SUMMARY The phenotypic analysis of root system growth is important to inform efforts to enhance plant resource acquisition from soils; however, root phenotyping remains challenging because of the opacity of soil, requiring systems that facilitate root system visibility and image acquisition. Previously reported systems require costly or bespoke materials not available in most countries, where breeders need tools to select varieties best adapted to local soils and field conditions. Here, we report an affordable soil‐based growth (rhizobox) and imaging system to phenotype root development in glasshouses or shelters. All components of the system are made from locally available commodity components, facilitating the adoption of this affordable technology in low‐income countries. The rhizobox is large enough (approximately 6000 cm2 of visible soil) to avoid restricting vertical root system growth for most if not all of the life cycle, yet light enough (approximately 21 kg when filled with soil) for routine handling. Support structures and an imaging station, with five cameras covering the whole soil surface, complement the rhizoboxes. Images are acquired via the Phenotiki sensor interface, collected, stitched and analysed. Root system architecture (RSA) parameters are quantified without intervention. The RSAs of a dicot species (Cicer arietinum, chickpea) and a monocot species (Hordeum vulgare, barley), exhibiting contrasting root systems, were analysed. Insights into root system dynamics during vegetative and reproductive stages of the chickpea life cycle were obtained. This affordable system is relevant for efforts in Ethiopia and other low‐ and middle‐income countries to enhance crop yields and climate resilience sustainably.

Plants have evolved many mechanisms to increase the chance of gene dispersal mainly through pollen and environmental factors play an important role. Understanding the mechanism behind gene dispersal is therefore crucial in the correct evaluation of the use of genetically modified crops for cultivation. In this paper we address the question of weather nutrient availability for the female affects the outcome of pollen competition between two pollen donor cultivars of Cucumis sativus. We do this by carrying out controlled crosses of female plants grown at three different nutrient levels. We separated the effect of a specific donor from the effect of pollen tube growth rate by using reversed crosses of fast and slow pollen. Our results show that female effects on siring ability vary with nutrient level. Pollen with a high pollen tube growth rate was more successful when nutrient availability for the female was high. This could be the result of selection on the female to adjust preference according to environmental circumstances. Pollen tube growth rate was measured under nutrient rich circumstances, thus high performers possessed traits adapted to a nutrient rich situation. Due to trade-off effects, these traits might not be advantageous in poor environments. Instead, individuals adapted to low nutrient circumstances will have a higher pollen tube growth rate. If siring ability varies with the environment of the recipient plant, this means that assessments of gene flow must account for this variation and include both pollen donors and recipient plants subjected to a range of environmental circumstances. In risk assessments of transgenic plants, plants are often kept under experimental, homogenous conditions. If our results also apply to other species, estimates of gene flow under constant conditions may be misleading. Selection on siring ability and female preference have fundamental effects on gene flow and need to be considered in risk assessments of transgenic plants.

The analysis of root system growth, root phenotyping, is important to inform efforts to enhance plant resource acquisition from soils. However, root phenotyping remains challenging due to soil opacity and requires systems that optimize root visibility and image acquisition. Previously reported systems require costly and bespoke materials not available in most countries, where breeders need tools to select varieties best adapted to local soils and field conditions. Here, we present an affordable soil-based growth container (rhizobox) and imaging system to phenotype root development in greenhouses or shelters. All components of the system are made from commodity components, locally available worldwide to facilitate the adoption of this affordable technology in low-income countries. The rhizobox is large enough (~6000 cm2 visible soil) to not restrict vertical root system growth for at least seven weeks after sowing, yet light enough (~21 kg) to be routinely moved manually. Support structures and an imaging station, with five cameras covering the whole soil surface, complement the rhizoboxes. Images are acquired via the Phenotiki sensor interface, collected, stitched and analysed. Root system architecture (RSA) parameters are quantified without intervention. RSA of a dicot (chickpea, Cicer arietinum L.) and a monocot (barley, Hordeum vulgare L.) species, which exhibit contrasting root systems, were analysed. The affordable system is relevant for efforts in Ethiopia and elsewhere to enhance yields and climate resilience of chickpea and other crops for improved food security.Significance StatementAn affordable system to characterize root system architecture of soil-grown plants was developed. Using commodity components, this will enable local efforts world-wide to breed for enhanced root systems.

Septoria tritici blotch, caused by the fungus Zymoseptoria titici, poses serious and persistent challenges to wheat cultivation in Ethiopia and worldwide. Deploying resistant cultivars is a major component of controlling septoria tritici blotch (STB). Thus, the objective of this study was to elucidate the genomic architecture of STB resistance in an association panel of 178 bread wheat genotypes. The association panel was phenotyped for STB resistance, phenology, yield, and yield-related traits in three locations for 2 years. The panel was also genotyped for single nucleotide polymorphism (SNP) markers using the genotyping-by-sequencing (GBS) method, and a total of 7,776 polymorphic SNPs were used in the subsequent analyses. Marker-trait associations were also computed using a genome association and prediction integrated tool (GAPIT). The study then found that the broad-sense heritability for STB resistance ranged from 0.58 to 0.97 and 0.72 to 0.81 at the individual and across-environment levels, respectively, indicating the presence of STB resistance alleles in the association panel. Population structure and principal component analyses detected two sub-groups with greater degrees of admixture. A linkage disequilibrium (LD) analysis in 338,125 marker pairs also detected the existence of significant (p ≤ 0.01) linkage in 27.6% of the marker pairs. Specifically, in all chromosomes, the LD between SNPs declined within 2.26–105.62 Mbp, with an overall mean of 31.44 Mbp. Furthermore, the association analysis identified 53 loci that were significantly (false discovery rate, FDR, <0.05) associated with STB resistance, further pointing to 33 putative quantitative trait loci (QTLs). Most of these shared similar chromosomes with already published Septoria resistance genes, which were distributed across chromosomes 1B, 1D, 2A, 2B, 2D, 3A,3 B, 3D, 4A, 5A, 5B, 6A, 7A, 7B, and 7D. However, five of the putative QTLs identified on chromosomes 1A, 5D, and 6B appeared to be novel. Dissecting the detected loci on IWGSC RefSeq Annotation v2.1 revealed the existence of disease resistance-associated genes in the identified QTL regions that are involved in plant defense responses. These putative QTLs explained 2.7–13.2% of the total phenotypic variation. Seven of the QTLs (R2 = 2.7–10.8%) for STB resistance also co-localized with marker-trait associations (MTAs) for agronomic traits. Overall, this analysis reported on putative QTLs for adult plant resistance to STB and some important agronomic traits. The reported and novel QTLs have been identified previously, indicating the potential to improve STB resistance by pyramiding QTLs by marker-assisted selection.

Durum wheat is an important cereal grown in Ethiopia, a country which is also its center for genetic diversity. Yellow (stripe) rust caused by Puccinia striiformis fsp tritici is one of the most devastating diseases threatening Ethiopian wheat production. To identify sources of genetic resistance and combat this pathogen, we conducted a genome wide association study of yellow rust resistance on 300 durum wheat accessions comprising 261 landraces and 39 cultivars. The accessions were evaluated for their field resistance using a modified Cobb scale at Meraro, Kulumsa and Chefe Donsa in the 2015 and 2016 main growing seasons. Analysis of the 35K Axiom Array genotyping data of the panel resulted in a total of 8,797 polymorphic SNPs of which 7,093 were used in subsequent analyses. Population structure analysis suggested two groups in which the cultivars clearly stood out separately from the landraces. Eleven SNPs significantly associated with yellow rust resistance were identified on four chromosomes (1A, 1B, 2B, and 5A) which defined at least five genomic loci. Six of the SNPs were consistently identified on chromosome 1B singly at each and combined overall environments which explained 62.6–64.0% of the phenotypic variation (R2). Resistant allele frequency ranged from 14.0–71.0%; Zooming in to the identified resistance loci revealed the presence of disease resistance related genes involved in the plant defense system such as the ABC transporter gene family, disease resistance protein RPM1 (NBS-LRR class), Receptor kinases and Protein kinases. This study has provided SNPs for tracking the loci associated with yellow rust resistance and a diversity panel which can be used for association study of other agriculturally important traits in durum wheat.