Turkey presents a great diversity of common bean landraces in farmers’ fields. We collected 183 common bean accessions from 19 different Turkish geographic regions and 5 scarlet runner bean accessions to investigate their genetic diversity and population structure using phenotypic information (growth habit, and seed weight, flower color, bracteole shape and size, pod shape and leaf shape and color), geographic provenance and 12,557 silicoDArT markers. A total of 24.14% markers were found novel. For the entire population (188 accessions), the expected heterozygosity was 0.078 and overall gene diversity, Fst and Fis were 0.14, 0.55 and 1, respectively. Using marker information, model-based structure, principal coordinate analysis (PCoA) and unweighted pair-group method with arithmetic means (UPGMA) algorithms clustered the 188 accessions into two main populations A (predominant) and B, and 5 unclassified genotypes, representing 3 meaningful heterotic groups for breeding purposes. Phenotypic information clearly distinguished these populations; population A and B, respectively, were bigger (>40g/100 seeds) and smaller (<40g/100 seeds) seed-sized. The unclassified population was pure and only contained climbing genotypes with 100 seed weight 2–3 times greater than populations A and B. Clustering was mainly based on A: seed weight, B: growth habit, C: geographical provinces and D: flower color. Mean kinship was generally low, but population B was more diverse than population A. Overall, a useful level of gene and genotypic diversity was observed in this work and can be used by the scientific community in breeding efforts to develop superior common bean strains.

Sorghum crop is grown under tropical and temperate latitudes for several purposes including production of health promoting food from the kernel and forage and biofuels from aboveground biomass. One of the concerns of policy-makers and sorghum growers is to cost-effectively predict biomass yields early during the cropping season to improve biomass and biofuel management. The objective of this study was to investigate if Sentinel-2 satellite images could be used to predict within-season biomass sorghum yields in the Mediterranean region. Thirteen machine learning algorithms were tested on fortnightly Sentinel-2A and Sentinel-2B estimates of the fraction of Absorbed Photosynthetically Active Radiation (fAPAR) in combination with in situ aboveground biomass yields from demonstrative fields in Italy. A gradient boosting algorithm implementing the xgbtree method was the best predictive model as it was satisfactorily implemented anywhere from May to July. The best prediction time was the month of May followed by May–June and May–July. To the best of our knowledge, this work represents the first time Sentinel-2-derived fAPAR is used in sorghum biomass predictive modeling. The results from this study will help farmers improve their sorghum biomass business operations and policy-makers and extension services improve energy planning and avoid energy-related crises.

Current potato breeding approaches are hampered by several factors including costly seed tubers, tetrasomic inheritance and inbreeding depression. Genomic selection (GS) demonstrated interesting results regardless of the ploidy level, and can be harnessed to circumvent these problems. In this work, three GS models were evaluated using 50,107 informative SilicoDArT markers and 11 traits in two values for cultivation and use (VCU) potato trials. Two key breeding problems modelled included predicting the performance of (i) new and unphenotyped clones (cross‐validation) and (ii) a VCU using another as training set (TS). GS models performed comparably. Cross‐validation accuracy was high for D35, D45, DMW and BVAL, in ascending order. Prediction accuracies of the VCUs were highly correlated, but the best prediction was obtained for the smaller VCU using the bigger as TS. Cross‐validation and VCU prediction accuracies were higher when bigger TSs were used. The findings herein indicate that GS can be attractively integrated in potato breeding, particularly in early clonal generations to predict and select for traits with low heritability which would otherwise require more testing years, environments and resources.

Plant landraces represent a repository of a gene pool, local adaptation of their domestic species, and thereby are considered a great source of genetic variations. Such genetic variation can be helpful to mitigate the current and future food challenges. A total of 183 common bean accessions including three commercial varieties collected from 19 Turkish provinces were grown to record their morpho-agronomic variations and to evaluate the best performing accessions under multi-environmental conditions. Plant height, days to maturity, pods weight, seed length, and 100-seed weight were used to evaluate the best performing accessions under different environmental conditions. A wide range of variations for traits like days to maturity (99-161), plant height (21-168.7 cm), seed length (7.41-16.4 mm), seeds per plant (17.8-254.4), and 100-seeds weight (24.97-73.8 g) were observed and can be useful for breeding purposes. The analytic results derived from the first three eigenvectors suggested that plant height, plant weight, 100-seed weight, and days to flowering were biologically significant bean traits. Seed yield per plant was positively and significantly correlated with plant weight and pods weight. Genotype × environment biplot discriminated the studied common bean accessions based on their plant height and growth habit. Plant height, days to maturity, seed width, and first pod height were found highly heritable traits and were least affected by environmental forces. Among 19 provinces, accessions of Bilecik showed maximum pods per plant, seed yield per plant and 100-seed weight, while Erzincan and Sivas provinces reflected the prevalence of bushy and early maturing accessions. Information provided herein comprehensively explored the occurrence of

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