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.

The tricot approach: an agile framework for decentralized on-farm testing supported by citizen science. A retrospective

Matching crop varieties to their target use context and user preferences is a challenge faced by many plant breeding programs serving smallholder agriculture. Numerous participatory approaches proposed by CGIAR and other research teams over the last four decades have attempted to capture farmers' priorities/preferences and crop variety field performance in representative growing environments through experimental trials with higher external validity. Yet none have overcome the challenges of scalability, data validity and reliability, and difficulties in capturing socio-economic and environmental heterogeneity. Building on the strengths of these attempts, we developed a new data-generation approach, called triadic comparison of technology options (tricot). Tricot is a decentralized experimental approach supported by crowdsourced citizen science. In this article, we review the development, validation, and evolution of the tricot approach, through our own research results and reviewing the literature in which tricot approaches have been successfully applied. The first results indicated that tricot-aggregated farmer-led assessments contained information with adequate validity and that reliability could be achieved with a large sample. Costs were lower than current participatory approaches. Scaling the tricot approach into a large on-farm testing network successfully registered specific climatic effects of crop variety performance in representative growing environments. Tricot's recent application in plant breeding networks in relation to decision-making has (i) advanced plant breeding lines recognizing socio-economic heterogeneity, and (ii) identified consumers' preferences and market demands, generating alternative breeding design priorities. We review lessons learned from tricot applications that have enabled a large scaling effort, which should lead to stronger decision-making in crop improvement and increased use of improved varieties in smallholder agriculture.

Genetic gains in early maturing maize hybrids developed by the International Maize and Wheat Improvement Center in Southern Africa during 2000-2018

Genetic gain estimation in a breeding program provides an opportunity to monitor breeding efficiency and genetic progress over a specific period. The present study was conducted to (i) assess the genetic gains in grain yield of the early maturing maize hybrids developed by the International Maize and Wheat Improvement Center (CIMMYT) Southern African breeding program during the period 2000-2018 and (ii) identify key agronomic traits contributing to the yield gains under various management conditions. Seventy-two early maturing hybrids developed by CIMMYT and three commercial checks were assessed under stress and non-stress conditions across 68 environments in seven eastern and southern African countries through the regional on-station trials. Genetic gain was estimated as the slope of the regression of grain yield and other traits against the year of first testing of the hybrid in the regional trial. The results showed highly significant (p< 0.01) annual grain yield gains of 118, 63, 46, and 61 kg ha-1 year-1 under optimum, low N, managed drought, and random stress conditions, respectively. The gains in grain yield realized in this study under both stress and non-stress conditions were associated with improvements in certain agronomic traits and resistance to major maize diseases. The findings of this study clearly demonstrate the significant progress made in developing productive and multiple stress-tolerant maize hybrids together with other desirable agronomic attributes in CIMMYT's hybrid breeding program.

Redesigning crop varieties to win the race between climate change and food security

Climate change poses daunting challenges to agricultural production and food security. Rising temperatures, shifting weather patterns, and more frequent extreme events have already demonstrated their effects on local, regional, and global agricultural systems. Crop varieties that withstand climate-related stresses and are suitable for cultivation in innovative cropping systems will be crucial to maximize risk avoidance, productivity, and profitability under climate-changed environments. We surveyed 588 expert stakeholders to predict current and novel traits that may be essential for future pearl millet, sorghum, maize, groundnut, cowpea, and common bean varieties, particularly in sub-Saharan Africa. We then review the current progress and prospects for breeding three prioritized future-essential traits for each of these crops. Experts predict that most current breeding priorities will remain important, but that rates of genetic gain must increase to keep pace with climate challenges and consumer demands. Importantly, the predicted future-essential traits include innovative breeding targets that must also be prioritized; for example, (1) optimized rhizosphere microbiome, with benefits for P, N, and water use efficiency, (2) optimized performance across or in specific cropping systems, (3) lower nighttime respiration, (4) improved stover quality, and (5) increased early vigor. We further discuss cutting-edge tools and approaches to discover, validate, and incorporate novel genetic diversity from exotic germplasm into breeding populations with unprecedented precision, accuracy, and speed. We conclude that the greatest challenge to developing crop varieties to win the race between climate change and food security might be our innovativeness in defining and boldness to breed for the traits of tomorrow.

Innovative approaches to integrating gender into conventional maize breeding: lessons from the Seed Production Technology for Africa project

The integration of gender concerns in crop breeding programs aims to improve the suitability and appeal of new varieties to both women and men, in response to concerns about unequal adoption of improved seed. However, few conventional breeding programs have sought to center social inclusion concerns. This community case study documents efforts to integrate gender into the maize-focused Seed Production Technology for Africa (SPTA) project using innovation history analysis drawing on project documents and the authors' experiences. These efforts included deliberate exploration of potential gendered impacts of project technologies and innovations in the project's approach to variety evaluation, culminating in the use of decentralized on-farm trials using the tricot approach. Through this case study, we illustrate the power of active and respectful collaborations between breeders and social scientists, spurred by donor mandates to address gender and social inclusion. Gender integration in this case was further facilitated by open-minded project leaders and allocation of funding for gender research. SPTA proved to be fertile ground for experimentation and interdisciplinary collaboration around gender and maize breeding, and has provided proof of concept for larger breeding projects seeking to integrate gender considerations.

Data-driven approaches can harness crop diversity to address heterogeneous needs for breeding products

This perspective describes the opportunities and challenges of data-driven approaches for crop diversity management (genebanks and breeding) in the context of agricultural research for sustainable development in the Global South. Data-driven approaches build on larger volumes of data and flexible analyses that link different datasets across domains and disciplines. This can lead to more information-rich management of crop diversity, which can address the complex interactions between crop diversity, production environments, and socioeconomic heterogeneity and help to deliver more suitable portfolios of crop diversity to users with highly diverse demands. We describe recent efforts that illustrate the potential of data-driven approaches for crop diversity management. A continued investment in this area should fill remaining gaps and seize opportunities, including i) supporting genebanks to play a more active role in linking with farmers using data-driven approaches; ii) designing low-cost, appropriate technologies for phenotyping; iii) generating more and better gender and socioeconomic data; iv) designing information products to facilitate decision-making; and v) building more capacity in data science. Broad, well-coordinated policies and investments are needed to avoid fragmentation of such capacities and achieve coherence between domains and disciplines so that crop diversity management systems can become more effective in delivering benefits to farmers, consumers, and other users of crop diversity.

Genetic Variation of Zinc and Iron Concentration in Normal, Provitamin A and Quality Protein Maize under Stress and Non-Stress Conditions

The negative impacts of zinc (Zn) and iron (Fe) deficiency due to over-reliance on monotonous cereal-based diets are well-documented. Increasing micronutrient densities in maize is currently among top breeders' priorities. Here, 77 single-cross Zn-enhanced hybrids with normal, provitamin A and quality protein maize genetic backgrounds were evaluated together with seven checks for grain Zn and Fe concentration and agronomic traits under optimum, low nitrogen (N) and managed drought conditions. Results showed a fairly wide variability for grain Zn (10.7-57.8 mg kg^-1) and Fe (7.1-58.4 mg kg^-1) concentration amongst the hybrids, across management conditions. Notable differences in Zn concentration were observed between the Zn-enhanced quality protein maize (QPM) (31.5 mg kg^-1), Zn-enhanced provitamin A maize (28.5 mg kg^-1), Zn-enhanced normal maize (26.0 mg kg^-1) and checks (22.9 mg kg^-1). Although checks showed the lowest micronutrient concentration, they were superior in grain yield (GY) performance, followed by Zn-enhanced normal hybrids. Genotypes grown optimally had higher micronutrient concentrations than those grown under stress. Genotype × environment interaction (G × E) was significant (p ≤ 0.01) for GY, grain Zn and Fe concentration, hence micronutrient-rich varieties could be developed for specific environments. Furthermore, correlation between grain Zn and Fe was positive and highly significant (r = 0.97; p ≤ 0.01) suggesting the possibility of improving these traits simultaneously. However, the negative correlation between GY and grain Zn (r = -0.44; p ≤ 0.01) and between GY and grain Fe concentration (r = -0.43; p ≤ 0.01) was significant but of moderate magnitude, suggesting slight dilution effects. Therefore, development of high yielding and micronutrient-dense maize cultivars is possible, which could reduce the highly prevalent micronutrient deficiency in sub-Saharan Africa (SSA).

Genome-wide association studies of grain yield and quality traits under optimum and low-nitrogen stress in tropical maize (Zea mays L.)

Genome-wide association study (GWAS) demonstrated that multiple genomic regions influence grain quality traits under nitrogen-starved soils. Using genomic prediction, genetic gains can be improved through selection for grain quality traits. Soils in sub-Saharan Africa are nitrogen deficient due to low fertilizer use and inadequate soil fertility management practices. This has resulted in a significant yield gap for the major staple crop maize, which is undermining nutritional security and livelihood sustainability across the region. Dissecting the genetic basis of grain protein, starch and oil content under nitrogen-starved soils can increase our understanding of the governing genetic systems and improve the efficacy of future breeding schemes. An association mapping panel of 410 inbred lines and four bi-parental populations were evaluated in field trials in Kenya and South Africa under optimum and low nitrogen conditions and genotyped with 259,798 SNP markers. Genetic correlations demonstrated that these populations may be utilized to select higher performing lines under low nitrogen stress. Furthermore, genotypic, environmental and GxE variations in nitrogen-starved soils were found to be significant for oil content. Broad sense heritabilities ranged from moderate (0.18) to high (0.86). Under low nitrogen stress, GWAS identified 42 SNPs linked to grain quality traits. These significant SNPs were associated with 51 putative candidate genes. Linkage mapping identified multiple QTLs for the grain quality traits. Under low nitrogen conditions, average prediction accuracies across the studied genotypes were higher for oil content (0.78) and lower for grain yield (0.08). Our findings indicate that grain quality traits are polygenic and that using genomic selection in maize breeding can improve genetic gain. Furthermore, the identified genomic regions and SNP markers can be utilized for selection to improve maize grain quality traits.

Gender inclusivity through maize breeding in Africa: A review of the issues and options for future engagement

With the prioritization of social inclusion in agricultural development, donors and research centers have shown growing interest in gender-intentional varietal development and delivery. Breeding maize varieties that respond to gender-based differences in trait preferences now represents a central objective of maize R&D in the CGIAR and elsewhere. Drawing on literature on gender and maize seed adoption, variety preferences, and seed system constraints, we take stock of knowns and unknowns related to gender-responsive and gender-intentional maize breeding. While recent research on farmers' variety preferences across crops has yielded insights into gender-based differences, we find that evidence of gender-differentiated preferences for maize varieties remains inconclusive. Ultimately, we identify several research priorities to support gender-intentional maize breeding, including a more nuanced understanding of gender relations in maize production and maize seed decision-making, new and more gender-responsive approaches to measuring farmer preferences and seed demand more broadly, and research to address operational challenges in gender-intentional breeding. We close by identifying some institutional constraints to achieving impact through gender-intentional maize breeding.

Genotypic variation in maize (Zea mays) influences rates of soil organic matter mineralization and gross nitrification

Agricultural management practices that increase soil organic matter (SOM), such as no-tillage (NT) with crop residue retention, together with crop varieties best able to source nutrients from SOM, may help reverse soil degradation and improve soil nutrient supply and uptake by plants in low-input environments of tropical and subtropical areas. Here, we screened germplasm representing genetic diversity within tropical maize breeding programmes in relation to shaping SOM mineralization. Then we assessed effects of contrasting genotypes on nitrification rates, and genotype-by-management history interactions on these rates. SOM-C mineralization and gross nitrification rates varied under different maize genotypes. Cumulative SOM-C mineralization increased with root diameter but decreased with increasing root length. Strong influences of management history and interaction of maize genotype-by-management history on nitrification were observed. Overall, nitrification rates were higher in NT soil with residue retention. We propose that there is potential to exploit genotypic variation in traits associated with SOM mineralization and nitrification within breeding programmes. Root diameter and length could be used as proxies for root-soil interactions driving these processes. Development of maize varieties with enhanced ability to mineralize SOM combined with NT and residue retention to build/replenish SOM could be key to sustainable production.

Beat the stress: breeding for climate resilience in maize for the tropical rainfed environments

Intensive public sector breeding efforts and public-private partnerships have led to the increase in genetic gains, and deployment of elite climate-resilient maize cultivars for the stress-prone environments in the tropics. Maize (Zea mays L.) plays a critical role in ensuring food and nutritional security, and livelihoods of millions of resource-constrained smallholders. However, maize yields in the tropical rainfed environments are now increasingly vulnerable to various climate-induced stresses, especially drought, heat, waterlogging, salinity, cold, diseases, and insect pests, which often come in combinations to severely impact maize crops. The International Maize and Wheat Improvement Center (CIMMYT), in partnership with several public and private sector institutions, has been intensively engaged over the last four decades in breeding elite tropical maize germplasm with tolerance to key abiotic and biotic stresses, using an extensive managed stress screening network and on-farm testing system. This has led to the successful development and deployment of an array of elite stress-tolerant maize cultivars across sub-Saharan Africa, Asia, and Latin America. Further increasing genetic gains in the tropical maize breeding programs demands judicious integration of doubled haploidy, high-throughput and precise phenotyping, genomics-assisted breeding, breeding data management, and more effective decision support tools. Multi-institutional efforts, especially public-private alliances, are key to ensure that the improved maize varieties effectively reach the climate-vulnerable farming communities in the tropics, including accelerated replacement of old/obsolete varieties.

Line × tester analysis of maize grain yield under acid and non-acid soil conditions

Soil acidity has received less attention than other biophysical stresses such as drought and low N, despite accounting for a considerable reduction in maize (Zea mays L.) productivity in many parts of southern Africa. The line × tester mating design was used to determine the general combining ability (GCA) for grain yield of 14 maize inbred lines and the specific combining ability (SCA) of their corresponding crosses. Thirty-three single-cross hybrids were evaluated under acid and optimum soils across 11 environments over three seasons. Across environments, mean grain yield reduction ranged from 11 to 37% due to low pH. Additive gene action was more important than nonadditive gene action for grain yield under both soil conditions. Tester GCA effects were larger for grain yield than GCA effects of lines and SCA effects of crosses for both soil conditions. Tester GCA effects were less sensitive to environmental fluctuations than line GCA effects and SCA effects of crosses. Cross combinations with desirable SCA effects for grain yield were associated with high per se grain yield, which suggests that SCA was a good predictor of grain yield in this study. These crosses consisted of good × good and good × poor general combiners, which indicates that GCA was a good predictor of grain yield. Therefore, priority should be given for yield selection in progenies and hybridization of specific crosses with desirable SCA when breeding acid-soil-tolerant maize.

Nitrogen rate impacts on tropical maize nitrogen use efficiency and soil nitrogen depletion in eastern and southern Africa

Sub-Saharan Africa is facing food security challenges due, in part, to decades of soil nitrogen (N) depletion. Applying N fertilizer could increase crop yields and replenish soil N pools. From 2010 to 2015, field experiments conducted in Embu and Kiboko, Kenya and Harare, Zimbabwe investigated yield and N uptake response of six maize (Zea mays L.) hybrids to four N fertilizer rates (0 to 160 kg N ha^-1) in continuous maize production systems. The N recovery efficiency (NRE), cumulative N balance, and soil N content in the upper 0.9 m of soil following the final harvest were determined at each N rate. Plant and soil responses to N fertilizer applications did not differ amongst hybrids. Across locations and N rates, NRE ranged from 0.4 to 1.8 kg kg^-1. Higher NRE values in Kiboko and Harare occurred at lower post-harvest soil inorganic N levels. The excessively high NRE value of 1.8 kg kg^-1 at 40 kg N ha^-1 in Harare suggested that maize hybrids deplete soil inorganic N most at low N rates. Still, negative cumulative N balances indicated that inorganic soil N depletion occurred at all N rates in Embu and Harare (up to - 193 and - 167 kg N ha^-1, respectively) and at the 40 kg N ha^-1 rate in Kiboko (- 72 kg N ha^-1). Overall, maize N uptake exceeded fertilizer N applied and so, while yields increased, soil N pools were not replenished, especially at low total soil N levels (< 10,000 kg N ha^-1 in top 0.9 m).

Evaluating Maize Genotype Performance under Low Nitrogen Conditions Using RGB UAV Phenotyping Techniques

Maize is the most cultivated cereal in Africa in terms of land area and production, but low soil nitrogen availability often constrains yields. Developing new maize varieties with high and reliable yields using traditional crop breeding techniques in field conditions can be slow and costly. Remote sensing has become an important tool in the modernization of field-based high-throughput plant phenotyping (HTPP), providing faster gains towards the improvement of yield potential and adaptation to abiotic and biotic limiting conditions. We evaluated the performance of a set of remote sensing indices derived from red-green-blue (RGB) images along with field-based multispectral normalized difference vegetation index (NDVI) and leaf chlorophyll content (SPAD values) as phenotypic traits for assessing maize performance under managed low-nitrogen conditions. HTPP measurements were conducted from the ground and from an unmanned aerial vehicle (UAV). For the ground-level RGB indices, the strongest correlations to yield were observed with hue, greener green area (GGA), and a newly developed RGB HTPP index, NDLab (normalized difference Commission Internationale de I´Edairage (CIE)Lab index), while GGA and crop senescence index (CSI) correlated better with grain yield from the UAV. Regarding ground sensors, SPAD exhibited the closest correlation with grain yield, notably increasing in its correlation when measured in the vegetative stage. Additionally, we evaluated how different HTPP indices contributed to the explanation of yield in combination with agronomic data, such as anthesis silking interval (ASI), anthesis date (AD), and plant height (PH). Multivariate regression models, including RGB indices (R2 > 0.60), outperformed other models using only agronomic parameters or field sensors (R2 > 0.50), reinforcing RGB HTPP's potential to improve yield assessments. Finally, we compared the low-N results to the same panel of 64 maize genotypes grown under optimal conditions, noting that only 11% of the total genotypes appeared in the highest yield producing quartile for both trials. Furthermore, we calculated the grain yield loss index (GYLI) for each genotype, which showed a large range of variability, suggesting that low-N performance is not necessarily exclusive of high productivity in optimal conditions.

Identification of donors for low-nitrogen stress with maize lethal necrosis (MLN) tolerance for maize breeding in sub-Saharan Africa

After drought, a major challenge to smallholder farmers in sub-Saharan Africa is low-fertility soils with poor nitrogen (N)-supplying capacity. Many challenges in this region need to be overcome to create a viable fertilizer market. An intermediate solution is the development of maize varieties with an enhanced ability to take up or utilize N in severely depleted soils, and to more efficiently use the small amounts of N that farmers can supply to their crops. Over 400 elite inbred lines from seven maize breeding programs were screened to identify new sources of tolerance to low-N stress and maize lethal necrosis (MLN) for introgression into Africa-adapted elite germplasm. Lines with high levels of tolerance to both stresses were identified. Lines previously considered to be tolerant to low-N stress ranked in the bottom 10% under low-N confirming the need to replace these lines with new donors identified in this study. The lines that performed best under low-N yielded about 0. 5 Mg ha-1 (20%) more in testcross combinations than some widely used commercial parent lines such as CML442 and CML395. This is the first large scale study to identify maize inbred lines with tolerance to low-N stress and MLN in eastern and southern Africa.

Genome-Wide Association Mapping and Genomic Prediction Analyses Reveal the Genetic Architecture of Grain Yield and Flowering Time Under Drought and Heat Stress Conditions in Maize

Drought stress (DS) is a major constraint to maize yield production. Heat stress (HS) alone and in combination with DS are likely to become the increasing constraints. Association mapping and genomic prediction (GP) analyses were conducted in a collection of 300 tropical and subtropical maize inbred lines to reveal the genetic architecture of grain yield and flowering time under well-watered (WW), DS, HS, and combined DS and HS conditions. Out of the 381,165 genotyping-by-sequencing SNPs, 1549 SNPs were significantly associated with all the 12 trait-environment combinations, the average PVE (phenotypic variation explained) by these SNPs was 4.33%, and 541 of them had a PVE value greater than 5%. These significant associations were clustered into 446 genomic regions with a window size of 20 Mb per region, and 673 candidate genes containing the significantly associated SNPs were identified. In addition, 33 hotspots were identified for 12 trait-environment combinations and most were located on chromosomes 1 and 8. Compared with single SNP-based association mapping, the haplotype-based associated mapping detected fewer number of significant associations and candidate genes with higher PVE values. All the 688 candidate genes were enriched into 15 gene ontology terms, and 46 candidate genes showed significant differential expression under the WW and DS conditions. Association mapping results identified few overlapped significant markers and candidate genes for the same traits evaluated under different managements, indicating the genetic divergence between the individual stress tolerance and the combined drought and HS tolerance. The GP accuracies obtained from the marker-trait associated SNPs were relatively higher than those obtained from the genome-wide SNPs for most of the target traits. The genetic architecture information of the grain yield and flowering time revealed in this study, and the genomic regions identified for the different trait-environment combinations are useful in accelerating the efforts on rapid development of the stress-tolerant maize germplasm through marker-assisted selection and/or genomic selection.

Nitrogen fertilizer rate increases plant uptake and soil availability of essential nutrients in continuous maize production in Kenya and Zimbabwe

Low fertilizer application rates for several decades have depleted soil nutrients in Sub-Saharan Africa (SSA) and contributed to relatively stagnant maize (Zea mays L.) yields. As maize is a staple crop, nutrient depletion has resulted in major food insecurity. While one potential solution is to apply more nitrogen (N) fertilizer, previous studies in SSA have found maize yield responses to be variable, likely because N is often not the only limiting nutrient. This study aimed to determine the impact of consecutive N fertilizer applications on plant uptake and available soil reserves of non-N nutrients. Maize was grown continuously in 3 sites that were representative of the ecosystem variability found in East/Southern Africa (Embu, Kenya; Kiboko, Kenya; Harare, Zimbabwe) at 4 different N fertilizer rates (0-160 kg N ha^-1) from 2010 to 2015. Following the final season, grain, stover, and soil (sampled at different depths to 0.9 m) samples were analyzed for essential plant nutrients. Nitrogen fertilizer increased plant uptake of P, S, Cu, and Zn by up to 280%, 320%, 420%, and 210%, respectively, showing potential for mitigating non-N nutrient deficiencies in 2 of the 3 sites. Cumulatively, however, there was a net negative effect of higher N rates on the P, K, and S soil-plant balances in all sites and on the Mn and Cu soil-plant balance in Kiboko, indicating that applying N fertilizer depletes non-N soil nutrients. While N fertilizer enhances the uptake of non-N nutrients, a balanced application of multiple essential nutrients is needed to sustainably increase yields in SSA.

Developing and deploying climate-resilient maize varieties in the developing world

In sub-Saharan Africa (SSA) and Asia maize yields remain variable due to climate shocks. Over the past decade extensive progress has been made on the development and delivery of climate-resilient maize. In 2016 over 70000 metric tonnes of drought-tolerant maize seed was commercialized in 13 countries in SSA, benefiting an estimated 53 million people. Significant progress is also being made with regard to the development and deployment of elite heat-tolerant maize varieties in South Asia. Increased genetic gain in grain yield under stress-prone environments, coupled with faster replacement of old/obsolete varieties, through intensive engagement with seed companies is essential to protect maize crops grown by smallholders from the changing climates in SSA and Asia.

Translating High-Throughput Phenotyping into Genetic Gain

Inability to efficiently implement high-throughput field phenotyping is increasingly perceived as a key component that limits genetic gain in breeding programs. Field phenotyping must be integrated into a wider context than just choosing the correct selection traits, deployment tools, evaluation platforms, or basic data-management methods. Phenotyping means more than conducting such activities in a resource-efficient manner; it also requires appropriate trial management and spatial variability handling, definition of key constraining conditions prevalent in the target population of environments, and the development of more comprehensive data management, including crop modeling. This review will provide a wide perspective on how field phenotyping is best implemented. It will also outline how to bridge the gap between breeders and 'phenotypers' in an effective manner.

Phenotyping Conservation Agriculture Management Effects on Ground and Aerial Remote Sensing Assessments of Maize Hybrids Performance in Zimbabwe

In the coming decades, Sub-Saharan Africa (SSA) faces challenges to sustainably increase food production while keeping pace with continued population growth. Conservation agriculture (CA) has been proposed to enhance soil health and productivity to respond to this situation. Maize is the main staple food in SSA. To increase maize yields, the selection of suitable genotypes and management practices for CA conditions has been explored using remote sensing tools. They may play a fundamental role towards overcoming the traditional limitations of data collection and processing in large scale phenotyping studies. We present the result of a study in which Red-Green-Blue (RGB) and multispectral indexes were evaluated for assessing maize performance under conventional ploughing (CP) and CA practices. Eight hybrids under different planting densities and tillage practices were tested. The measurements were conducted on seedlings at ground level (0.8 m) and from an unmanned aerial vehicle (UAV) platform (30 m), causing a platform proximity effect on the images resolution that did not have any negative impact on the performance of the indexes. Most of the calculated indexes (Green Area (GA) and Normalized Difference Vegetation Index (NDVI)) were significantly affected by tillage conditions increasing their values from CP to CA. Indexes derived from the RGB-images related to canopy greenness performed better at assessing yield differences, potentially due to the greater resolution of the RGB compared with the multispectral data, although this performance was more precise for CP than CA. The correlations of the multispectral indexes with yield were improved by applying a soil-mask derived from a NDVI threshold with the aim of corresponding pixels with vegetation. The results of this study highlight the applicability of remote sensing approaches based on RGB images to the assessment of crop performance and hybrid choice.

High-Throughput Phenotyping of Canopy Cover and Senescence in Maize Field Trials Using Aerial Digital Canopy Imaging

In the crop breeding process, the use of data collection methods that allow reliable assessment of crop adaptation traits, faster and cheaper than those currently in use, can significantly improve resource use efficiency by reducing selection cost and can contribute to increased genetic gain through improved selection efficiency. Current methods to estimate crop growth (ground canopy cover) and leaf senescence are essentially manual and/or by visual scoring, and are therefore often subjective, time consuming, and expensive. Aerial sensing technologies offer radically new perspectives for assessing these traits at low cost, faster, and in a more objective manner. We report the use of an unmanned aerial vehicle (UAV) equipped with an RGB camera for crop cover and canopy senescence assessment in maize field trials. Aerial-imaging-derived data showed a moderately high heritability for both traits with a significant genetic correlation with grain yield. In addition, in some cases, the correlation between the visual assessment (prone to subjectivity) of crop senescence and the senescence index, calculated from aerial imaging data, was significant. We concluded that the UAV-based aerial sensing platforms have great potential for monitoring the dynamics of crop canopy characteristics like crop vigor through ground canopy cover and canopy senescence in breeding trial plots. This is anticipated to assist in improving selection efficiency through higher accuracy and precision, as well as reduced time and cost of data collection.

Comparative Performance of Ground vs. Aerially Assessed RGB and Multispectral Indices for Early-Growth Evaluation of Maize Performance under Phosphorus Fertilization

Low soil fertility is one of the factors most limiting agricultural production, with phosphorus deficiency being among the main factors, particularly in developing countries. To deal with such environmental constraints, remote sensing measurements can be used to rapidly assess crop performance and to phenotype a large number of plots in a rapid and cost-effective way. We evaluated the performance of a set of remote sensing indices derived from Red-Green-Blue (RGB) images and multispectral (visible and infrared) data as phenotypic traits and crop monitoring tools for early assessment of maize performance under phosphorus fertilization. Thus, a set of 26 maize hybrids grown under field conditions in Zimbabwe was assayed under contrasting phosphorus fertilization conditions. Remote sensing measurements were conducted in seedlings at two different levels: at the ground and from an aerial platform. Within a particular phosphorus level, some of the RGB indices strongly correlated with grain yield. In general, RGB indices assessed at both ground and aerial levels correlated in a comparable way with grain yield except for indices a* and u*, which correlated better when assessed at the aerial level than at ground level and Greener Area (GGA) which had the opposite correlation. The Normalized Difference Vegetation Index (NDVI) evaluated at ground level with an active sensor also correlated better with grain yield than the NDVI derived from the multispectral camera mounted in the aerial platform. Other multispectral indices like the Soil Adjusted Vegetation Index (SAVI) performed very similarly to NDVI assessed at the aerial level but overall, they correlated in a weaker manner with grain yield than the best RGB indices. This study clearly illustrates the advantage of RGB-derived indices over the more costly and time-consuming multispectral indices. Moreover, the indices best correlated with GY were in general those best correlated with leaf phosphorous content. However, these correlations were clearly weaker than against grain yield and only under low phosphorous conditions. This work reinforces the effectiveness of canopy remote sensing for plant phenotyping and crop management of maize under different phosphorus nutrient conditions and suggests that the RGB indices are the best option.

Rapid breeding and varietal replacement are critical to adaptation of cropping systems in the developing world to climate change

Plant breeding is a key mechanism for adaptation of cropping systems to climate change. Much discussion of breeding for climate change focuses on genes with large effects on heat and drought tolerance, but phenology and stress tolerance are highly polygenic. Adaptation will therefore mainly result from continually adjusting allele frequencies at many loci through rapid-cycle breeding that delivers a steady stream of incrementally improved cultivars. This will require access to elite germplasm from other regions, shortened breeding cycles, and multi-location testing systems that adequately sample the target population of environments. The objective of breeding and seed systems serving smallholder farmers should be to ensure that they use varieties developed in the last 10 years. Rapid varietal turnover must be supported by active dissemination of new varieties, and active withdrawal of obsolete ones. Commercial seed systems in temperate regions achieve this through competitive seed markets, but in the developing world, most crops are not served by competitive commercial seed systems, and many varieties date from the end of the Green Revolution (the late 1970s, when the second generation of modern rice and wheat varieties had been widely adopted). These obsolete varieties were developed in a climate different than today's, placing farmers at risk. To reduce this risk, a strengthened breeding system is needed, with freer international exchange of elite varieties, short breeding cycles, high selection intensity, wide-scale phenotyping, and accurate selection supported by genomic technology. Governments need to incentivize varietal release and dissemination systems to continuously replace obsolete varieties.

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Continuous turnover of crop varieties is critical to climate change adaptation.

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Farmers in commercial temperate cropping systems, with rapid varietal replacement, are best protected.

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Breeding programs need unfettered access to elite varieties from regions now facing their future climate.

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Rapid and effective breeding cycles are needed to deliver climate change adaptation in real time.

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Farmers in the developing world are at risk from slow breeding and varietal replacement cycles.

A Novel Remote Sensing Approach for Prediction of Maize Yield Under Different Conditions of Nitrogen Fertilization

Maize crop production is constrained worldwide by nitrogen (N) availability and particularly in poor tropical and subtropical soils. The development of affordable high-throughput crop monitoring and phenotyping techniques is key to improving maize cultivation under low-N fertilization. In this study several vegetation indices (VIs) derived from Red-Green-Blue (RGB) digital images at the leaf and canopy levels are proposed as low-cost tools for plant breeding and fertilization management. They were compared with the performance of the normalized difference vegetation index (NDVI) measured at ground level and from an aerial platform, as well as with leaf chlorophyll content (LCC) and other leaf composition and structural parameters at flowering stage. A set of 10 hybrids grown under five different nitrogen regimes and adequate water conditions were tested at the CIMMYT station of Harare (Zimbabwe). Grain yield and leaf N concentration across N fertilization levels were strongly predicted by most of these RGB indices (with R (2)~ 0.7), outperforming the prediction power of the NDVI and LCC. RGB indices also outperformed the NDVI when assessing genotypic differences in grain yield and leaf N concentration within a given level of N fertilization. The best predictor of leaf N concentration across the five N regimes was LCC but its performance within N treatments was inefficient. The leaf traits evaluated also seemed inefficient as phenotyping parameters. It is concluded that the adoption of RGB-based phenotyping techniques may significantly contribute to the progress of plant breeding and the appropriate management of fertilization.

Factors preventing the performance of oxygen isotope ratios as indicators of grain yield in maize

This paper provides new insights into source-sink relationships and transpiration processes which will eventually help to interpret δ (18) O as a genotype selection and ecophysiological tool for maize adaptation to drought. Oxygen isotope composition (δ(18)O) has been proposed as a phenotyping tool to integrate leaf transpiration in C4 crops, such as maize. Within this context we hypothesize that δ(18)O in leaves may reflect primarily environmental and genetic variability in evaporative processes, but that this signal may become dampened in transit from source to sink tissues. The aim of this study was to assess the relative importance of transpirative or translocation-related factors affecting δ(18)O in plant tissues of maize. We performed two water regime experiments, one with two varieties under semi-controlled conditions, and another in the field with 100 genotypes during two consecutive years. The δ(18)O in organic matter at the leaf base was strongly correlated with the δ(18)O in stem water, indicating that it could be a good proxy for source water in extensive samplings. Compared to leaves, we observed an (18)O depletion in silks and grains, but not in stem-soluble organic matter. We interpret this as evidence of exchange with unenriched water from source to sink, but mainly occurring within sink tissues. Although grain yield (GY) and physiological variables did not show clear intra-trial patterns against δ(18)O, the only tissues that correlated with GY in the linear regression approach were that of silks, giving an insight of evapotranspirative demand during female flowering and thus of potential maize lines that are better adapted to drought. This finding will eventually help to interpret δ(18)O as a genotype selection and ecophysiological tool for the adaption of maize and other crops to drought, offering insight into source-sink relationships and transpiration processes.

Metabolite Profiles of Maize Leaves in Drought, Heat, and Combined Stress Field Trials Reveal the Relationship between Metabolism and Grain Yield

The development of abiotic stress-resistant cultivars is of premium importance for the agriculture of developing countries. Further progress in maize (Zea mays) performance under stresses is expected by combining marker-assisted breeding with metabolite markers. In order to dissect metabolic responses and to identify promising metabolite marker candidates, metabolite profiles of maize leaves were analyzed and compared with grain yield in field trials. Plants were grown under well-watered conditions (control) or exposed to drought, heat, and both stresses simultaneously. Trials were conducted in 2010 and 2011 using 10 tropical hybrids selected to exhibit diverse abiotic stress tolerance. Drought stress evoked the accumulation of many amino acids, including isoleucine, valine, threonine, and 4-aminobutanoate, which has been commonly reported in both field and greenhouse experiments in many plant species. Two photorespiratory amino acids, glycine and serine, and myoinositol also accumulated under drought. The combination of drought and heat evoked relatively few specific responses, and most of the metabolic changes were predictable from the sum of the responses to individual stresses. Statistical analysis revealed significant correlation between levels of glycine and myoinositol and grain yield under drought. Levels of myoinositol in control conditions were also related to grain yield under drought. Furthermore, multiple linear regression models very well explained the variation of grain yield via the combination of several metabolites. These results indicate the importance of photorespiration and raffinose family oligosaccharide metabolism in grain yield under drought and suggest single or multiple metabolites as potential metabolic markers for the breeding of abiotic stress-tolerant maize.

Field high-throughput phenotyping: the new crop breeding frontier

Constraints in field phenotyping capability limit our ability to dissect the genetics of quantitative traits, particularly those related to yield and stress tolerance (e.g., yield potential as well as increased drought, heat tolerance, and nutrient efficiency, etc.). The development of effective field-based high-throughput phenotyping platforms (HTPPs) remains a bottleneck for future breeding advances. However, progress in sensors, aeronautics, and high-performance computing are paving the way. Here, we review recent advances in field HTPPs, which should combine at an affordable cost, high capacity for data recording, scoring and processing, and non-invasive remote sensing methods, together with automated environmental data collection. Laboratory analyses of key plant parts may complement direct phenotyping under field conditions. Improvements in user-friendly data management together with a more powerful interpretation of results should increase the use of field HTPPs, therefore increasing the efficiency of crop genetic improvement to meet the needs of future generations.

Field high-throughput phenotyping: the new crop breeding frontier

Constraints in field phenotyping capability limit our ability to dissect the genetics of quantitative traits, particularly those related to yield and stress tolerance (e.g., yield potential as well as increased drought, heat tolerance, and nutrient efficiency, etc.). The development of effective field-based high-throughput phenotyping platforms (HTPPs) remains a bottleneck for future breeding advances. However, progress in sensors, aeronautics, and high-performance computing are paving the way. Here, we review recent advances in field HTPPs, which should combine at an affordable cost, high capacity for data recording, scoring and processing, and non-invasive remote sensing methods, together with automated environmental data collection. Laboratory analyses of key plant parts may complement direct phenotyping under field conditions. Improvements in user-friendly data management together with a more powerful interpretation of results should increase the use of field HTPPs, therefore increasing the efficiency of crop genetic improvement to meet the needs of future generations.

Dissecting maize productivity: ideotypes associated with grain yield under drought stress and well-watered conditions

To increase maize (Zea mays L.) yields in drought-prone environments and offset predicted maize yield losses under future climates, the development of improved breeding pipelines using a multi-disciplinary approach is essential. Elucidating key growth processes will provide opportunities to improve drought breeding progress through the identification of key phenotypic traits, ideotypes, and donors. In this study, we tested a large set of tropical and subtropical maize inbreds and single cross hybrids under reproductive stage drought stress and well-watered conditions. Patterns of biomass production, senescence, and plant water status were measured throughout the crop cycle. Under drought stress, early biomass production prior to anthesis was important for inbred yield, while delayed senescence was important for hybrid yield. Under well-watered conditions, the ability to maintain a high biomass throughout the growing cycle was crucial for inbred yield, while a stay-green pattern was important for hybrid yield. While new quantitative phenotyping tools such as spectral reflectance (Normalized Difference Vegetation Index, NDVI) allowed for the characterization of growth and senescence patterns as well as yield, qualitative measurements of canopy senescence were also found to be associated with grain yield.

Phenotyping for abiotic stress tolerance in maize

The ability to quickly develop germplasm having tolerance to several complex polygenic inherited abiotic and biotic stresses combined is critical to the resilience of cropping systems in the face of climate change. Molecular breeding offers the tools to accelerate cereal breeding; however, suitable phenotyping protocols are essential to ensure that the much-anticipated benefits of molecular breeding can be realized. To facilitate the full potential of molecular tools, greater emphasis needs to be given to reducing the within-experimental site variability, application of stress and characterization of the environment and appropriate phenotyping tools. Yield is a function of many processes throughout the plant cycle, and thus integrative traits that encompass crop performance over time or organization level (i.e. canopy level) will provide a better alternative to instantaneous measurements which provide only a snapshot of a given plant process. Many new phenotyping tools based on remote sensing are now available including non-destructive measurements of growth-related parameters based on spectral reflectance and infrared thermometry to estimate plant water status. Here we describe key field phenotyping protocols for maize with emphasis on tolerance to drought and low nitrogen.

Does susceptibility to heat stress confound screening for drought tolerance in rice?

Drought affected rice areas are predicted to double by the end of this century, demanding greater tolerance in widely adapted mega-varieties. Progress on incorporating better drought tolerance has been slow due to lack of appropriate phenotyping protocols. Furthermore, existing protocols do not consider the effect of drought and heat interactions, especially during the critical flowering stage, which could lead to false conclusion about drought tolerance. Screening germplasm and mapping-populations to identify quantitative trait loci (QTL)/candidate genes for drought tolerance is usually conducted in hot dry seasons where water supply can be controlled. Hence, results from dry season drought screening in the field could be confounded by heat stress, either directly on heat sensitive processes such as pollination or indirectly by raising tissue temperature through reducing transpirational cooling under water deficit conditions. Drought-tolerant entries or drought-responsive candidate genes/QTL identified from germplasm highly susceptible to heat stress during anthesis/flowering have to be interpreted with caution. During drought screening, germplasm tolerant to water stress but highly susceptible to heat stress has to be excluded during dry and hot season screening. Responses to drought and heat stress in rice are compared and results from field and controlled environment experiments studying drought and heat tolerance and their interaction are discussed.

Linking drought-resistance mechanisms to drought avoidance in upland rice using a QTL approach: progress and new opportunities to integrate stomatal and mesophyll responses

The advent of saturated molecular maps promised rapid progress towards the improvement of crops for genetically complex traits like drought resistance via analysis of quantitative trait loci (QTL). Progress with the identification of QTLs for drought resistance-related traits in rice is summarized here with the emphasis on a mapping population of a cross between drought-resistant varieties Azucena and Bala. Data which have used root morphological traits and indicators of drought avoidance in field-grown plants are reviewed, highlighting problems and uncertainties with the QTL approach. The contribution of root-growth QTLs to drought avoidance appears small in the experiments so far conducted, and the limitations of screening methodologies and the involvement of shoot-related mechanisms of drought resistance are studied. When compared to Azucena, Bala has been observed to have highly sensitive stomata, does not roll its leaves readily, has a greater ability to adjust osmotically, slows growth more rapidly when droughted and has a lower water-use efficiency. It is also a semi-dwarf variety and hence has a different canopy structure. There is a need to clarify the contribution of the shoot to drought resistance from the level of the biochemistry of photosynthesis through stomatal behaviour and leaf anatomy to canopy architecture. Recent advances in studying the physical and biochemical processes related to water use and drought stress offer the opportunity to advance a more holistic understanding of drought resistance. These include the potential use of infrared thermal imaging to study energy balance, integrated and online stable isotope analysis to dissect processes involved in carbon dioxide fixation and water evaporation, and leaf fluorescence to monitor photosynthesis and photochemical quenching. Justification and a strategy for this integrated approach is described, which has relevance to the study of drought resistance in most crops.

Experience with the Molteno long tube implant

Dissatisfaction with other forms of treatment in the neovascular and other 'difficult' glaucomas led the authors to use the Molteno long tube implant. This paper resulted from a review of the results obtained in 30 cases over the past four years. The patients fell naturally into the two groups of neovascular and non-neovascular glaucomas. The eyes with neovascular glaucoma had an implant used early in the disease process, while the eyes with non-neovascular glaucoma tended to have the implant used as a last resort, after the failure of conventional techniques. An overall success rate of 63 per cent was found and this could be subdivided into success rates of 50 per cent for the non-neovascular group and of 75 per cent for the neovascular group. These findings probably reflect the late or early use of the implant in the disease process. The results confirm the authors' clinical impression that the Molteno long tube implant is a useful tool in the management of these glaucomas, and that for optimal results it should be considered early in the condition.

Iridocyclo-retraction in glaucoma secondary to essential iris atrophy

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Temperature-sensitive mutants of vesicular stomatitis virus: in vitro studies of virion-associated polymerase

The temperature dependence of the virion-associated polymerase activity of six temperature-sensitive (ts) mutants of vesicular stomatitis virus (tsW10, 11, 14, 16B, 28, and 29) has been examined in vitro and compared to the heat-resistant parent (HR). The polymerase of five of the mutants (tsW10, 11, 14, 16B, and 28) appears to be significantly more ts than that of HR. Because certain pairs of these five mutants can complement each other's in vitro polymerase activity, it appears that in vitro some components involved in the polymerase of one virion can be utilized by another virion. Examination of 19 revertants of tsW11 and tsW16B which had regained their ability to replicate at 38 C showed that their in vitro polymerase activity had also become less ts. Furthermore, it was found that the pairs of mutants which showed in vitro complementation of polymerase activity at 38 C were those which had shown complementation in yielding infectious progeny in mixedly infected cells. These two observations suggest that the ts behavior of the in vitro polymerase activity of the five mutants is related to their inability to replicate at the nonpermissive temperature.

"Sunflower cataract" in Wilson's disease

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Cutaneous leishmaniasis (Oriental sore). A case with corneal involvement

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