Sustainable management practices for durum wheat production: Analyzing specific agronomic interventions on productivity, grain micronutrient content, and quality.

As compared with single agronomic crop management practices during grain formation, knowledge about integrated agronomic management practices on grain mineral composition and grain technological properties in durum wheat is limited. This knowledge is important for determining management strategies aimed at increasing grain yield without affecting grain nutritional quality. Integrated agronomic practices such as foliar nutrient application × seeding rate × varieties combined with growing locations were investigated to evaluate the dynamics of yield and grain quality traits. Two durum wheat varieties, three-level of micronutrients (i.e. control, FeSO4, and ZnSO4), and four levels of seeding rate (i.e. 100, 125, 150, and 175 kg ha-1) were arranged in split-split plot design under two different growing locations (environments). The main plots were assigned to the varieties, subplots to micronutrients, and sub-sub plots to the seeding rate treatments. Zinc and iron were applied in a form of ZnSO4 and FeSO4 at the early flowering stage, both at a rate of 25 kg ha-1. Results showed a linear increment in biomass (21.5%) and grain yield (23.5%) under a high seeding rate, even though the 1000-grain weight, the number of grains spike-1, spike length, and the number of grains spike-1 were decreased. Higher varietal and environmental response of seeding rate was observed between varieties. The grain protein content, gluten, and zeleyn index decreased as the seeding rate increased. Grain micronutrient content was significantly influenced by seeding rate and varietal difference. The grain protein content was higher in a dryland environment than in a wet environment. A combined use of density-tolerant varieties, high seeding rate, and foliar-based iron application can improve the grain yield from 2.01 to 3.20 t ha-1 under a potential environment. Hence, all stakeholders should consider the genotype (G), environment (E), management (M), and their synergies, as far as grain yield and quality are considered simultaneously.

Indigenous agricultural knowledge: A neglected human based resource for sustainable crop protection and production.

Indigenous knowledge, developed over generations and owned by communities or individuals within a community, offers alternative strategies and perspectives on resource management and use. However, as emphasized in the contemporary agricultural history of Ethiopia, the most effective indigenous agricultural knowledge has not been well documented and some of them are replaced by modern techniques. This study was therefore conducted to assess and document community-based techniques to control pests and diseases and the practical implications of indigenous farming techniques. A focus group discussion, key informant interviews and semi-structured questionnaires were conducted with 150 farmers. The result showed that a substantial number (92%) of the farming community uses indigenous based plant protection measures. Indigenous farmers (92%) splash liquids made of cow urine to control the adverse effect of fungi. Farmers are also using different seed selection methods for next season planting. About 29% of the farmers do single head-based seed selection prior to mass harvesting, 34% are collected as "Qerm" and 45% select their seeds during threshing. Indigenous farming knowledge varies with the natural feature of the growing location and cropping system, including the rainfall pattern, soil fertility status, crop, and weed type. The observed positive effect of indigenous agricultural practices on crop production substantiates the need to include these essential approaches in the cultivation system along with the modern agronomic techniques. This might reduce the dependency on expensive and pollutant agricultural inputs. However, sociodemographic factors such as educational level, marital status and farming experience have been found as a determinant factor that influences utilization of indigenous farming knowledge. It can be therefore inferred that documenting indigenous knowledge and proving its applicability scientifically could contribute to organically oriented agricultural production and consequently reduce agriculture's contribution to environmental pollution.

A dataset of Agronomic Biofortification and Seeding rate - by - Location effects on Grain Mineral concentration, End-use quality and Agro-phenological traits of Durum wheat Genotypes.

Improving durum wheat end-use quality traits such as protein and gluten content becomes the principal research focus area, due to the increase in market demand and premium price paid for durum wheat producing farmers. The success is, however, limited because of crop genetic bottleneck, factors from growing environments and crop agronomic management practices. A study was conducted to i) identify an optimum seeding rate for durum wheat genotypes that can improve grain yield and grain quality and ii) to evaluate the effect of agronomic biofortification on grain protein, gluten contents, Zeleny index, and grain mineral content. Zinc and Iron containing fertilizers were applied foliarily in the form of ZnSO4.7H2O and FeSO4.7H2O. The data presented in this dataset article included yield and yield related traits, phenological and grain quality traits as well as grain Zn and Fe contents. The grain mineral content was measured by using atomic absorption photometer. A machine Minfra Smart T® wheat grain analyzer was used to measure grain protein content, gluten content, and Zeleny index values for each sample. The collected data were analyzed using GenStat (14th ed.) statistical software package. The aim of this dataset article is make the data publicly available to enable further extended analyses and as a guide for further research works to improve the productivity of smallholder durum wheat producing farmers.

Integrating Conventional and Participatory Crop Improvement for Smallholder Agriculture Using the Seeds for Needs Approach: A Review.

In response to the climate change, it is essential to provide smallholder farmers with improved field crop genotypes that may increase the resilience of their farming system. This requires a fast turnover of varieties in a system capable of injecting significant amounts of genetic diversity into productive landscapes. Crop improvement is a pivotal strategy to cope with and adapt to climate change. Modern breeding may rely on the genomics revolution to speed up the development of new varieties with adaptive potential. However, centralized breeding may not adequately address smallholder farmers' needs for more locally acclimatized varieties or groups of varieties. This, in turn, constrains adoption of new varieties that reduces the effectiveness of a resource-intensive breeding process, an issue that may be overcome with participatory, decentralized approaches. Whether high-tech centralized breeding or decentralized participatory approaches are better suited for smallholder farmers in the global South is hotly debated. Sidestepping any false dichotomies and ideological issues in these debates, this review provides a perspective on relevant advances in a breeding approach that combines the two approaches and uses genomics for trait mining from ex situ collections of genetic materials, participatory multilocation trials and crowdsourced citizen science. It argues that this new combination of high-tech centralized and participatory decentralized methods can provide a coherent and effective approach to breeding for climate adaptation and the present review advocates on a different way forward for the future research.

The Rural Household Multiple Indicator Survey, data from 13,310 farm households in 21 countries.

The Rural Household Multiple Indicator Survey (RHoMIS) is a standardized farm household survey approach which collects information on 758 variables covering household demographics, farm area, crops grown and their production, livestock holdings and their production, agricultural product use and variables underlying standard socio-economic and food security indicators such as the Probability of Poverty Index, the Household Food Insecurity Access Scale, and household dietary diversity. These variables are used to quantify more than 40 different indicators on farm and household characteristics, welfare, productivity, and economic performance. Between 2015 and the beginning of 2018, the survey instrument was applied in 21 countries in Central America, sub-Saharan Africa and Asia. The data presented here include the raw survey response data, the indicator calculation code, and the resulting indicator values. These data can be used to quantify on- and off-farm pathways to food security, diverse diets, and changes in poverty for rural smallholder farm households.

Crop variety management for climate adaptation supported by citizen science.

Crop adaptation to climate change requires accelerated crop variety introduction accompanied by recommendations to help farmers match the best variety with their field contexts. Existing approaches to generate these recommendations lack scalability and predictivity in marginal production environments. We tested if crowdsourced citizen science can address this challenge, producing empirical data across geographic space that, in aggregate, can characterize varietal climatic responses. We present the results of 12,409 farmer-managed experimental plots of common bean (Phaseolus vulgaris L.) in Nicaragua, durum wheat (Triticum durum Desf.) in Ethiopia, and bread wheat (Triticum aestivum L.) in India. Farmers collaborated as citizen scientists, each ranking the performance of three varieties randomly assigned from a larger set. We show that the approach can register known specific effects of climate variation on varietal performance. The prediction of variety performance from seasonal climatic variables was generalizable across growing seasons. We show that these analyses can improve variety recommendations in four aspects: reduction of climate bias, incorporation of seasonal climate forecasts, risk analysis, and geographic extrapolation. Variety recommendations derived from the citizen science trials led to important differences with previous recommendations.

A large nested association mapping population for breeding and quantitative trait locus mapping in Ethiopian durum wheat.

The Ethiopian plateau hosts thousands of durum wheat (Triticum turgidum subsp. durum) farmer varieties (FV) with high adaptability and breeding potential. To harness their unique allelic diversity, we produced a large nested association mapping (NAM) population intercrossing fifty Ethiopian FVs with an international elite durum wheat variety (Asassa). The Ethiopian NAM population (EtNAM) is composed of fifty interconnected bi-parental families, totalling 6280 recombinant inbred lines (RILs) that represent both a powerful quantitative trait loci (QTL) mapping tool, and a large pre-breeding panel. Here, we discuss the molecular and phenotypic diversity of the EtNAM founder lines, then we use an array featuring 13 000 single nucleotide polymorphisms (SNPs) to characterize a subset of 1200 EtNAM RILs from 12 families. Finally, we test the usefulness of the population by mapping phenology traits and plant height using a genome wide association (GWA) approach. EtNAM RILs showed high allelic variation and a genetic makeup combining genetic diversity from Ethiopian FVs with the international durum wheat allele pool. EtNAM SNP data were projected on the fully sequenced AB genome of wild emmer wheat, and were used to estimate pairwise linkage disequilibrium (LD) measures that reported an LD decay distance of 7.4 Mb on average, and balanced founder contributions across EtNAM families. GWA analyses identified 11 genomic loci individually affecting up to 3 days in flowering time and more than 1.6 cm in height. We argue that the EtNAM is a powerful tool to support the production of new durum wheat varieties targeting local and global agriculture.

Erratum: Joining smallholder farmers' traditional knowledge with metric traits to select better varieties of Ethiopian wheat.

A correction to this article has been published and is linked from the HTML version of this paper. The error has been fixed in the paper.

Genome-Wide Association Study of Septoria tritici Blotch Resistance in Ethiopian Durum Wheat Landraces.

Septoria tritici blotch (STB) is a devastating fungal disease affecting durum and bread wheat cultivation worldwide. The identification, development, and employment of resistant wheat genetic material is the key to overcoming costs and limitations of fungicide treatments. The search for resistance sources in untapped genetic material may speed up the deployment of STB genetic resistance in the field. Ethiopian durum wheat landraces represent a valuable source of such diversity. In this study, 318 Ethiopian durum wheat genotypes, for the most part traditional landraces, were phenotyped for resistance to different aspects of STB infection. Phenology, yield and yield component traits were concurrently measured the collection. Here we describe the distribution of STB resistance traits in modern varieties and in landraces, and the relation existing between STB resistance and other agronomic traits. STB resistance sources were found in landraces as well as in modern varieties tested, suggesting the presence of alleles of breeding relevance. The genetic material was genotyped with more than 16 thousand genome-wide polymorphic markers to describe the linkage disequilibrium and genetic structure existing within the panel of genotypes, and a genome-wide association (GWA) study was run to allow the identification of genomic loci involved in STB resistance. High diversity and low genetic structure in the panel allowed high efficiency GWA. The GWA scan detected five major putative QTL for STB resistance, only partially overlapping those already reported in the wheat literature. We report four putative loci for Septoria resistance with no match in previous literature: two highly significant ones on Chr 3A and 5A, and two suggestive ones on Chr 4B and 5B. Markers underlying these QTL explained as much as 10% of the phenotypic variance for disease resistance. We found three cases in which putative QTL for agronomic traits overlapped marker trait association deriving from STB GWA. Our results show that the Ethiopian untapped allelic diversity bears a great value in studying the molecular basis of STB resistance and in breeding for resistance in local and international material.

Genome Wide Association Study to Identify the Genetic Base of Smallholder Farmer Preferences of Durum Wheat Traits.

Smallholder agriculture involves millions of farmers worldwide. A methodical utilization of their traditional knowledge in modern breeding efforts may help the production of locally adapted varieties better addressing their needs. In this study, a combination of participatory approaches, genomics, and quantitative genetics is used to trace the genetic basis of smallholder farmer preferences of durum wheat traits. Two smallholder communities evaluated 400 Ethiopian wheat varieties, mostly landraces, for traits of local interest in two locations in the Ethiopian highlands. For each wheat variety, farmers provided quantitative evaluations of their preference for flowering time, spike morphology, tillering capacity, and overall quality. Ten agronomic and phenology traits were simultaneously measured on the same varieties, providing the means to compare them with farmer traits. The analysis of farmer traits showed that they were partially influenced by gender and location but were repeatable and heritable, in some cases more than metric traits. The durum wheat varieties were genotyped for more than 80,000 SNP markers, and the resulting data was used in a genome wide association (GWA) study providing the molecular dissection of smallholder farmers' choice criteria. We found 124 putative quantitative trait loci (QTL) controlling farmer traits and 30 putative QTL controlling metric traits. Twenty of such QTL were jointly identified by farmer and metric traits. QTL derived from farmer traits were in some cases dependent on gender and location, but were consistent throughout. The results of the GWA study show that smallholder farmers' traditional knowledge can yield QTL eluding metric measurements of phenotypes. We discuss the potential of including farmer evaluations based on traditional knowledge in crop breeding, arguing for the utilization of this untapped resource to develop better adapted genetic materials for local agriculture.

Joining smallholder farmers' traditional knowledge with metric traits to select better varieties of Ethiopian wheat.

Smallholder farming communities face highly variable climatic conditions that threaten locally adapted, low-input agriculture. The benefits of modern crop breeding may fail to reach their fields when broadly adapted genetic materials do not address local requirements. To date, participatory methods only scratched the surface of the exploitability of farmers' traditional knowledge in breeding. In this study, 30 smallholder farmers in each of two locations in Ethiopia provided quantitative evaluations of earliness, spike morphology, tillering capacity and overall quality on 400 wheat genotypes, mostly traditional varieties, yielding altogether 192,000 data points. Metric measurements of ten agronomic traits were simultaneously collected, allowing to systematically break down farmers' preferences on quantitative phenotypes. Results showed that the relative importance of wheat traits differed by gender and location. Farmer traits were variously contributed by metric traits, and could only partially be explained by them. Eventually, farmer trait values were used to produce a ranking of the 400 wheat varieties identifying the trait combinations most desired by farmers. The study scale and methods lead to a better understanding of the quantitative basis of Ethiopian smallholder farmer preference in wheat, broadening the discussion for the future of local, sustainable breeding efforts accommodating farmers' knowledge.