Diseases of soybean caused by Cercospora spp. are endemic throughout the world’s soybean production regions. Species diversity in the genus Cercospora has been underestimated due to overdependence on morphological characteristics, symptoms, and host associations. Currently, only two species (Cercospora kikuchii and C. sojina) are recognized to infect soybean; C. kikuchii causes Cercospora leaf blight (CLB) and purple seed stain (PSS), whereas C. sojina causes frogeye leaf spot. To assess cryptic speciation among pathogens causing CLB and PSS, phylogenetic and phylogeographic analyses were performed with isolates from the top three soybean producing countries (USA, Brazil, and Argentina; collectively accounting for ~80% of global production). Eight nuclear genes and one mitochondrial gene were partially sequenced and analyzed. Additionally, amino acid substitutions conferring fungicide resistance were surveyed, and the production of cercosporin (a polyketide toxin produced by many Cercospora spp.) was assessed. From these analyses, the long-held assumption of C. kikuchii as the single causal agent of CLB and PSS was rejected experimentally. Four cercosporin-producing lineages were uncovered with origins (about 1 Mya) predicted to predate agriculture. Some of the Cercospora spp. newly associated with CLB and PSS appear to represent undescribed species; others were not previously reported to infect soybeans. Lineage 1, which contained the ex-type strain of C. kikuchii, was monophyletic and occurred in Argentina and Brazil. In contrast, lineages 2 and 3 were polyphyletic and contained wide-host range species complexes. Lineage 4 was monophyletic, thrived in Argentina and the USA, and included the generalist Cercospora cf. flagellaris. Interlineage recombination was detected, along with a high frequency of mutations linked to fungicide resistance in lineages 2 and 3. These findings point to cryptic Cercospora species as underappreciated global considerations for soybean production and phytosanitary vigilance, and urge a reassessment of host-specificity as a diagnostic tool for Cercospora.

O objetivo deste trabalho foi detectar e mapear locos de caracteres quantitativos (QTL) que afetam os conteúdos de proteína e óleo em soja (Glycine max L. Merr.). Plantas F2, derivadas do cruzamento entre a linhagem CS3032PTA276 e a variedade UFVS2012, foram cultivadas em casa de vegetação e forneceram as folhas para extração e análise de DNA. Quarenta e oito marcadores microssatélites (SSR) polimórficos foram avaliados na população F2. A avaliação dos fenótipos foi realizada em 207 famílias das progênies F2:3, em um delineamento em blocos ao acaso, com três repetições, conduzido em Viçosa, MG, em 2006. Foram detectados quatro QTL associados ao conteúdo de proteína, nos grupos de ligação D1a, G, A1, e I, e três QTL associados ao conteúdo de óleo, nos grupos A1, I e O. A variação fenotípica explicada pelos QTL variou de 6,24 a 18,94% e 17,26 a 25,93%, respectivamente, para os conteúdos de proteína e óleo. Foram detectados novos QTL associados aos conteúdos de proteína e óleo, além dos previamente relatados em outros estudos. Regiões distintas das atualmente conhecidas podem estar envolvidas no controle genético do teor de proteína e óleo na soja.

The objective of this work was to evaluate the interaction between genotypes and environments for productivity and content of protein and oil, as well as to estimate the genetic parameters and genetic variation among 18 genotypes of soybean grown in four environments. The experiments were set up in the 2006/2007 agricultural year in a randomized block design with three repetitions. The content of protein and oil in the beans was determined by near infrared spectroscopy (NIR). In the four environments the significance was noted for genetic variability and genotype x environment interactions for all traits. Estimates of the heritability of the analyzed variables were high, indicating potential for selecting superior genotypes in breeding programs. In partial correlation analysis only the oil and protein contents were significantly correlated. Correspondence was observed between the UPGMA and Tocher estimation methods, dividing the genotypes into three heterotic groups, with the protein content being the character that most contributed to genetic diversity.

Soybeans contain about 30% carbohydrate, mainly consisting of non-starch polysaccharides (NSP) and oligosaccharides. NSP are not hydrolyzed in the gastrointestinal tract of monogastric animals. These NSP negatively affect the development of these animals, especially the soluble fraction. This work aimed to establish a method to quantify NSP in soybeans, using high performance liquid chromatography (HPLC), and to estimate correlations between NSP, oligosaccharides, protein and oil. Sucrose, raffinose + stachyose, soluble and insoluble NSP contents were determined by HPLC. Oil and protein contents were determined by near-infrared spectroscopy (NIRS). The soluble PNAs content showed no significant correlation with protein, oil, sucrose and raffinose + stachyose contents, but oligosaccharides showed a negative correlation with protein content. These findings open up the possibility of developing cultivars with low soluble NSP content, aiming to develop feed for monogastric animals.

Core Ideas The sporophytic homomorphic self‐incompatibility system advanced the greatest diversity within populations. The phenotypic correlation network facilitates rapid observation of the relationships among groups of variables related to vegetative vigor, incidence of leaf diseases, and physicochemical properties of passion fruit. The correlation networks associated with the relative contribution of the variable can help in the selection of important variables. Sour passion fruit (Passiflora edulis Sims) is a highly suitable crop for small farmers because of its high market value and short time to maturity. However, passion fruit breeding programs need to provide cultivars to producers with quality, disease resistance, and production improvements. The objective of this study was to assess the genetic diversity among and within improved populations of sour passion fruit (SPF) using predicted genetic values, select the most divergent accessions, and evaluate the relationships among groups of traits of vegetative vigor, incidence of leaf diseases, and physicochemical properties of fruits. Twenty‐three genotypes were selected and divided into five populations with variable numbers of accessions. Phenotypic data were transformed into genotypic values using mixed model restricted maximum likelihood‐best linear unbiased prediction. We tested the hypothesis that there is differentiation among populations and between their components and the accessions. Graphic dispersion of the genotypes around the centroids of five populations was performed. The Tocher method was used to group the accessions. The relative importance of the variables and correlation networks was evaluated. Populations showed genetic variability; the hybrid combinations involving the population I accessions 1 (B1 29 PL1), 2 (B1 41 PL3), 4 (B2 9 PL 3), 5 (B2 37 PL3), 10 (G1 B1 9), and 19 (BRS GA1) can be exploited in breeding programs to improve the quality of SPF. The correlation network facilitates the observation of the relationships among groups of traits and helps in the selection of variables when associated with the relative contribution.