Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields.

Crop yield monitoring demonstrated the potential to improve agricultural productivity through improved crop breeding, farm management and commodity planning. Remote and proximal sensing offer the possibility to cut crop monitoring costs traditionally associated with surveys and censuses. Fraction of absorbed photosynthetically active radiation (fAPAR), chlorophyll concentration (CI) and normalized difference vegetation (NDVI) indices were used in crop monitoring, but their comparative performances in sorghum monitoring is lacking. This work aimed therefore at closing this gap by evaluating the performance of machine learning modelling of in-season sorghum biomass yields based on Sentinel-2-derived fAPAR and simpler high-throughput optical handheld meters-derived NDVI and CI calculated from sorghum plants reflectance. Bayesian ridge regression showed good cross-validated performance, and high reliability (R2 = 35%) and low bias (mean absolute prediction error, MAPE = 0.4%) during the validation step. Hand-held optical meter-derived CI and Sentinel-2-derived fAPAR showed comparable effects on machine learning performance, but CI outperformed NDVI and was therefore considered as a good alternative to Sentinel-2's fAPAR. The best times to sample the vegetation indices were the months of June (second half) and July. The results obtained in this work will serve several purposes including improvements in plant breeding, farming management and sorghum biomass yield forecasting at extension services and policy making levels

Genome-wide association mapping of total antioxidant capacity, phenols, tannins, and flavonoids in a panel of Sorghum bicolor and S. bicolor × S. halepense populations using multi-locus models.

Sorghum is widely used for producing food, feed, and biofuel, and it is increasingly grown to produce grains rich in health-promoting antioxidants. The conventional use of grain color as a proxy to indirectly select against or for antioxidants polyphenols in sorghum grain was hampered by the lack of consistency between grain color and the expected antioxidants concentration. Marker-assisted selection built upon significant loci identified through linkage disequilibrium studies showed interesting potential in several plant breeding and animal husbandry programs, and can be used in sorghum breeding for consumer-tailored antioxidant production. The purpose of this work was therefore to conduct genome-wide association study of sorghum grain antioxidants using single nucleotide polymorphisms in a novel diversity panel of Sorghum bicolor landraces and S. bicolor × S. halepense recombinant inbred lines. The recombinant inbred lines outperformed landraces for antioxidant production and contributed novel polymorphism. Antioxidant traits were highly correlated and showed very high broad-sense heritability. The genome-wide association analysis uncovered 96 associations 55 of which were major quantitative trait loci (QTLs) explaining 15 to 31% of the observed antioxidants variability. Eight major QTLs localized in novel chromosomal regions. Twenty-four pleiotropic major effect markers and two novel functional markers (Chr9_1550093, Chr10_50169631) were discovered. A novel pleiotropic major effect marker (Chr1_61095994) explained the highest proportion (R2 = 27-31%) of the variance observed in most traits evaluated in this work, and was in linkage disequilibrium with a hotspot of 19 putative glutathione S-transferase genes conjugating anthocyanins into vacuoles. On chromosome four, a hotspot region was observed involving major effect markers linked with putative MYB-bHLH-WD40 complex genes involved in the biosynthesis of the polyphenol class of flavonoids. The findings in this work are expected to help the scientific community particularly involved in marker assisted breeding for the development of sorghum cultivars with consumer-tailored antioxidants concentration

Diversity of Macro- and Micronutrients in the Seeds of Lentil Landraces

Increasing the amount of bioavailable mineral elements in plant foods would help to improve the nutritional status of populations in developing countries. Legume seeds have the potential to provide many essential nutrients. It is important to have information on genetic variations among different lentil populations so that plant breeding programs can use new varieties in cross-breeding programs. The main objective of this study was to characterize the micro- and macronutrient concentrations of lentil landraces seeds collected from South-Eastern Turkey. We found impressive variation in the micro- and macroelement concentrations in 39 lentil landraces and 7 cultivars. We investigated the relationships of traits by correlation analysis and principal component analysis (PCA). The concentrations of several minerals, particularly Zn, were positively correlated with other minerals, suggesting that similar pathways or transporters control the uptake and transport of these minerals. Some genotypes had high mineral and protein content and potential to improve the nutritional value of cultivated lentil. Cross-breeding of numerous lentil landraces from Turkey with currently cultivated varieties could improve the levels of micro- and macronutrients of lentil and may contribute to the worldwide lentil quality breeding program

In-silico Exploration of Channel Type and Efflux Silicon Transporters and Silicification Proteins in 80 Sequenced Viridiplantae Genomes

Silicon (Si) accumulation protects plants from biotic and abiotic stresses. It is transported and distributed within the plant body through a cooperative system of channel type (e.g., OsLsi1) and efflux (Lsi2s e.g., OsLsi2) Si transporters (SITs) that belong to Noduline-26 like intrinsic protein family of aquaporins and an uncharacterized anion transporter family, respectively. Si is deposited in plant tissues as phytoliths and the process is known as biosilicification but the knowledge about the proteins involved in this process is limited. In the present study, we explored channel type SITs and Lsi2s, and siliplant1 protein (Slp1) in 80 green plant species. We found 80 channel type SITs and 133 Lsi2s. The channel type SITs characterized by the presence of two NPA motifs, GSGR or STAR selectivity filter, and 108 amino acids between two NPA motifs were absent from Chlorophytes, while Streptophytes evolved two different types of channel type SITs with different selectivity filters. Both channel type SITs and Lsi2s evolved two types of gene structures each, however, Lsi2s are ancient and were also found in Chlorophyta. Homologs of Slp1 (225) were present in almost all Streptophytes regardless of their Si accumulation capacity. In Si accumulator plant species, the Slp1s were characterized by the presence of H, D-rich domain, P, K, E-rich domain, and P, T, Y-rich domain, while moderate Si accumulators lacked H, D-rich domain and P, T, Y-rich domains. The digital expression analysis and coexpression networks highlighted the role of channel type and Lsi2s, and how Slp1 homologs were ameliorating plants’ ability to withstand different stresses by co-expressing with genes related to structural integrity and signaling. Together, the in-silico exploration made in this study increases our knowledge of the process of biosilicification in plants

The grain <i>Hardness</i> locus characterized in a diverse wheat panel (<i>Triticum aestivum L</i>.) adapted to the central part of the Fertile Crescent:genetic diversity, haplotype structure, and phylogeny

PubMedID: 26898967Wheat belongs to the most important crops domesticated in the Fertile Crescent. In this region, fortunately, locally adapted wheat landraces are still present in farmers’ fields. This material might be of immense value for future breeding programs. However, especially wheat germplasm adapted to the central part of the Fertile Crescent has been poorly characterized for allelic variation at key loci of agricultural importance. Grain hardness is an important trait influencing milling and baking quality of wheat. This trait is mainly determined by three tightly linked genes, namely, Puroindoline a (Pina), Puroindoline b (Pinb), and Grain softness protein-1 (Gsp-1), at the Hardness (Ha-D) locus on chromosome 5DS. To investigate genetic diversity and haplotype structure, we resequenced 96 diverse wheat lines at Pina-D1, Pinb-D1, Gsp-A1, Gsp-B1, and Gsp-D1. Three types of null alleles were identified using diagnostic primers: the first type was a multiple deletion of Pina-D1, Pinb-D1, and Gsp-D1 (Pina-D1k), the second was a Pina-D1 deletion (Pina-D1b); and the third type was a deletion of Gsp-D1, representing a novel null allele designated here as Gsp-D1k. Sequence analysis resulted in four allelic variants at Pinb-D1 and five at Gsp-A1, among them Gsp-A1-V was novel. Pina-D1, Gsp-B1 and Gsp-D1 sequences were monomorphic. Haplotype and phylogenetic analysis suggested that (1) bread wheat inherited its 5DS telomeric region probably from wild diploid Ae. tauschii subsp. tauschii found within an area from Transcaucasia to Caspian Iran; and that (2) the Ha-A and Ha-B homoeoloci were most closely related to sequences of wild tetraploid T. dicoccoides. This study provides a good overview of available genetic diversity at Pina-D1, Pinb-D1, and Gsp-1, which can be exploited to extend the range of grain texture traits in wheat. © 2016, Springer-Verlag Berlin Heidelberg