Root system architecture variation among barley (Hordeum vulgare L.) accessions at seedling stage under soil acidity condition.

MAIN CONCLUSION: Soil acidity in Ethiopian highlands impacts barley production, affecting root system architecture. Study on 300 accessions showed significant trait variability, with potential for breeding enhancement. Soil acidity poses a significant challenge to crop production in the highland regions of Ethiopia, particularly impacting barley, a crucial staple crop. This acidity serves as a key stressor affecting the root system architecture (RSA) of this crop. Hence, the objective of this study was to assess the RSA traits variability under acidic soil conditions using 300 barley accessions in a greenhouse experiment. The analysis of variance indicated substantial variations among the accessions across all traits studied. The phenotypic coefficient of variation ranged from 24.4% for shoot dry weight to 11.1% for root length, while the genotypic coefficient variation varied between 18.83 and 9.2% for shoot dry weight and root length, respectively. The broad-sense heritability ranged from 36.7% for leaf area to 69.9% for root length, highlighting considerable heritability among multiple traits. The genetic advances as a percent of the mean ranged from 13.63 to 29.9%, suggesting potential for enhancement of these traits through breeding efforts. Principal component analysis and cluster analysis grouped the genotypes into two major clusters, each containing varying numbers of genotypes with contrasting traits. This diverse group presents an opportunity to access a wide range of potential parent candidates to enhance genetic variablity in breeding programs. The Pearson correlation analysis revealed significant negative associations between root angle (RA) and other RSA traits. This helps indirect selection of accessions for further improvement in soil acidity. In conclusion, this study offers valuable insights into the RSA characteristics of barley in acidic soil conditions, aiding in the development of breeding strategies to enhance crop productivity in acidic soil environments.

Response of common bean (Phaseolus vulgaris L.) to lime and TSP fertilizer under acid soil.

This study was design to investigate responses of four common bean (Polpole and Pantarkin, Deme and Nasir) varieties to four combinations of soil acidity treatments: lime and triple supper phosphate (TSP) fertilizer (+Lime, +TSP, +Lime + TSP, control) by using factorial randomized complete block design with sixteen treatments and three replications. The results of ANOVA showed statistically significant (p < 0.05) differences in interactions of common bean varieties and soil amendments, except shoot fresh weight. The highest root fresh and dry matters weight were obtained from Pantarkin (18.12 g) and Polpole (2.70 g) with interaction of the plot treated with lime and TSP fertilizer, respectively. The highest Leaf area index (6.50 and 5.17), yield (3.84 and 3.33 t ha-1), and hundred seed weight (51.21 and 18.46 g) recorded from Deme and Polpole varieties under buffered plots by lime and TSP fertilizers. The highest phosphorus use efficiency recorded from Deme (0.69) variety. The observed responses indicated improvements of acidity problems through buffering materials (lime) and common bean varieties such as Polpole and Deme which showed better tolerance than Pantarkin and Nasir varieties. These results demonstrate the importance of varietal responses and soil amendments as form of nutrients and buffering acidity for common bean production improvements in acid soil.

Inter- and intraspecific diversity of food legumes among households and communities in Ethiopia.

Smallholders throughout sub-Saharan Africa produce legume crops as sources of food, fodder, and cash income, as well as to improve soil fertility. Ethiopian farmers have developed diverse legume varieties that enable adaptation to changing agroecological and sociocultural conditions. However, over the past several decades, as farm sizes declined and extension services promoted new varieties developed by plant breeders, changes in legume diversity have not been monitored. Based on interviews with smallholder farmers (n = 1296), we investigated the status of inter- and intraspecific legume diversity in major production areas of Ethiopia for five food legumes: common bean (Phaseolus vulgaris L.), field pea (Pisum sativum L.), faba bean (Vicia faba L.), groundnut (Arachis hypogaea L.) and fenugreek (Trigonella foenum-graecum L.). Legume species richness increased with altitude, relative household wealth, and land area planted to legumes. The highest numbers of varieties were found for common bean, followed by field pea, faba bean, groundnut and fenugreek. The average number of varieties planted per household was low (ranging from 1 to 2) and often much lower than the number reported in the same community or zone, which ranged from 2 to 18. For three out of the five species, the number of varieties significantly increased with total land area planted to legumes. Most varieties were rare, planted by less than 1/3 of farmers; however, informants accurately named varieties planted by others in the same community, demonstrating awareness of legume diversity at the community level. Given that the ability to plant multiple legume varieties is limited by land size, policies need to strengthen community-level conservation based on the diverse interests and needs of individual households.

A deconvolutional Bayesian mixing model approach for river basin sediment source apportionment.

Increasing complexity in human-environment interactions at multiple watershed scales presents major challenges to sediment source apportionment data acquisition and analysis. Herein, we present a step-change in the application of Bayesian mixing models: Deconvolutional-MixSIAR (D-MIXSIAR) to underpin sustainable management of soil and sediment. This new mixing model approach allows users to directly account for the 'structural hierarchy' of a river basin in terms of sub-watershed distribution. It works by deconvoluting apportionment data derived for multiple nodes along the stream-river network where sources are stratified by sub-watershed. Source and mixture samples were collected from two watersheds that represented (i) a longitudinal mixed agricultural watershed in the south west of England which had a distinct upper and lower zone related to topography and (ii) a distributed mixed agricultural and forested watershed in the mid-hills of Nepal with two distinct sub-watersheds. In the former, geochemical fingerprints were based upon weathering profiles and anthropogenic soil amendments. In the latter compound-specific stable isotope markers based on soil vegetation cover were applied. Mixing model posterior distributions of proportional sediment source contributions differed when sources were pooled across the watersheds (pooled-MixSIAR) compared to those where source terms were stratified by sub-watershed and the outputs deconvoluted (D-MixSIAR). In the first example, the stratified source data and the deconvolutional approach provided greater distinction between pasture and cultivated topsoil source signatures resulting in a different posterior distribution to non-deconvolutional model (conventional approaches over-estimated the contribution of cultivated land to downstream sediment by 2 to 5 times). In the second example, the deconvolutional model elucidated a large input of sediment delivered from a small tributary resulting in differences in the reported contribution of a discrete mixed forest source. Overall D-MixSIAR model posterior distributions had lower (by ca 25-50%) uncertainty and quicker model run times. In both cases, the structured, deconvoluted output cohered more closely with field observations and local knowledge underpinning the need for closer attention to hierarchy in source and mixture terms in river basin source apportionment. Soil erosion and siltation challenge the energy-food-water-environment nexus. This new tool for source apportionment offers wider application across complex environmental systems affected by natural and human-induced change and the lessons learned are relevant to source apportionment applications in other disciplines.

Effect of brewery spent diatomite sludge on trace metal availability in soil and uptake by wheat crop, and trace metal risk on human health through the consumption of wheat grain.

Soil plays a crucial role in food safety as it determines the composition of food at the beginning of the food chain. However, the quality of soil resources in terms of their potential impact on human health caused by harmful elements is poorly understood in Ethiopia due to lack of reliable and appropriate experimental data. In this study, a field experiment was conducted to evaluate trace metal accumulation in soils amended with brewery spent diatomite sludge (BSDS) in comparison to control, recommended inorganic fertilizers (RIF) and integrated BSDS & RIF (BSDS:RIF). Trace metals uptake by wheat crop and the degree of soil contamination, and human health risk were investigated. BSDS application significantly increased the concentration of trace metals (Cu, Zn, Pb and Ni) in soil compared to that in the control, the RIF, and BSDS:RIF applications. It also significantly increased the concentration of Cu, Zn, Pb and Ni in the wheat grain compared to that in the control and the RIF, but the increase was not significantly different from that in BSDS:RIF amendment. All trace metal concentrations in soil and wheat grain (except Pb in wheat grain) were below the maximum permissible limits in some European countries of agricultural soils, and the maximum permissible limit of FAO/WHO. The degree of soil contamination from each of the treatments was below the maximum acceptable degree of contamination. The Health Risk Index (HRI) was <1 for all metals in all treatments. Thus, we conclude that consumption of wheat grain grown on soils amended with BSDS and BSDS:RIF has no human risks and has low likelihood of human exposure to trace metals.