Whole-genome sequencing and comparative genomics reveal candidate genes associated with quality traits in Dioscorea alata.

BACKGROUND: Quality traits are essential determinants of consumer preferences. Dioscorea alata (Greater Yam), is a starchy tuber crop in tropical regions. However, a comprehensive understanding of the genetic basis underlying yam tuber quality remains elusive. To address this knowledge gap, we employed population genomics and candidate gene association approaches to unravel the genetic factors influencing the quality attributes of boiled yam. METHODS AND RESULTS: Comparative genomics analysis of 45 plant species revealed numerous novel genes absent in the existing D. alata gene annotation. This approach, adding 48% more genes, significantly enhanced the functional annotation of three crucial metabolic pathways associated with boiled yam quality traits: pentose and glucuronate interconversions, starch and sucrose metabolism, and flavonoid biosynthesis. In addition, the whole-genome sequencing of 127 genotypes identified 27 genes under selection and 22 genes linked to texture, starch content, and color through a candidate gene association analysis. Notably, five genes involved in starch content and cell wall composition, including 1,3-beta Glucan synthase, ß-amylase, and Pectin methyl esterase, were common to both approaches and their expression levels were assessed by transcriptomic data. CONCLUSIONS: The analysis of the whole-genome of 127 genotypes of D. alata and the study of three specific pathways allowed the identification of important genes for tuber quality. Our findings provide insights into the genetic basis of yam quality traits and will help the enhancement of yam tuber quality through breeding programs.

Starch granule size and shape characterization of yam (Dioscorea alata L.) flour using automated image analysis.

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.

Convolutional neural network allows amylose content prediction in yam (Dioscorea alata L.) flour using near infrared spectroscopy.

BACKGROUND: Yam (Dioscorea alata L.) is the staple food of many populations in the intertropical zone, where it is grown. The lack of phenotyping methods for tuber quality has hindered the adoption of new genotypes from breeding programs. Recently, near-infrared spectroscopy (NIRS) has been used as a reliable tool to characterize the chemical composition of the yam tuber. However, it failed to predict the amylose content, although this trait is strongly involved in the quality of the product. RESULTS: This study used NIRS to predict the amylose content from 186 yam flour samples. Two calibration methods were developed and validated on an independent dataset: partial least squares (PLS) and convolutional neural networks (CNN). To evaluate final model performances, the coefficient of determination (R2 ), the root mean square error (RMSE), and the ratio of performance to deviation (RPD) were calculated using predictions on an independent validation dataset. The tested models showed contrasting performances (i.e., R2 of 0.72 and 0.89, RMSE of 1.33 and 0.81, RPD of 2.13 and 3.49 respectively, for the PLS and the CNN model). CONCLUSION: According to the quality standard for NIRS model prediction used in food science, the PLS method proved unsuccessful (RPD < 3 and R2 < 0.8) for predicting amylose content from yam flour but the CNN model proved to be reliable and efficient method. With the application of deep learning methods, this study established the proof of concept that amylose content, a key driver of yam textural quality and acceptance, can be predicted accurately using NIRS as a high throughput phenotyping method. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Genome-wide association studies reveal novel loci controlling tuber flesh color and oxidative browning in Dioscorea alata.

BACKGROUND: Consumers' preferences for food crops are guided by quality attributes. This study aimed at deciphering the genetic basis of quality traits, especially tuber flesh color (FC) and oxidative browning (OB) in Dioscorea alata, based on the genome-wide association studies (GWAS) approach. The D. alata panel was planted at two locations in Guadeloupe. At harvest, the FC was scored visually as white, cream, or purple on longitudinally sliced mature tubers. The OB was scored visually as the presence or absence of browning after 15 min of exposure of the sliced samples to ambient air. RESULTS: Phenotypic characterization for FC and OB of a diverse panel of D. alata genotypes highlighted significant variation within the panel and across two locations. The genotypes within the panel displayed a weak structure and could be classified into three subpopulations. GWAS identified 14 and 4 significant associations for tuber FC and OB, respectively, with phenotypic variance, explained values ranging from 7.18% to 18.04%. Allele segregation analysis at the significantly associated loci highlighted the favorable alleles for the desired traits, i.e., white FC and no OB. A total of 24 putative candidate genes were identified around the significant signals. A comparative analysis with previously reported quantitative trait loci indicated that numerous genomic regions control these traits in D. alata. CONCLUSION: Our study provides important insights into the genetic control of tuber FC and OB in D. alata. The major and stable loci can be further utilized to improve selection in breeding programs for developing new cultivars with enhanced tuber quality. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Food quality profile of pounded yam and implications for yam breeding.

BACKGROUND: Assessment of the key preferred quality traits in pounded yam, a popularly consumed yam food product in West Africa, is often done through sensory evaluation. Such assessment is time-consuming and results may be biased. Therefore, there is a need to develop objective, high-throughput methods to predict the quality of consumer-preferred traits in pounded yam. This study focused on how key quality traits in pounded yam proposed to yam breeders were determined, measured by biophysical and biochemical methods, in order to shorten the breeding selection cycle through adoption of these methods by breeders. RESULTS: Consumer tests and sensory quantitative descriptive analysis (QDA) validated that preferred priority quality traits in pounded yam were related to textural quality (smooth, stretchable, moldable, slightly sticky and moderately hard) and color (white, cream or light yellow). There were significant correlations between sensory textural quality attributes cohesiveness/moldability, hardness, and adhesiveness/stickiness, with textural quality measurements from instrumental texture profile analysis (TPA). Color measurement parameters (L*, a*, and b*) with chromameter agreed with that of sensory evaluation and can replace the sensory panel approach. The smoothness (R2 = 1.00), stickiness (R2 = 1.00), stretchability (R2 = 1.00), hardness (R2 = 0.99), and moldability (R2 = 0.53) of pounded yam samples can be predicted by the starch, amylose, and protein contents of yam tubers estimated by near-infrared spectroscopy. CONCLUSION: TPA and Hunter colorimeter can be used as medium-high throughput methods to evaluate the textural quality and color of pounded yam in place of the sensory panelists. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Into the range: a latitudinal gradient or a center-margins differentiation of ecological strategies in Arabidopsis thaliana?

BACKGROUND AND AIMS: Determining within-species large-scale variation in phenotypic traits is central to elucidate the drivers of species' ranges. Intraspecific comparisons offer the opportunity to understand how trade-offs and biogeographical history constrain adaptation to contrasted environmental conditions. Here we test whether functional traits, ecological strategies from the CSR scheme and phenotypic plasticity in response to abiotic stress vary along a latitudinal or a center- margins gradient within the native range of Arabidopsis thaliana. METHODS: We experimentally examined the phenotypic outcomes of plant adaptation at the center and margins of its geographic range using 30 accessions from southern, central and northern Europe. We characterized the variation of traits related to stress tolerance, resource use, colonization ability, CSR strategy scores, survival and fecundity in response to high temperature (34 °C) or frost (- 6 °C), combined with a water deficit treatment. KEY RESULTS: We found evidence for both a latitudinal and a center-margins differentiation for the traits under scrutiny. Age at maturity, leaf dry matter content, specific leaf area and leaf nitrogen content varied along a latitudinal gradient. Northern accessions presented a greater survival to stress than central and southern accessions. Leaf area, C-scores, R-scores and fruit number followed a center-margins differentiation. Central accessions displayed a higher phenotypic plasticity than northern and southern accessions for most studied traits. CONCLUSIONS: Traits related to an acquisitive/conservative resource-use trade-off followed a latitudinal gradient. Traits associated with a competition/colonization trade-off differentiated along the historic colonization of the distribution range and then followed a center-margins differentiation. Our findings pinpoint the need to consider the joint effect of evolutionary history and environmental factors when examining phenotypic variation across the distribution range of a species.

Genetic control of flowering in greater yam (Dioscorea alata L.).

BACKGROUND: Greater yam (Dioscorea alata L.) is a major tropical and subtropical staple crop cultivated for its starchy tubers. Breeding of this dioecious species is hampered by its erratic flowering, yet little is currently known on the genetic determinism of its sexual reproduction. RESULT: Here we used a genome-wide association approach and identified a major genetic barrier to reproduction in yam on chromosome 1, as represented by two candidate genes. A deleterious effect on male fitness could be hypothesized considering the involvement of these two genes in male reproduction and the low frequency of this non-flowering dominant allele within the male genepool. We also extended the hypothesis of a XX/XY sex-determination system located on chromosome 6 in D. alata to encompass most of the species diversity. Moreover, a kompetitive allele-specific PCR (KASPar) marker was designed and validated that enables accurate cultivar sex estimation. The reconstruction of chromosome 6 associated with the detection of highly putative structural variations confirmed the possible involvement of a major part of the chromosome. CONCLUSION: The findings of this study, combined with proper estimation of accession ploidy levels to avoid endosperm incompatibility issues, could facilitate the design of future promising parental combinations in D. alata breeding programs. Moreover, the discovery of this genetic barrier to reproduction opens new avenues for gaining insight into yam reproductive biology and diversification.

AraDiv: a dataset of functional traits and leaf hyperspectral reflectance of Arabidopsis thaliana.

Data from functional trait databases have been increasingly used to address questions related to plant diversity and trait-environment relationships. However, such databases provide intraspecific data that combine individual records obtained from distinct populations at different sites and, hence, environmental conditions. This prevents distinguishing sources of variation (e.g., genetic-based variation vs. phenotypic plasticity), a necessary condition to test for adaptive processes and other determinants of plant phenotypic diversity. Consequently, individual traits measured under common growing conditions and encompassing within-species variation across the occupied geographic range have the potential to leverage trait databases with valuable data for functional and evolutionary ecology. Here, we recorded 16 functional traits and leaf hyperspectral reflectance (NIRS) data for 721 widely distributed Arabidopsis thaliana natural accessions grown in a common garden experiment. These data records, together with meteorological variables obtained during the experiment, were assembled to create the AraDiv dataset. AraDiv is a comprehensive dataset of A. thaliana's intraspecific variability that can be explored to address questions at the interface of genetics and ecology.

A Perspective on Plant Phenomics: Coupling Deep Learning and Near-Infrared Spectroscopy.

The trait-based approach in plant ecology aims at understanding and classifying the diversity of ecological strategies by comparing plant morphology and physiology across organisms. The major drawback of the approach is that the time and financial cost of measuring the traits on many individuals and environments can be prohibitive. We show that combining near-infrared spectroscopy (NIRS) with deep learning resolves this limitation by quickly, non-destructively, and accurately measuring a suite of traits, including plant morphology, chemistry, and metabolism. Such an approach also allows to position plants within the well-known CSR triangle that depicts the diversity of plant ecological strategies. The processing of NIRS through deep learning identifies the effect of growth conditions on trait values, an issue that plagues traditional statistical approaches. Together, the coupling of NIRS and deep learning is a promising high-throughput approach to capture a range of ecological information on plant diversity and functioning and can accelerate the creation of extensive trait databases.

Near-infrared spectroscopy applications for high-throughput phenotyping for cassava and yam: A review.

The review aimed to identify the different high-throughput phenotyping (HTP) techniques that used for quality evaluation in cassava and yam breeding programmes, and this has provided insights towards the development of metrics and their application in cassava and yam improvements. A systematic review of the published research articles involved the use of NIRS in analysing the quality traits of cassava and yam was carried out, and Scopus, Science Direct, Web of Sciences and Google Scholar were searched. The results of the review established that NIRS could be used in understanding the chemical constituents (carbohydrate, protein, vitamins, minerals, carotenoids, moisture, starch, etc.) for high-throughput phenotyping. This study provides preliminary evidence of the application of NIRS as an efficient and affordable procedure for HTP. However, the feasibility of using mid-infrared spectroscopy (MIRS) and hyperspectral imaging (HSI) in combination with the NIRS could be further studied for quality traits phenotyping.

A Bayesian network approach for the identification of relationships between drivers of chlordecone bioaccumulation in plants.

Plants were sampled from four different types of chlordecone-contaminated land in Guadeloupe (West Indies). The objective was to investigate the importance of biological and agri-environmental parameters in the ability of plants to bioaccumulate chlordecone. Among the plant traits studied, only the growth habit significantly affected chlordecone transfer, since prostrate plants concentrated more chlordecone than erect plants. In addition, intensification of land use has led to a significant increase in the amount of chlordecone absorbed by plants. The use of Bayesian networks uncovers some hypothesis and identifies paths for reflection and possible studies to identify and quantify relationships that explain our data. Graphical abstract.

Consumers' preferences for fresh yam: a focus group study.

In West and Central Africa and in the Caribbean, yam is one of the most important sources of carbohydrates and has a great potential to improve food security. The yam production sector is, however, now challenged by the satisfaction of evolving consumers' preferences. Since little is known about consumers' preferences regarding yams' characteristics, product quality, and the drivers of yam purchase, six focus group discussions were conducted (for a total of 31 participants). Among the purchasing criteria, price was considered more important than the others. It was followed by the external damage, the origin, and the size of the tuber. The most frequently cited consumption criteria were the taste, the texture, and color of flesh after cooking. Taste was considered more important than the other criteria. Three consumers' profiles were established reflecting heterogeneity in preferences, especially as concerns the willingness to pay for yam and consumption habits. They were designated as the Hedonistic, the Thrifty and the Flexible. Our results suggest that innovations can be implemented to sustain and stimulate the development of the yam sector in Guadeloupe. Two main development paths were identified. The first path is the valorization of the great existing diversity of yam varieties and the increase in the level of information for consumers about product attributes such as the cooking mode, the origin, and the mode of production. Building a marketing strategy based on the valorization of this diversity can help maintain and preserve yam's agro-biodiversity and the satisfaction of rapidly evolving consumption habits. The second path is the definition of yam ideotypes that suit consumers' needs. We expect that tailoring the production to consumers' needs will have a positive impact on global food security in the Caribbean region.

Multivariate Analysis of the Determinants of the End-Product Quality of Manure-Based Composts and Vermicomposts Using Bayesian Network Modelling.

Previous studies indicated that the quality of tropical composts is poorer than that of composts produced in temperate regions. The aim of this study was to test the type of manure, the use of co-composting with green waste, and the stabilization method for their ability to improve compost quality in the tropics. We produced 68 composts and vermicomposts that were analysed for their C, lignin and NPK contents throughout the composting process. Bayesian networks were used to assess the mechanisms controlling compost quality. The concentration effect, for C and lignin, and the initial blend quality, for NPK content, were the main factors affecting compost quality. Cattle manure composts presented the highest C and lignin contents, and poultry litter composts exhibited the highest NPK content. Co-composting improved quality by enhancing the concentration effect, which reduced the impact of C and nutrient losses. Vermicomposting did not improve compost quality; co-composting without earthworms thus appears to be a suitable stabilization method under the conditions of this study because it produced high quality composts and is easier to implement.

Dry Matter Production, Nutrient Cycled and Removed, and Soil Fertility Changes in Yam-Based Cropping Systems with Herbaceous Legumes in the Guinea-Sudan Zone of Benin.

Traditional yam-based cropping systems (shifting cultivation, slash-and-burn, and short fallow) often result in deforestation and soil nutrient depletion. The objective of this study was to determine the impact of yam-based systems with herbaceous legumes on dry matter (DM) production (tubers, shoots), nutrients removed and recycled, and the soil fertility changes. We compared smallholders' traditional systems (1-year fallow of Andropogon gayanus-yam rotation, maize-yam rotation) with yam-based systems integrated herbaceous legumes (Aeschynomene histrix/maize intercropping-yam rotation, Mucuna pruriens/maize intercropping-yam rotation). The experiment was conducted during the 2002 and 2004 cropping seasons with 32 farmers, eight in each site. For each of them, a randomized complete block design with four treatments and four replicates was carried out using a partial nested model with five factors: Year, Replicate, Farmer, Site, and Treatment. Analysis of variance (ANOVA) using the general linear model (GLM) procedure was applied to the dry matter (DM) production (tubers, shoots), nutrient contribution to the systems, and soil properties at depths 0-10 and 10-20 cm. DM removed and recycled, total N, P, and K recycled or removed, and soil chemical properties (SOM, N, P, K, and pH water) were significantly improved on yam-based systems with legumes in comparison with traditional systems.

Varietal Dynamics and Yam Agro-Diversity Demonstrate Complex Trajectories Intersecting Farmers' Strategies, Networks, and Disease Experience.

Loss of varietal diversity is a worldwide challenge to crop species at risk for genetic erosion, while the loss of biological resources may hinder future breeding objectives. Loss of varieties has been mostly investigated in traditional agricultural systems where variety numbers are dramatically high, or for most economically important crop species for which comparison between pre-intensive and modern agriculture was possible. Varietal dynamics, i.e., turnover, or gains and losses of varieties by farmers, is nevertheless more rarely studied and while we currently have good estimates of genetic or varietal diversity for most crop species, we have less information as to how on farm agro-diversity changes and what cause its dynamics. We therefore investigated varietal dynamics in the agricultural yam system in the Caribbean island of Guadeloupe. We interviewed producers about varieties they cultivated in the past compared to their current varieties, in addition to characterizing yam cropping characteristics and both farm level and producers socio-economic features. We then used regression tree analyses to investigate the components of yam agro-diversity, varietal dynamics and impact of anthracnose on varieties. Our data demonstrated that no dramatic loss of varieties occurred within the last decades. Cultivation changes mostly affected widespread cultivars while frequency of uncommon varieties stayed relatively stable. Varietal dynamics nevertheless followed sub-regional patterns, and socio-economic influences such as producer age or farm crop diversity. Recurrent anthracnose epidemics since the 1970s did not alter varietal dynamics strongly, but sometimes translated into transition from Dioscorea alata to less susceptible species or into a decrease of yam cultivation. Factors affecting changes in agro-diversity were not relating to agronomy in our study, and surprisingly there were different processes delineating short term from long term varietal dynamics, independently of disease risk. Our results highlighted the importance of understanding varietal dynamics, an often overlooked component of agriculture sustainability, in addition to evolutionary forces shaping agro-diversity and genetic diversity distribution within crops. It is also crucial to understand how processes involved do scale up worldwide and for different crop species, so as not to mislead on-farm conservation efforts and efficacy of agro-diversity preservation.