On-farm dynamic management of genetic diversity: the impact of seed diffusions and seed saving practices on a population-variety of bread wheat

Crop genetic erosion: understanding and responding to loss of crop diversity

Crop diversity underpins the productivity, resilience and adaptive capacity of agriculture. Loss of this diversity, termed crop genetic erosion, is therefore concerning. While alarms regarding evident declines in crop diversity have been raised for over a century, the magnitude, trajectory, drivers and significance of these losses remain insufficiently understood. We outline the various definitions, measurements, scales and sources of information on crop genetic erosion. We then provide a synthesis of evidence regarding changes in the diversity of traditional crop landraces on farms, modern crop cultivars in agriculture, crop wild relatives in their natural habitats and crop genetic resources held in conservation repositories. This evidence indicates that marked losses, but also maintenance and increases in diversity, have occurred in all these contexts, the extent depending on species, taxonomic and geographic scale, and region, as well as analytical approach. We discuss steps needed to further advance knowledge around the agricultural and societal significance, as well as conservation implications, of crop genetic erosion. Finally, we propose actions to mitigate, stem and reverse further losses of crop diversity.

The INCREASE project: Intelligent Collections of food-legume genetic resources for European agrofood systems

Food legumes are crucial for all agriculture-related societal challenges, including climate change mitigation, agrobiodiversity conservation, sustainable agriculture, food security and human health. The transition to plant-based diets, largely based on food legumes, could present major opportunities for adaptation and mitigation, generating significant co-benefits for human health. The characterization, maintenance and exploitation of food-legume genetic resources, to date largely unexploited, form the core development of both sustainable agriculture and a healthy food system. INCREASE will implement, on chickpea (Cicer arietinum), common bean (Phaseolus vulgaris), lentil (Lens culinaris) and lupin (Lupinus albus and L. mutabilis), a new approach to conserve, manage and characterize genetic resources. Intelligent Collections, consisting of nested core collections composed of single-seed descent-purified accessions (i.e., inbred lines), will be developed, exploiting germplasm available both from genebanks and on-farm and subjected to different levels of genotypic and phenotypic characterization. Phenotyping and gene discovery activities will meet, via a participatory approach, the needs of various actors, including breeders, scientists, farmers and agri-food and non-food industries, exploiting also the power of massive metabolomics and transcriptomics and of artificial intelligence and smart tools. Moreover, INCREASE will test, with a citizen science experiment, an innovative system of conservation and use of genetic resources based on a decentralized approach for data management and dynamic conservation. By promoting the use of food legumes, improving their quality, adaptation and yield and boosting the competitiveness of the agriculture and food sector, the INCREASE strategy will have a major impact on economy and society and represents a case study of integrative and participatory approaches towards conservation and exploitation of crop genetic resources.

Biocultural Diversity for Food System Transformation Under Global Environmental Change

Biocultural diversity is central to the nutrition, resilience, and adaptive capacity of Indigenous and traditional peoples, who collectively maintain the longest ongoing human experiences with the provision of food under environmental change. In the form of crops and livestock and associated knowledge on their cultivation and use, food-related biocultural diversity likewise underpins global food security. As food system transformation is increasingly recognized as an urgent priority, we argue that food security, sustainability, resilience, and adaptive capacity can be furthered through greater emphasis on conservation, use, and celebration of food-related biocultural diversity. We provide examples from the Parque de la Papa, Peru, a “food biocultural diversity neighborhood” which through advocacy and partnerships based around its diversity, has both enhanced local communities and contributed to food security at a much larger scale. We outline collaborative actions which we believe are important to up- and out-scale food biocultural diversity neighborhood successes. Further research and knowledge sharing are critical to better document, understand, track, and communicate the value, functions, and state of biocultural diversity in food systems. Expanded training and capacity development opportunities are important to enable the interchange of experiences and visions on food, health, sustainability and resilience, climate adaptation, equity and justice, and livelihood generation with others facing similar challenges. Finally, strengthened networking across food biocultural diversity neighborhoods is essential to their persistence and growth as they increasingly engage with local, national, and international organizations, based on shared interests and on their own terms, across five continents.

Trees and their seed networks: The social dynamics of urban fruit trees and implications for genetic diversity

Trees are a traditional component of urban spaces where they provide ecosystem services critical to urban wellbeing. In the Tropics, urban trees’ seed origins have rarely been characterized. Yet, understanding the social dynamics linked to tree planting is critical given their influence on the distribution of associated genetic diversity. This study examines elements of these dynamics (seed exchange networks) in an emblematic indigenous fruit tree species from Central Africa, the African plum tree (Dacryodes edulis, Burseraceae), within the urban context of Yaoundé. We further evaluate the consequences of these social dynamics on the distribution of the genetic diversity of the species in the city. Urban trees were planted predominantly using seeds sourced from outside the city, resulting in a level of genetic diversity as high in Yaoundé as in a whole region of production of the species. Debating the different drivers that foster the genetic diversity in planted urban trees, the study argues that cities and urban dwellers can unconsciously act as effective guardians of indigenous tree genetic diversity.

Gender and Social Seed Networks for Climate Change Adaptation: Evidence from Bean, Finger Millet, and Sorghum Seed Systems in East Africa

In many East African countries, women and men have different levels of access to formal markets for agricultural inputs, including seed, reflecting a combination of gender norms and resource constraints. As a result, women and men may have different levels of participation in—and reliance upon—informal seed systems for sourcing preferred planting material and accessing new crop varieties over time. We use network analysis to explore differences in seed networks accessed by women and men for three major food security crops—beans, finger millet, and sorghum—in Kenya, Tanzania, and Uganda. Drawing on data from an original survey of 1001 rural farm households across five study sites, we find that women, on average, have fewer connections to experts and farmers’ groups than men but are relatively better connected in farmer-to-farmer social networks across different farming systems. We further find women’s and men’s networks are clustered by gender (i.e., women’s networks include more women, and men’s networks include more men)—and that men’s networks are more likely to exchange improved seed. Women’s networks, though sometimes larger, are less likely to exchange improved varieties that might help farmers adapt to climate change. Women farmers across contexts may also be more reliant on farmer-to-farmer networks than men due to their relative isolation from other seed and information sources. Findings emphasize the need for careful attention to the different implications of seed policies, market interventions, and other seed system reforms to support gender-equitable food security options for women and men in sub-Saharan Africa.

Genetic Variability, Heritability, and Clustering Pattern Exploration of Bambara Groundnut (Vigna subterranea L. Verdc) Accessions for the Perfection of Yield and Yield-Related Traits

Bambara groundnut (Vigna subterranea L. Verdc.) is considered an emerging crop for the future and known as a crop for the new millennium. The core intention of this research work was to estimate the variation of landraces of Bambara groundnut considering their 14 qualitative and 27 numerical traits, to discover the best genotype fitted in Malaysia. The findings of the ANOVA observed a highly significant variation (p ≤ 0.01) for all the traits evaluated. There was a substantial variation (7.27 to 41.21%) coefficient value, and 14 out of the 27 numerical traits noted coefficient of variation (CV) ≥ 20%. Yield (kg/ha) disclosed positively strong to perfect high significant correlation (r = 0.75 to 1.00; p ≤ 0.001) with traits like fresh pod weight, dry pod weight, and dry seed weight. The topmost PCV and GCV values were estimated for biomass dry (41.09%) and fresh (40.53%) weight with high heritability (Hb) and genetic advance (GA) Hb = 95.19%, GA = 80.57% and Hb = 98.52%, GA = 82.86%, respectively. The topmost heritability was recorded for fresh pod weight (99.89%) followed by yield (99.75%) with genetic advance 67.95% and 62.03%, respectively. The traits with Hb ≥ 60% and GA ≥ 20% suggested the least influenced by the environment as well as governed by the additive genes and direct selection for improvement of such traits can be beneficial. To estimate the genetic variability among accessions, the valuation of variance components, coefficients of variation, heritability, and genetic advance were calculated. To authenticate the genetic inequality, an unweighted pair group produced with arithmetic mean (UPGMA) and principal component analysis was executed based on their measurable traits that could be a steadfast method for judging the degree of diversity. Based on the UPGMA cluster analysis, constructed five distinct clusters and 44 accessions from clusters II and IV consider an elite type of genotypes that produce more than one ton yield per hectare land with desirable traits. This study exposed an extensive disparity among the landraces and the evidence on genetic relatives will be imperative in using the existing germplasm for Bambara groundnut varietal improvement. Moreover, this finding will be beneficial for breeders to choose the desirable numerical traits of V. subterranea in their future breeding program.

SHiNeMaS: a web tool dedicated to seed lots history, phenotyping and cultural practices

MOTIVATION

In 2005, researchers from the French National Research Institute for Agriculture, Food and Environment (Institut national de recherche pour l'agriculture, l'alimentation et l'environnement, INRAE) started a collaboration with the French farmers' seed network Réseau Semences Paysannes (RSP) on bread wheat participatory breeding (PPB). The aims were: (1) to study on-farm management of crop diversity, (2) to develop population-varieties adapted to organic and low-inputs agriculture, (3) to co-develop tools and methods adapted to on-farm experiments. In this project, researchers and farmers' organizations needed to map the history and life cycle of the population-varieties using network formalism to represent relationships between seed lots. All this information had to be centralized and stored in a database.

RESULTS

We describe here SHiNeMaS (Seeds History and Network Management System) a web tool database. SHiNeMaS aims to provide useful interfaces to track seed lot history and related data (phenotyping, environment, cultural practices). Although SHiNeMaS has been developed in the context of a bread wheat participatory breeding program, the database has been designed to manage any kind and even multiple cultivated plant species. SHiNeMaS is available under Affero GPL licence and uses free technologies such as the Python language, Django framework or PostgreSQL database management system (DBMS).

CONCLUSION

We developed SHiNeMaS, a web tool database, dedicated to the management of the history of seed lots and related data like phenotyping, environmental information and cultural practices. SHiNeMaS has been used in production in our laboratory for 5 years and farmers' organizations facilitators manage their own information in the system.

Peasant Seeds in France: Fostering A More Resilient Agriculture

The profitability of the French agricultural sector has fallen over the last two decades, leading to the suggestion of a “rupture in technical progress”. Additionally, the intellectual property regime in force has contributed to the erosion of the cultivated biodiversity, limiting plant resiliency to climate change and other hazards. In the face of these challenges, agroecological farming practices are a viable alternative. This paper investigates the positive and negative aspects associated with the development of alternative seed procurement networks in France. The findings indicate that peasant seed networks can effectively contribute to overcoming many of the structural blockages with which French agriculture is confronted, but that yield concerns; higher information and supervisory costs, as well as the unfavourable legislative context, constitute key challenges to their development. However, these could be partially or totally eliminated if adequate policies are implemented. In this regard, the recommendations are to: (i) strengthen the dialogue with farmers in the shaping of policies related to the use of plant genetic resources; (ii) abrogate the “obligatory voluntary contribution” on farm-saved seeds; (iii) diversify the collection of Centres for Biological Resources, increase their number, and democratize their access; (iv) harmonize the French and European regime on intellectual property; and (v) encourage participatory research.

Predicting genomic selection efficiency to optimize calibration set and to assess prediction accuracy in highly structured populations

KEY MESSAGE

We propose a criterion to predict genomic selection efficiency for structured populations. This criterion is useful to define optimal calibration set and to estimate prediction reliability for multiparental populations. Genomic selection refers to the use of genotypic information for predicting the performance of selection candidates. It has been shown that prediction accuracy depends on various parameters including the composition of the calibration set (CS). Assessing the level of accuracy of a given prediction scenario is of highest importance because it can be used to optimize CS sampling before collecting phenotypes, and once the breeding values are predicted it informs the breeders about the reliability of these predictions. Different criteria were proposed to optimize CS sampling in highly diverse panels, which can be useful to screen collections of genotypes. But plant breeders often work on structured material such as biparental or multiparental populations, for which these criteria are less adapted. We derived from the generalized coefficient of determination (CD) theory different criteria to optimize CS sampling and to assess the reliability associated to predictions in structured populations. These criteria were evaluated on two nested association mapping (NAM) populations and two highly diverse panels of maize. They were efficient to sample optimized CS in most situations. They could also estimate at least partly the reliability associated to predictions between NAM families, but they could not estimate differences in the reliability associated to the predictions of NAM families using the highly diverse panels as calibration sets. We illustrated that the CD criteria could be adapted to various prediction scenarios including inter and intra-family predictions, resulting in higher prediction accuracies.

Short-Term Local Adaptation of Historical Common Bean (Phaseolus vulgaris L.) Varieties and Implications for In Situ Management of Bean Diversity

Recognizing both the stakes of traditional European common bean diversity and the role farmers’ and gardeners’ networks play in maintaining this diversity, the present study examines the role that local adaptation plays for the management of common bean diversity in situ. To the purpose, four historical bean varieties and one modern control were multiplied on two organic farms for three growing seasons. The fifteen resulting populations, the initial ones and two populations of each variety obtained after the three years of multiplication, were then grown in a common garden. Twenty-two Simple Sequence Repeat (SSR) markers and 13 phenotypic traits were assessed. In total, 68.2% of tested markers were polymorphic and a total of 66 different alleles were identified. F_ST analysis showed that the genetic composition of two varieties multiplied in different environments changed. At the phenotypic level, differences were observed in flowering date and leaf length. Results indicate that three years of multiplication suffice for local adaptation to occur. The spatial dynamics of genetic and phenotypic bean diversity imply that the maintenance of diversity should be considered at the scale of the network, rather than individual farms and gardens. The microevolution of bean populations within networks of gardens and farms emerges as a research perspective.

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.

Diversifying mechanisms in the on-farm evolution of crop mixtures

While modern agriculture relies on genetic homogeneity, diversifying practices associated with seed exchange and seed recycling may allow crops to adapt to their environment. This socio-genetic model is an original experimental evolution design referred to as on-farm dynamic management of crop diversity. Investigating such model can help in understanding how evolutionary mechanisms shape crop diversity submitted to diverse agro-environments. We studied a French farmer-led initiative where a mixture of four wheat landraces called 'Mélange de Touselles' (MDT) was created and circulated within a farmers' network. The 15 sampled MDT subpopulations were simultaneously submitted to diverse environments (e.g. altitude, rainfall) and diverse farmers' practices (e.g. field size, sowing and harvesting date). Twenty-one space-time samples of 80 individuals each were genotyped using 17 microsatellite markers and characterized for their heading date in a 'common-garden' experiment. Gene polymorphism was studied using four markers located in earliness genes. An original network-based approach was developed to depict the particular and complex genetic structure of the landraces composing the mixture. Rapid differentiation among populations within the mixture was detected, larger at the phenotypic and gene levels than at the neutral genetic level, indicating potential divergent selection. We identified two interacting selection processes: variation in the mixture component frequencies, and evolution of within-variety diversity, that shaped the standing variability available within the mixture. These results confirmed that diversifying practices and environments maintain genetic diversity and allow for crop evolution in the context of global change. Including concrete measurements of farmers' practices is critical to disentangle crop evolution processes.

An Analysis of Social Seed Network and Its Contribution to On-Farm Conservation of Crop Genetic Diversity in Nepal

Social seed systems are important for the maintenance of crop genetic diversity on farm. This is governed by local and informal system in the community through a farmers’ network. This paper analyses these local seed systems through application of social network analysis tools and mappings and examines the network member and its stability over space and time in a small rice farming community in Nepal. NetDraw software is used for data analysis and network mapping. We found that the dynamic network structure had key role in provisioning of traditional varieties and maintaining of crop genetic diversity on farm. We identify and ascertain the key network members, constituted either as nodal or bridging (connector) farmers, occupying central position in the network who promote seed flow of local crop diversity, thus strengthening crop genetic resource diversity on farm.

Network impact on persistence in a finite population dynamic diffusion model: application to an emergent seed exchange network

Dynamic extinction colonisation models (also called contact processes) are widely studied in epidemiology and in metapopulation theory. Contacts are usually assumed to be possible only through a network of connected patches. This network accounts for a spatial landscape or a social organization of interactions. Thanks to social network literature, heterogeneous networks of contacts can be considered. A major issue is to assess the influence of the network in the dynamic model. Most work with this common purpose uses deterministic models or an approximation of a stochastic Extinction-Colonisation model (sEC) which are relevant only for large networks. When working with a limited size network, the induced stochasticity is essential and has to be taken into account in the conclusions. Here, a rigorous framework is proposed for limited size networks and the limitations of the deterministic approximation are exhibited. This framework allows exact computations when the number of patches is small. Otherwise, simulations are used and enhanced by adapted simulation techniques when necessary. A sensitivity analysis was conducted to compare four main topologies of networks in contrasting settings to determine the role of the network. A challenging case was studied in this context: seed exchange of crop species in the Réseau Semences Paysannes (RSP), an emergent French farmers׳ organisation. A stochastic Extinction-Colonisation model was used to characterize the consequences of substantial changes in terms of RSP׳s social organization on the ability of the system to maintain crop varieties.

Anchoring durum wheat diversity in the reality of traditional agricultural systems: varieties, seed management, and farmers' perception in two Moroccan regions

BACKGROUND

Traditional agrosystems are the places were crop species have evolved and continue to evolve under a combination of human and environmental pressures. A better knowledge of the mechanisms underlying the dynamics of crop diversity in these agrosystems is crucial to sustain food security and farmers' self-reliance. It requires as a first step, anchoring a description of the available diversity in its geographical, environmental, cultural and socio-economic context.

METHODS

We conducted interviews with farmers cultivating durum wheat in two contrasted traditional agrosystems of Morocco in the Pre-Rif (163 farmers) and in the oases of the Atlas Mountains (110 farmers). We documented the varietal diversity of durum wheat, the main characteristics of the farms, the farming and seed management practices applied to durum wheat, and the farmers' perception of their varieties.

RESULTS

As expected in traditional agrosystems, farmers largely practiced diversified subsistence agriculture on small plots and relied on on-farm seed production or informal seed exchange networks. Heterogeneity nevertheless prevailed on many variables, especially on the modernization of practices in the Pre-Rif region. Fourteen (resp. 11) traditional and 5 (resp. 3) modern varieties were identified in the Pre-Rif region (resp. in the Atlas Mountains). The majority of farmers grew a single variety, and most traditional varieties were distributed in restricted geographical areas. At the farm level, more than half of the varieties were renewed in the last decade in the Pre-Rif, a more rapid renewal than in the Atlas Mountain. Modern varieties were more prevalent in the Pre-Rif region and were integrated in the traditional practices of seed production, selection and exchange. They were clearly distinguished by the farmers from the landraces, the last ones being appreciated for their quality traits.

CONCLUSIONS

The surveyed traditional agrosystems constitute open, dynamic and heterogeneous entities. We suggest that competing factors could favour or limit the cultivation of improved varieties and the erosion of original durum wheat diversity. This first description opens the way to focused further investigations, including complementing variety names with cultural, genetic and phenotypic information and unravelling the multidimensional factors and consequences of modern variety adoption.

Maximizing the reliability of genomic selection by optimizing the calibration set of reference individuals: comparison of methods in two diverse groups of maize inbreds (Zea mays L.)

Genomic selection refers to the use of genotypic information for predicting breeding values of selection candidates. A prediction formula is calibrated with the genotypes and phenotypes of reference individuals constituting the calibration set. The size and the composition of this set are essential parameters affecting the prediction reliabilities. The objective of this study was to maximize reliabilities by optimizing the calibration set. Different criteria based on the diversity or on the prediction error variance (PEV) derived from the realized additive relationship matrix-best linear unbiased predictions model (RA-BLUP) were used to select the reference individuals. For the latter, we considered the mean of the PEV of the contrasts between each selection candidate and the mean of the population (PEVmean) and the mean of the expected reliabilities of the same contrasts (CDmean). These criteria were tested with phenotypic data collected on two diversity panels of maize (Zea mays L.) genotyped with a 50k SNPs array. In the two panels, samples chosen based on CDmean gave higher reliabilities than random samples for various calibration set sizes. CDmean also appeared superior to PEVmean, which can be explained by the fact that it takes into account the reduction of variance due to the relatedness between individuals. Selected samples were close to optimality for a wide range of trait heritabilities, which suggests that the strategy presented here can efficiently sample subsets in panels of inbred lines. A script to optimize reference samples based on CDmean is available on request.