RESUMO
The strong societal demand to reduce pesticide use and adaptation to climate change challenges the capacities of phenotyping new varieties in the vineyard. High-throughput phenotyping is a way to obtain meaningful and reliable information on hundreds of genotypes in a limited period. We evaluated traits related to growth in 209 genotypes from an interspecific grapevine biparental cross, between IJ119, a local genitor, and Divona, both in summer and in winter, using several methods: fresh pruning wood weight, exposed leaf area calculated from digital images, leaf chlorophyll concentration, and LiDAR-derived apparent volumes. Using high-density genetic information obtained by the genotyping by sequencing technology (GBS), we detected 6 regions of the grapevine genome [quantitative trait loci (QTL)] associated with the variations of the traits in the progeny. The detection of statistically significant QTLs, as well as correlations (R2) with traditional methods above 0.46, shows that LiDAR technology is effective in characterizing the growth features of the grapevine. Heritabilities calculated with LiDAR-derived total canopy and pruning wood volumes were high, above 0.66, and stable between growing seasons. These variables provided genetic models explaining up to 47% of the phenotypic variance, which were better than models obtained with the exposed leaf area estimated from images and the destructive pruning weight measurements. Our results highlight the relevance of LiDAR-derived traits for characterizing genetically induced differences in grapevine growth and open new perspectives for high-throughput phenotyping of grapevines in the vineyard.
RESUMO
A plethora of biotechnological methodologies is used to authenticate quality olive oils. Among the DNA-based approaches, SNPs and SSRs combined with high resolution melting (HRM) provide certain advantages such as speed, simplicity and reliability. SNP-HRM and SSR-HRM were used for the authentication of monovarietal olive oils as well as the quantification of varietal composition in olive oil DNA admixtures and olive oil blends of two different cultivars. The SSR-HRM was more efficient in distinguishing monovarietal olive oils while the SNP-HRM assay was more reliable in discriminating olive oil blends. HRM was also used for the detection of adulteration of olive oil with oils of different plant origin by using plastid trnL indels and SNPs. The trnL-indels-HRM showed higher discrimination power than the trnL-SNP-HRM in determining adulteration in olive oil. These results indicate that traceability of adulteration might be more reliable than authentication of the varietal origin in olive oil blends.
