Communicating uncertainties in spatial predictions of grain micronutrient concentration

The concentration of micronutrients in staple crops varies spatially. Quantitative information about this can help in designing efficient interventions to address micronutrient deficiency. Concentration of a micronutrient in a staple crop can be mapped from limited samples, but the resulting statistical predictions are uncertain. Decision makers must understand this uncertainty to make robust use of spatial information, but this is a challenge due to the difficulties in communicating quantitative concepts to a general audience. We proposed strategies to communicate uncertain information and present a systematic evaluation and comparison in the form of maps. We proposed testing five methods to communicate the uncertainty about the conditional mean grain concentration of an essential micronutrient, selenium (Se). Evaluation of the communication methods was done through a questionnaire by eliciting stakeholder opinions about the usefulness of the methods of communicating uncertainty. We found significant differences in how participants responded to the different methods. In particular, there was a preference for methods based on the probability that concentrations are below or above a nutritionally significant threshold compared with general measures of uncertainty such as the prediction interval. There was no evidence that methods which used pictographs or calibrated verbal phrases to support the interpretation of probabilities made a different impression than probability alone, as judged from the responses to interpretative questions, although these approaches were ranked most highly when participants were asked to put the methods in order of preference

Eliciting experts’ tacit models for the interpretation of soil information, an example from the evaluation of potential benefits from conservation agriculture

© 2020 The Authors We examined a procedure to elicit the tacit models underlying expert opinions on environmental factors that affect the absolute yield benefits expected from the adoption of conservation agriculture (CA) practices in southern Africa. The procedure is based on expert evaluation of the expected improvement in crop yield on adoption of CA in a particular scenario or ‘state’, a state being a specified set of soil conditions captured by a standard soil profile description from a specified agroecological zone (AEZ) of Zambia. Mixed groups of scientists including soil scientists, agronomists, agricultural economists and other environmental scientists, facilitated by experienced senior researchers, were presented with multiple subsets each of three states, and asked to rank the states in each subset with respect to expected yield improvement under CA. The groups of scientists could be divided into two sets. Each set comprised two groups, and the agreement on ranking between groups within each set was larger than would be expected if the ranking were done at random. For both sets of groups the ranking could be modelled with respect to properties of the soil, and the contrast between AEZ. The models revealed two contrasting groups of conceptual assumptions. One group broadly expected larger absolute yield improvements from conservation agriculture in settings where water is most likely to be limiting and the carbon status of the soil is poor. By contrast, the other group expected larger improvements where water was less likely to be limiting. These contrasting views are relevant to current discussions as to whether conservation agriculture, which is promoted as a ‘climate smart’ strategy for cropping, is sufficiently attractive for smallholder producers in conditions where crop production is already challenging, and whether the potential benefits in areas where water availability is not of itself a common limitation should be considered. The elicited models could be translated directly into competing hypotheses to be tested, perhaps in on-farm trials of conservation agriculture practices over contrasting soils in the different AEZ. The method, based on modelling the ranking process, could be of more general interest for the elicitation of expert opinion about complex soil, crop and environmental systems

Reversible and irreversible root phenotypic plasticity under fluctuating soil physical conditions

Roots grow in a highly heterogeneous physical environment due to the spatial complexity of soil structure. Thereby, the root growth zone repeatedly experiences soil physical stress such as hypoxia or increased penetration resistance. To mimic the highly variable physical environment surrounding the root growth zone, we subjected pea and wheat seedlings to periodic soil physical stress. One day of soil hypoxia or increased penetration resistance reduced root elongation rate of both species by at least 20 %. Upon stress release, root elongation rate of pea could recover within one day, while no such recovery occurred in wheat. Similarly, the diameter of the root elongation zone in pea increased by 15 % and 20 % due to hypoxia and increased penetration resistance, respectively, but decreased again once the stresses were released. In contrast, the diameter of the elongation zone of wheat roots started to decrease with the onset of soil physical stress and this trend continued upon stress release. Hence, root responses to short-term soil physical stress were reversible in pea and irreversible in wheat, indicating reversible and irreversible root phenotypic plasticity, respectively. This suggests that strategies to cope with periodic soil physical stress may vary among species. The differentiation between reversible and irreversible phenotypic plasticity is crucial to advance our understanding on soil exploration, resource acquisition, whole plant growth, and ultimately crop yield formation on structured soil

Assessing the residual benefit of soil-applied zinc on grain zinc nutritional quality of maize grown under contrasting soil types in Malawi.

A proper understanding of the residual value of zinc (Zn) is necessary for sustainable biofortification of food crops. This study aimed to establish the extent to which application of Zn at the national rate, plus two experimentally elevated rates, in one year provided any benefit to plant yield and nutritional quality in the following growing season. Residual effects of soil-applied Zn on grain Zn concentration and uptake were estimated by an experiment in which maize was grown in successive seasons at two agricultural research stations in Malawi, with Zn applied to the soil in the first season but not the second. At each site two common soil types were used: Lixisols and Vertisols. The study used three Zn fertilizer rates of 1, 30 and 90 kg Zn ha -1 applied to the soil in the previous cropping season, arranged in a randomized complete block design (RCBD) with 10 replications at each experimental site. At harvest, maize grain yield and Zn concentration in grain and stover were measured; Zn uptake by maize grain and stover were determined and Zn harvest index was calculated. Effects on grain yield and Zn uptake by the crop were assessed in relation to residual Zn fertilizer and soil type. Maize grain yield on plots in the second season where 30 kg Zn ha -1 had been applied exceeded that on second season plots where 1 kg Zn ha -1 had been applied by 25%. The grain Zn concentration and Zn uptake in the second season after fertilizer application were larger by 13% and 30% respectively on the plots which had received 30 kg Zn ha -1 than those which had received 1 kg Zn ha -1 . There was no evidence that applying Zn at 90 kg Zn ha -1 resulted in larger crop yield, grain Zn concentration, or Zn uptake the second year after application than was seen in plots the second year after application of 30 kg Zn ha -1 . The magnitude of the benefits attributed to residual effects of soil-applied Zn did not depend on soil type. Conclusively, the residual effects of 30 kg ha -1 of soil-applied Zn in the preceding season benefited the subsequent maize compared to the national recommendation of 1 kg Zn ha -1 . The benefits of larger applications of Zn than the current national recommendations should be considered across at least two seasons and for different crops

Longitudinal analysis of a long-Term conservation agriculture experiment in Malawi and lessons for future experimental design

Resilient cropping systems are required to achieve food security in the presence of climate change, and so several long-Term conservation agriculture (CA) trials have been established in southern Africa-one of them at the Chitedze Agriculture Research Station in Malawi in 2007. The present study focused on a longitudinal analysis of 10 years of data from the trial to better understand the joint effects of variations between the seasons and particular contrasts among treatments on yield of maize. Of further interest was the variability of treatment responses in time and space and the implications for design of future trials with adequate statistical power. The analysis shows treatment differences of the mean effect which vary according to cropping season. There was a strong treatment effect between rotational treatments and other treatments and a weak effect between intercropping and monocropping. There was no evidence for an overall advantage of systems where residues are retained (in combination with direct seeding or planting basins) over conventional management with respect to maize yield. A season effect was evident although the strong benefit of rotation in El Niño season was also reduced, highlighting the strong interaction between treatment and climatic conditions. The power analysis shows that treatment effects of practically significant magnitude may be unlikely to be detected with just four replicates, as at Chitedze, under either a simple randomised control trial or a factorial experiment. Given logistical and financial constraints, it is important to design trials with fewer treatments but more replicates to gain enough statistical power and to pay attention to the selection of treatments to given an informative outcome

Soil and landscape factors influence geospatial variation in maize grain zinc concentration in Malawi

Dietary zinc (Zn) deficiency is widespread globally, and in particular among people in sub-Saharan Africa (SSA). In Malawi, dietary sources of Zn are dominated by maize and spatially dependent variation in grain Zn concentration, which will affect dietary Zn intake, has been reported at distances of up to ~ 100 km. The aim of this study was to identify potential soil properties and environmental covariates which might explain this longer-range spatial variation in maize grain Zn concentration. Data for maize grain Zn concentrations, soil properties, and environmental covariates were obtained from a spatially representative survey in Malawi (n = 1600 locations). Labile and non-labile soil Zn forms were determined using isotopic dilution methods, alongside conventional agronomic soil analyses. Soil properties and environmental covariates as potential predictors of the concentration of Zn in maize grain were tested using a priori expert rankings and false discovery rate (FDR) controls within the linear mixed model (LMM) framework that informed the original survey design. Mean and median grain Zn concentrations were 21.8 and 21.5 mg kg−1, respectively (standard deviation 4.5; range 10.0–48.1). A LMM for grain Zn concentration was constructed for which the independent variables: soil pH(water), isotopically exchangeable Zn (ZnE), and diethylenetriaminepentaacetic acid (DTPA) extractable Zn (ZnDTPA) had predictive value (p < 0.01 in all cases, with FDR controlled at < 0.05). Downscaled mean annual temperature also explained a proportion of the spatial variation in grain Zn concentration. Evidence for spatially dependent variation in maize grain Zn concentrations in Malawi is robust within the LMM framework used in this study, at distances of up to ~ 100 km. Spatial predictions from this LMM provide a basis for further investigation of variations in the contribution of staple foods to Zn nutrition, and where interventions to increase dietary Zn intake (e.g. biofortification) might be most effective. Other soil and landscape factors influencing spatially dependent variation in maize grain Zn concentration, along with factors operating over shorter distances such as choice of crop variety and agronomic practices, require further exploration beyond the scope of the design of this survey

Uncovering the hidden half of plants using new advances in root phenotyping

Major increases in crop yield are required to keep pace with population growth and climate change. Improvements to the architecture of crop roots promise to deliver increases in water and nutrient use efficiency but profiling the root phenome (i.e., its structure and function) represents a major bottleneck. We describe how advances in imaging and sensor technologies are making root phenomic studies possible. However, methodological advances in acquisition, handling and processing of the resulting ‘big-data’ is becoming increasingly important. Advances in automated image analysis approaches such as Deep Learning promise to transform the root phenotyping landscape. Collectively, these innovations are helping drive the selection of the next-generation of crops to deliver real world impact for ongoing global food security efforts