed excellent predictive capacity, making them suitable for predicting the resistance or susceptibility of sugarcane genotypes in the early stages of a plant's life., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The sunflower has adaptability to growing regions with different climatic and soil characteristics, showing drought tolerance and high-quality oil production. The State of Rio Grande do Sul is the third largest sunflower producer in Brazil, with research related to the sunflower breeding initiated after the decade of 1950. The aim of this study was to evaluate the genetic progress for grain yield, oil content, and oil yield of sunflower (Helianthus annuus L.) in the State of Rio Grande do Sul. Data of grain yield, oil content, and oil yield obtained from 58 sunflower cultivar yield trials in 19 municipalities in Rio Grande do Sul during the period from 2005 to 2014 were used. Genetic progress was studied according to the methodology proposed by Vencovsky and data from sunflower cultivar yield trials were used. Annual genetic progress of sunflower during the period of 10 years (2005-2014) was 132.46 kg⋅ha -1 ⋅year -1 for grain yield, -0.17%/year for oil content, and 48.11 kg⋅ha -1 ⋅year -1 for oil yield. The sunflower-breeding programs in the State of Rio Grande do Sul were efficient for the traits grain yield and oil yield and presented no efficiency for oil content.

The State of Rio Grande do Sul (RS) stands out as the largest wheat producer in Brazil. Wheat is the most emphasized winter cereal in RS, attracting public and private investments directed to wheat genetic breeding. The study of genetic progress should be performed routinely at breeding programs to study the behavior of cultivars developed for homogeneous regions of cultivation. The objectives of this study were: 1) to evaluate the genetic progress of wheat grain yield in RS; 2) to evaluate the influence of cultivar competition trial stratification in homogeneous regions of cultivation on the study of genetic progress. Grain yield data of 122 wheat cultivars evaluated in 137 trials arranged in randomized block design with three or four replications were used. Field trials were carried out in 23 locations in RS divided into two homogeneous regions during the period from 2002 to 2013. Genetic progress for RS and homogeneous regions was studied utilizing the method proposed by Vencovsky. Annual genetic progress for wheat grain yield during the period of 12 years in the State of RS was 2.86%, oscillating between homogeneous regions of cultivation. The difference of annual genetic progress in region 1 (1.82%) in relation to region 2 (4.38%) justifies the study of genetic progress by homogeneous regions of cultivation.

The State of Rio Grande do Sul (RS) is the largest producer of oat in Brazil with the aid of consolidated breeding programs, which are constantly releasing new cultivars. The main objectives of this study were to: 1) evaluate the annual genetic progress in grain yield and hectoliter weight of the oat cultivars in RS, with and without fungicide use on aerial parts of plants; and 2) evaluate the efficiency of oat breeding programs in introducing disease-resistant genes in the released cultivars through network yield trials conducted with and without fungicide use on aerial plant parts. The data on grain yield and hectoliter weight were obtained from 89 competition field trials of oat cultivars carried out from 2007 to 2014 in nine municipalities of RS. Of the total 89 trials, 44 were carried out with fungicide application on aerial plant parts and 45 were carried out without fungicide application. The annual genetic progress in oat cultivars was studied using the methodology proposed by Vencovsky (1988). The annual genetic progress in oat grain yield was 1.02% with fungicide use and 4.02% without fungicide use during the eight-year study period in RS. The annual genetic progress with respect to the hectoliter weight was 0.08% for trials with fungicide use and 0.71% for trials without fungicide use. Performing network yield trials with and without fungicide use on the aerial plants parts is a feasible method to evaluate the efficiency of oat breeding programs in introducing disease-resistant genes in the released cultivars.

Tassel traits are important in maize breeding programs aiming to reduce the size and number of branches and maintain satisfactory pollen production in order to increase grain yield. The objectives of this study were to determine the sample size (number of tassels) required to estimate the mean values for tassel traits in maize genotypes and to verify the variability of sample size among genotypes. Twenty maize genotypes were evaluated in an experiment carried out in a randomized block design with three replicates. Twenty tassels were randomly collected in each plot, for a total of 1200 tassels. In each tassel, the following traits were measured: peduncle dry matter, branching space dry matter, central spike dry matter, tassel dry matter, peduncle length, branching space length, central spike length, tassel length, tassel dry matter to tassel length ratio, number of primary branches, number of secondary branches, and tassel branch number. Measures of central tendency and variability were calculated, analysis of variance and mean comparison tests were performed, normality was verified, and the sample size was determined. In order to estimate the means with the same precision, the sample size for weight traits was greater than that for length traits. For tassel traits, 11, 20, and 43 tassels are sufficient to estimate the mean with a precision of 40, 30, and 20%, respectively, of the estimated mean at a 95% confidence level. These data show that there is sample size variability among maize genotypes.