Projecting the Contribution of Provitamin A Maize Biofortification and Other Nutrition Interventions to the Nutritional Adequacy and Cost of Diets in Rural Zimbabwe.

BACKGROUND: Evidence of the effectiveness of biofortified maize with higher provitamin A (PVA) to address vitamin A deficiency in rural Africa remains scant. OBJECTIVES: This study projects the impact of adopting PVA maize for a diversity of households in an area typical of rural Zimbabwe and models the cost and composition of diets adequate in vitamin A. METHODS: Household-level weighed food records were generated from 30 rural households during a week in April and November 2021. Weekly household intakes were calculated, as well as indicative costs of diets using data from market surveys. The impact of PVA maize adoption was modeled assuming all maize products contained observed vitamin A concentrations. The composition and cost of the least expensive indicative diets adequate in vitamin A were calculated using linear programming. RESULTS: Very few households would reach adequate intake of vitamin A with the consumption of PVA maize. However, from a current situation of 33%, 50%-70% of households were projected to reach ≥50% of their requirements (the target of PVA), even with the modest vitamin A concentrations achieved on-farm (mean of 28.3 µg RAE per 100 g). This proportion would increase if higher concentrations recorded on-station were achieved. The estimated daily costs of current diets (mean ± standard deviation) were USD 1.43 ± 0.59 in the wet season and USD 0.96 ± 0.40 in the dry season. By comparison, optimization models suggest that diets adequate in vitamin A could be achieved at daily costs of USD 0.97 and USD 0.79 in the wet and dry seasons, respectively. CONCLUSIONS: The adoption of PVA maize would bring a substantial improvement in vitamin A intake in rural Zimbabwe but should be combined with other interventions (e.g., diet diversification) to fully address vitamin A deficiency.

Ethylene augments root hypoxia tolerance via growth cessation and reactive oxygen species amelioration.

Flooded plants experience impaired gas diffusion underwater, leading to oxygen deprivation (hypoxia). The volatile plant hormone ethylene is rapidly trapped in submerged plant cells and is instrumental for enhanced hypoxia acclimation. However, the precise mechanisms underpinning ethylene-enhanced hypoxia survival remain unclear. We studied the effect of ethylene pretreatment on hypoxia survival of Arabidopsis (Arabidopsis thaliana) primary root tips. Both hypoxia itself and re-oxygenation following hypoxia are highly damaging to root tip cells, and ethylene pretreatments reduced this damage. Ethylene pretreatment alone altered the abundance of transcripts and proteins involved in hypoxia responses, root growth, translation, and reactive oxygen species (ROS) homeostasis. Through imaging and manipulating ROS abundance in planta, we demonstrated that ethylene limited excessive ROS formation during hypoxia and subsequent re-oxygenation and improved oxidative stress survival in a PHYTOGLOBIN1-dependent manner. In addition, we showed that root growth cessation via ethylene and auxin occurred rapidly and that this quiescence behavior contributed to enhanced hypoxia tolerance. Collectively, our results show that the early flooding signal ethylene modulates a variety of processes that all contribute to hypoxia survival.

The value of volunteer surveillance for the early detection of biological invaders.

Early detection of invaders requires finding small numbers of individuals across large landscapes. It has been argued that the only feasible way to achieve the sampling effort needed for early detection of an invader is to involve volunteer groups (citizen scientists, passive surveyors, etc.). A key concern is that volunteers may have a considerable false-positive and false-negative rate. The question then becomes whether verification of a report from a volunteer is worth the effort. This question is the topic of this paper. Since we are interested in early detection we calculate the Z% upper limit of the one sided confidence interval of the incidence (fraction infected) and use the term maximum expected plausible incidence for this. We compare the maximum plausible incidence when the expert samples on their own, qE∼, and the maximum plausible incidence when the expert only verifies cases reported by the volunteer surveyor to be infected, qV∼. The maximum plausible incidences qE∼ and qV∼. are related as, qV∼=θfp1-θfnqE∼ where θfp and θfn are the false positive and false negative rate of the volunteer surveyor, respectively. We also show that the optimal monitoring programme consists of verifying only the cases reported by the volunteer surveyor if, TXTN<θfp1-θfn, where TN is the time needed for a sample taken by the expert and TX is the time needed for an expert to verify a case reported by a volunteer surveyor. Our results can be used to calculate the maximum plausible incidence of a plant disease based on reports of passive surveyors that have been verified by experts and data from experts sampling on their own. The results can also be used in the development phase of a surveillance project to assess whether including passive surveyor reports is useful in the early detection of exotic invaders.

Identification of traits underpinning good breadmaking performance of wheat grown with reduced nitrogen fertilisation.

BACKGROUND: Nitrogen fertiliser is the major input and cost for wheat production, being required to support the development of the canopy to maximise yield and for the synthesis of the gluten proteins that are necessary for breadmaking. Consequently, current high-yielding cultivars require the use of nitrogen fertilisation levels above the yield optimum to achieve the grain protein content needed for breadmaking. This study aimed to reduce this requirement by identifying traits that allow the use of lower levels of nitrogen fertiliser to produce wheat for breadmaking. RESULTS: A range of commercial wheat genotypes (cultivars) were grown in multiple field trials (six sites over 3 years) in the UK with optimal (200 kg Ha-1 ) and suboptimal (150 kg Ha-1 ) application of nitrogen. Bulked grain samples from four sites per year were milled and white flours were baked using three types of breadmaking process. This identified five cultivars that consistently exhibited good breadmaking quality when grown with the lower nitrogen application. Chemical and biochemical analyses showed that the five cultivars were characterised by exhibiting grain protein deviation (GPD) and high dough elasticity. CONCLUSIONS: It is possible to develop novel types of wheat that exhibit good breadmaking quality by selecting for GPD and high dough strength. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Laboratory phenomics predicts field performance and identifies superior indica haplotypes for early seedling vigour in dry direct-seeded rice.

Seedling vigour is an important agronomic trait and is gaining attention in Asian rice (Oryza sativa) as cultivation practices shift from transplanting to forms of direct seeding. To understand the genetic control of rice seedling vigour in dry direct seeded (aerobic) conditions we measured multiple seedling traits in 684 accessions from the 3000 Rice Genomes (3K-RG) population in both the laboratory and field at three planting depths. Our data show that phenotyping of mesocotyl length in laboratory conditions is a good predictor of field performance. By performing a genome wide association study, we found that the main QTL for mesocotyl length, percentage seedling emergence and shoot biomass are co-located on the short arm of chromosome 7. We show that haplotypes in the indica subgroup from this region can be used to predict the seedling vigour of 3K-RG accessions. The selected accessions may serve as potential donors in genomics-assisted breeding programs.

Functional QTL mapping and genomic prediction of canopy height in wheat measured using a robotic field phenotyping platform.

Genetic studies increasingly rely on high-throughput phenotyping, but the resulting longitudinal data pose analytical challenges. We used canopy height data from an automated field phenotyping platform to compare several approaches to scanning for quantitative trait loci (QTLs) and performing genomic prediction in a wheat recombinant inbred line mapping population based on up to 26 sampled time points (TPs). We detected four persistent QTLs (i.e. expressed for most of the growing season), with both empirical and simulation analyses demonstrating superior statistical power of detecting such QTLs through functional mapping approaches compared with conventional individual TP analyses. In contrast, even very simple individual TP approaches (e.g. interval mapping) had superior detection power for transient QTLs (i.e. expressed during very short periods). Using spline-smoothed phenotypic data resulted in improved genomic predictive abilities (5-8% higher than individual TP prediction), while the effect of including significant QTLs in prediction models was relatively minor (<1-4% improvement). Finally, although QTL detection power and predictive ability generally increased with the number of TPs analysed, gains beyond five or 10 TPs chosen based on phenological information had little practical significance. These results will inform the development of an integrated, semi-automated analytical pipeline, which will be more broadly applicable to similar data sets in wheat and other crops.

Disentangling juxtacrine from paracrine signalling in dynamic tissue.

Prolactin is a major hormone product of the pituitary gland, the central endocrine regulator. Despite its physiological importance, the cell-level mechanisms of prolactin production are not well understood. Having significantly improved the resolution of real-time-single-cell-GFP-imaging, the authors recently revealed that prolactin gene transcription is highly dynamic and stochastic yet shows space-time coordination in an intact tissue slice. However, it still remains an open question as to what kind of cellular communication mediates the observed space-time organization. To determine the type of interaction between cells we developed a statistical model. The degree of similarity between two expression time series was studied in terms of two distance measures, Euclidean and geodesic, the latter being a network-theoretic distance defined to be the minimal number of edges between nodes, and this was used to discriminate between juxtacrine from paracrine signalling. The analysis presented here suggests that juxtacrine signalling dominates. To further determine whether the coupling is coordinating transcription or post-transcriptional activities we used stochastic switch modelling to infer the transcriptional profiles of cells and estimated their similarity measures to deduce that their spatial cellular coordination involves coupling of transcription via juxtacrine signalling. We developed a computational model that involves an inter-cell juxtacrine coupling, yielding simulation results that show space-time coordination in the transcription level that is in agreement with the above analysis. The developed model is expected to serve as the prototype for the further study of tissue-level organised gene expression for epigenetically regulated genes, such as prolactin.

The contribution of fiber components to water absorption of wheat grown in the UK.

BACKGROUND AND OBJECTIVES: The water absorption (WA) of white wheat flour is a major factor affecting processing quality, and millers, therefore, process their wheat to achieve the required level. Although it is likely that WA is determined by the amounts and compositions of three major grain components, starch, protein, and arabinoxylan, the contribution of the latter is not agreed and not recognized in the widely used Farrand equation. FINDINGS: We have measured a range of parameters related to fiber amount and composition and tested the ability of these to improve the prediction of WA using a modified Farrand equation. The addition of a range of single fiber traits improved the prediction of WA from a baseline of 82.98% to a maximum of 86.78%, but inclusion of all fiber traits as PCs resulted in a further improvement to 90%. Inclusion of the PCs also accounted for variation in WA between harvest years. The greatest improvement from inclusion of a single trait was observed with ß-glucan, the inclusion of arabinogalactan peptide (AGP) also resulted in improved prediction of WA. CONCLUSIONS: The study shows that fiber components contribute to variation in WA, including differences between harvest years, but that ß-glucan and AGP have similar or greater impacts than AX. SIGNIFICANCE AND NOVELTY: The study dissects the contributions of AX amount and composition to WA and demonstrates a contribution of b-glucan for the first time.

Accounting for data sparsity when forming spatially coherent zones.

Efficient farm management can be aided by the identification of zones in the landscape. These zones can be informed from different measured variables by ensuring a sense of spatial coherence. Forming spatially coherent zones is an established method in the literature, but has been found to perform poorly when data are sparse. In this paper, we describe the different types of data sparsity and investigate how this impacts the performance of established methods. We introduce a set of methodological advances that address these shortcomings to provide a method for forming spatially coherent zones under data sparsity.

Beyond the one-way ANOVA for 'omics data.

BACKGROUND: With ever increasing accessibility to high throughput technologies, more complex treatment structures can be assessed in a variety of 'omics applications. This adds an extra layer of complexity to the analysis and interpretation, in particular when inferential univariate methods are applied en masse. It is well-known that mass univariate testing suffers from multiplicity issues and although this has been well documented for simple comparative tests, few approaches have focussed on more complex explanatory structures. RESULTS: Two frameworks are introduced incorporating corrections for multiplicity whilst maintaining appropriate structure in the explanatory variables. Within this paradigm, a choice has to be made as to whether multiplicity corrections should be applied to the saturated model, putting emphasis on controlling the rate of false positives, or to the predictive model, where emphasis is on model selection. This choice has implications for both the ranking and selection of the response variables identified as differentially expressed. The theoretical difference is demonstrated between the two approaches along with an empirical study of lipid composition in Arabidopsis under differing levels of salt stress. CONCLUSIONS: Multiplicity corrections have an inherent weakness when the full explanatory structure is not properly incorporated. Although a unifying 'single best' recommendation is not provided, two reasonable alternatives are provided and the applicability of these approaches is discussed for different scenarios where the aims of analysis will differ. The key result is that the point at which multiplicity is incorporated into the analysis will fundamentally change the interpretation of the results, and the choice of approach should therefore be driven by the specific aims of the experiment.

N-terminomics reveals control of Arabidopsis seed storage proteins and proteases by the Arg/N-end rule pathway.

The N-end rule pathway of targeted protein degradation is an important regulator of diverse processes in plants but detailed knowledge regarding its influence on the proteome is lacking. To investigate the impact of the Arg/N-end rule pathway on the proteome of etiolated seedlings, we used terminal amine isotopic labelling of substrates with tandem mass tags (TMT-TAILS) for relative quantification of N-terminal peptides in prt6, an Arabidopsis thaliana N-end rule mutant lacking the E3 ligase PROTEOLYSIS6 (PRT6). TMT-TAILS identified over 4000 unique N-terminal peptides representing c. 2000 protein groups. Forty-five protein groups exhibited significantly increased N-terminal peptide abundance in prt6 seedlings, including cruciferins, major seed storage proteins, which were regulated by Group VII Ethylene Response Factor (ERFVII) transcription factors, known substrates of PRT6. Mobilisation of endosperm α-cruciferin was delayed in prt6 seedlings. N-termini of several proteases were downregulated in prt6, including RD21A. RD21A transcript, protein and activity levels were downregulated in a largely ERFVII-dependent manner. By contrast, cathepsin B3 protein and activity were upregulated by ERFVIIs independent of transcript. We propose that the PRT6 branch of the pathway regulates protease activities in a complex manner and optimises storage reserve mobilisation in the transition from seed to seedling via control of ERFVII action.

Validating a cassava production spatial disaggregation model in sub-Saharan Africa.

Cassava is a staple in the diet of millions of people in sub-Saharan Africa, as it can grow in poor soils with limited inputs and can withstand a wide range of environmental conditions, including drought. Previous studies have shown that the distribution of rural populations is an important predictor of cassava density in sub-Saharan Africa's landscape. Our aim is to explore relationships between the distribution of cassava from the cassava production disaggregation models (CassavaMap and MapSPAM) and rural population density, looking at potential differences between countries and regions. We analysed various properties of cassava cultivations collected from surveys at 69 locations in Côte d'Ivoire and 87 locations in Uganda conducted between February and March 2018. The relationships between the proportion of surveyed land under cassava cultivation and rural population and settlement data were examined using a set of generalized additive models within each country. Information on rural settlements was aggregated around the survey locations at 2, 5 and 10 km circular buffers. The analysis of the original survey data showed no significant correlation between rural population and cassava production in both MapSPAM and CassavaMap. However, as we aggregate settlement buffers around the survey locations using CassavaMap, we find that at a large scale this model does capture large-scale variations in cassava production. Moreover, through our analyses, we discovered country-specific spatial trends linked to areas of higher cassava production. These analyses are useful for validating disaggregation models of cassava production. As the certainty that existing cassava production maps increases, analyses that rely on the disaggregation maps, such as models of disease spread, nutrient availability from cassava with respect to population in a region, etc. can be performed with increased confidence. These benefit social and natural scientists, policymakers and the population in general by ensuring that cassava production estimates are increasingly reliable.

Genetic Diversity in Nitrogen Fertiliser Responses and N Gas Emission in Modern Wheat.

Crops assimilate nitrogen (N) as ammonium via the glutamine synthetase/glutamate synthase (GS/GOGAT) pathway which is of central importance for N uptake and potentially represents a bottle neck for N fertiliser-use efficiency. The aim of this study was to assess whether genetic diversity for N-assimilation capacity exists in wheat and could be exploited for breeding. Wheat plants rapidly, within 6 h, responded to N application with an increase in GS activity. This was not accompanied by an increase in GS gene transcript abundance and a comparison of GS1 and GS2 protein models revealed a high degree of sequence conservation. N responsiveness amongst ten wheat varieties was assessed by measuring GS enzyme activity, leaf tissue ammonium, and by a leaf-disc assay as a proxy for apoplastic ammonia. Based on these data, a high-GS group showing an overall positive response to N could be distinguished from an inefficient, low-GS group. Subsequent gas emission measurements confirmed plant ammonia emission in response to N application and also revealed emission of N2O when N was provided as nitrate, which is in agreement with our current understanding that N2O is a by-product of nitrate reduction. Taken together, the data suggest that there is scope for improving N assimilation capacity in wheat and that further investigations into the regulation and role of GS-GOGAT in NH3 emission is justified. Likewise, emission of the climate gas N2O needs to be reduced, and future research should focus on assessing the nitrate reductase pathway in wheat and explore fertiliser management options.

Changes in organic carbon to clay ratios in different soils and land uses in England and Wales over time.

Realistic targets for soil organic carbon (SOC) concentrations are needed, accounting for differences between soils and land uses. We assess the use of SOC/clay ratio for this purpose by comparing changes over time in (a) the National Soil Inventory of England and Wales, first sampled in 1978-1983 and resampled in 1994-2003, and (b) two long-term experiments under ley-arable rotations on contrasting soils in the East of England. The results showed that normalising for clay concentration provides a more meaningful separation between land uses than changes in SOC alone. Almost half of arable soils in the NSI had degraded SOC/clay ratios (< 1/13), compared with just 5% of permanent grass and woodland soils. Soils with initially large SOC/clay ratios (≥ 1/8) were prone to greater losses of SOC between the two NSI samplings than those with smaller ratios. The results suggest realistic long-term targets for SOC/clay in arable, ley grass, permanent grass and woodland soils are 1/13, 1/10, and > 1/8, respectively. Given the wide range of soils and land uses across England and Wales in the datasets used to test these targets, they should apply across similar temperate regions globally, and at national to sub-regional scales.

Novel molecules and target genes for vegetative heat tolerance in wheat.

To prevent yield losses caused by climate change, it is important to identify naturally tolerant genotypes with traits and related pathways that can be targeted for crop improvement. Here we report on the characterization of contrasting vegetative heat tolerance in two UK bread wheat varieties. Under chronic heat stress, the heat-tolerant cultivar Cadenza produced an excessive number of tillers which translated into more spikes and higher grain yield compared to heat-sensitive Paragon. RNAseq and metabolomics analyses revealed that over 5000 genotype-specific genes were differentially expressed, including photosynthesis-related genes, which might explain the observed ability of Cadenza to maintain photosynthetic rate under heat stress. Around 400 genes showed a similar heat-response in both genotypes. Only 71 genes showed a genotype × temperature interaction. As well as known heat-responsive genes such as heat shock proteins (HSPs), several genes that have not been previously linked to the heat response, particularly in wheat, have been identified, including dehydrins, ankyrin-repeat protein-encoding genes, and lipases. Contrary to primary metabolites, secondary metabolites showed a highly differentiated heat response and genotypic differences. These included benzoxazinoid (DIBOA, DIMBOA), and phenylpropanoids and flavonoids with known radical scavenging capacity, which was assessed via the DPPH assay. The most highly heat-induced metabolite was (glycosylated) propanediol, which is widely used in industry as an anti-freeze. To our knowledge, this is the first report on its response to stress in plants. The identified metabolites and candidate genes provide novel targets for the development of heat-tolerant wheat.

Exploring the effects of land management change on productivity, carbon and nutrient balance: Application of an Ensemble Modelling Approach to the upper River Taw observatory, UK.

Agriculture is challenged to produce healthy food and to contribute to cleaner energy whilst mitigating climate change and protecting ecosystems. To achieve this, policy-driven scenarios need to be evaluated with available data and models to explore trade-offs with robust accounting for the uncertainty in predictions. We developed a novel model ensemble using four complementary state-of-the-art agroecosystems models to explore the impacts of land management change. The ensemble was used to simulate key agricultural and environmental outputs under various scenarios for the upper River Taw observatory, UK. Scenarios assumed (i) reducing livestock production whilst simultaneously increasing the area of arable where it is feasible to cultivate (PG2A), (ii) reducing livestock production whilst simultaneously increasing bioenergy production in areas of the catchment that are amenable to growing bioenergy crops (PG2BE) and (iii) increasing both arable and bioenergy production (PG2A + BE). Our ensemble approach combined model uncertainty using the tower property of expectation and the law of total variance. Results show considerable uncertainty for predicted nutrient losses with different models partitioning the uncertainty into different pathways. Bioenergy crops were predicted to produce greatest yields from Miscanthus in lowland and from SRC-willow (cv. Endurance) in uplands. Each choice of management is associated with trade-offs; e.g. PG2A results in a significant increase of edible calories (6736 Mcal ha-1) but reduced soil C (-4.32 t C ha-1). Model ensembles in the agroecosystem context are difficult to implement due to challenges of model availability and input and output alignment. Despite these challenges, we show that ensemble modelling is a powerful approach for applications such as ours, offering benefits such as capturing structural as well as data uncertainty and allowing greater combinations of variables to be explored. Furthermore, the ensemble provides a robust means for combining uncertainty at different scales and enables us to identify weaknesses in system understanding.

Resolving the identification of weak-flying insects during flight: a coupling between rigorous data processing and biology.

Bioacoustic methods play an increasingly important role for the detection of insects in a range of surveillance and monitoring programmes.Weak-flying insects evade detection because they do not yield sufficient audio information to capture wingbeat and harmonic frequencies. These inaudible insects often pose a significant threat to food security as pests of key agricultural crops worldwide.Automatic detection of such insects is crucial to the future of crop protection by providing critical information to assess the risk to a crop and the need for preventative measures.We describe an experimental set-up designed to derive audio recordings from a range of weak-flying aphids and beetles using an LED array.A rigorous data processing pipeline was developed to extract meaningful features, linked to morphological characteristics, from the audio and harmonic series for six aphid and two beetle species.An ensemble of over 50 bioacoustic parameters was used to achieve species discrimination with a success rate of 80%. The inclusion of the dominant and fundamental frequencies improved prediction between beetles and aphids because of large differences in wingbeat frequencies.At the species level, error rates were minimized when harmonic features were supplemented by features indicative of differences in species' flight energies.

Uncovering Trait Associations Resulting in Maximal Seed Yield in Winter and Spring Oilseed Rape.

Seed yield is a complex trait for many crop species including oilseed rape (OSR) (Brassica napus), the second most important oilseed crop worldwide. Studies have focused on the contribution of distinct factors in seed yield such as environmental cues, agronomical practices, growth conditions, or specific phenotypic traits at the whole plant level, such as number of pods in a plant. However, how female reproductive traits contribute to whole plant level traits, and hence to seed yield, has been largely ignored. Here, we describe the combined contribution of 33 phenotypic traits within a B. napus diversity set population and their trade-offs at the whole plant and organ level, along with their interaction with plant level traits. Our results revealed that both Winter OSR (WOSR) and Spring OSR (SOSR); the two more economically important OSR groups in terms of oil production; share a common dominant reproductive strategy for seed yield. In this strategy, the main inflorescence is the principal source of seed yield, producing a good number of ovules, a large number of long pods with a concomitantly high number of seeds per pod. Moreover, we observed that WOSR opted for additional reproductive strategies than SOSR, presenting more plasticity to maximise seed yield. Overall, we conclude that OSR adopts a key strategy to ensure maximal seed yield and propose an ideal ideotype highlighting crucial phenotypic traits that could be potential targets for breeding.

The potential for soybean to diversify the production of plant-based protein in the UK.

Soybean (Glycine max) offers an important source of plant-based protein. Currently much of Europe's soybean is imported, but there are strong economic and agronomic arguments for boosting local production. Soybean is grown in central and eastern Europe but is less favoured in the North due to climate. We conducted field trials across three seasons and two sites in the UK to test the viability of early-maturing soybean varieties and used the data from these trials to calibrate and validate the Rothamsted Landscape Model. Once validated, the model was used to predict the probability soybean would mature and the associated yield for 26 sites across the UK based on weather data under current, near-future (2041-60) and far-future (2081-2100) climate. Two representative concentration pathways, a midrange mitigation scenario (RCP4.5) and a high emission scenario (RCP8.5) were also explored. Our analysis revealed that under current climate early maturing varieties will mature in the south of the UK, but the probability of failure increases with latitude. Of the 26 sites considered, only at one did soybean mature for every realisation. Predicted expected yields ranged between 1.39 t ha-1 and 1.95 t ha-1 across sites. Under climate change these varieties are likely to mature as far north as southern Scotland. With greater levels of CO2, yield is predicted to increase by as much as 0.5 t ha-1 at some sites in the far future, but this is tempered by other effects of climate change meaning that for most sites no meaningful increase in yield is expected. We conclude that soybean is likely to be a viable crop in the UK and for similar climates at similar latitudes in Northern Europe in the future but that for yields to be economically attractive for local markets, varieties must be chosen to align with the growing season.

Plant Available Zinc Is Influenced by Landscape Position in the Amhara Region, Ethiopia.

Zinc (Zn) is an important element determining the grain quality of staple food crops and deficient in many Ethiopian soils. However, farming systems are highly variable in Ethiopia due to different soil types and landscape cropping positions. Zinc availability and uptake by plants from soil and fertilizer sources are governed by the retention and release potential of the soil, usually termed as adsorption and desorption, respectively. The aim of this study was to characterize the amount of plant available Zn at different landscape positions. During the 2018/19 cropping season, adsorption-desorption studies were carried out on soil samples collected from on-farm trials conducted at Aba Gerima, Debre Mewi and Markuma in the Amhara Region. In all locations and landscape positions, adsorption and desorption increased with increasing Zn additions. The amount of adsorption and desorption was highly associated with the soil pH, the soil organic carbon concentration and cation exchange capacity, and these factors are linked to landscape positions. The Freundlich isotherm fitted very well to Zn adsorption (r2 0.87-0.99) and desorption (r2 0.92-0.99), while the Langmuir isotherm only fitted to Zn desorption (r2 0.70-0.93). Multiple regression models developed by determining the most influential soil parameters for Zn availability could be used to inform Zn fertilizer management strategies for different locations and landscape positions in this region, and thereby improve plant Zn use efficiency.