ABSTRACT
BACKGROUND: In an environment where the adoption of improved varieties resulting from plant breeding programs is limited, it is essential to identify end-user preferences beforehand. A participatory survey was conducted in eight localities in Korhogo and Bouaké regions (central and northern Cote d'Ivoire respectively) to identify producers' preferences and increase the adoption of improved varieties. The study involved 160 producers and consumers through focus group discussions and individual interviews. RESULTS: Sweetpotato is mostly grown on small plots (<1 ha) of land (89.2%), with women (66%) as the main producers. In the Bouaké region, sweetpotatoes are grown on mounds (100%), whereas in Korhogo they are grown on ridges (86.2%). The main food products or forms of preparation from roots are fries (34.7%), boiled (34.3%), mashed (12.4%), and sweetpotato stew (9.1%). Major constraints, including low price of roots (26.3%), low productivity (16.2%), and post-harvest storage issues (14.5%), were identified as affecting sweetpotato production. CONCLUSIONS: The selection of new varieties should be oriented towards high-yielding varieties with high dry matter content, deployed stems, and roots of round, oblong, or elliptical shape with good culinary characteristics (dry matter, sweet taste, dry texture, absence of fiber). Plants must be drought resistant, be tolerant to poor soil, diseases, and pests, and have a good yield. The color of skin and flesh of the sweetpotato, although constituting criteria of choice, are not essential for the acceptance or the rejection of a variety by users. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
ABSTRACT
BACKGROUND: Roots, tubers and bananas (RTB) play an essential role as staple foods, particularly in Africa. Consumer acceptance for RTB products relies strongly on the functional properties of, which may be affected by the size and shape of its granules. Classically, these are characterized either using manual measurements on microscopic photographs of starch colored with iodine, or using a laser light-scattering granulometer (LLSG). While the former is tedious and only allows the analysis of a small number of granules, the latter only provides limited information on the shape of the starch granule. RESULTS: In this study, an open-source solution was developed allowing the automated measurement of the characteristic parameters of the size and shape of yam starch granules by applying thresholding and object identification on microscopic photographs. A random forest (RF) model was used to predict the starch granule shape class. This analysis pipeline was successfully applied to a yam diversity panel of 47 genotypes, leading to the characterization of more than 205 000 starch granules. Comparison between the classical and automated method shows a very strong correlation (R2 = 0.99) and an absence of bias for granule size. The RF model predicted shape class with an accuracy of 83%. With heritability equal to 0.85, the median projected area of the granules varied from 381 to 1115 µm2 and their observed shapes were ellipsoidal, polyhedral, round and triangular. CONCLUSION: The results obtained in this study show that the proposed open-source pipeline offers an accurate, robust and discriminating solution for medium-throughput phenotyping of yam starch granule size distribution and shape classification. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
ABSTRACT
Dioscorea alata (L.), also referred to as water, winged, or greater yam, is one of the most economically important staple food crops in tropical and subtropical areas. In Côte d'Ivoire, it represents, along with other yam species, the largest food crop and significantly contributes to food security. However, studies focusing on better understanding the structure and extent of genetic diversity among D. alata accessions, using molecular and phenotypic traits, are limited. This study was, therefore, conducted to assess the pattern of genetic variability in a set of 188 D. alata accessions from the National Agronomic Research Centre (CNRA) genebank using 11,722 SNP markers (generated by the Diversity Arrays Technology) and nine agronomic traits. Phylogenetic analyses using hierarchical clustering, admixture, kinship, and Discriminant analysis of principal component (DAPC) all assigned the accessions into four main clusters. Genetic diversity assessment using molecular-based SNP markers showed a high proportion of polymorphic SNPs (87.81%). The analysis of molecular variance (AMOVA) showed low molecular variability within genetic groups. In addition, the agronomic traits evaluated for two years in field conditions showed a high heritability and high variability among D. alata accessions. This study provides insights into the genetic diversity among accessions in the CNRA genebank and opens an avenue for sustainable resource management and the identification of promising parental clones for water yam breeding programs in Côte d'Ivoire.
