The nutritional safety of wheat-based food products is compromised by the presence of the processing contaminant acrylamide. Reduction of the key acrylamide precursor, free (soluble, non-protein) asparagine, in wheat grain can be achieved through crop management strategies, but such strategies have not been fully developed. We ran two field trials with 12 soft (biscuit) wheat varieties and different nitrogen, sulfur, potassium, and phosphorus fertilizer combinations. Our results indicated that a nitrogen-to-sulfur ratio of 10:1 kg/ha was sufficient to prevent large increases in free asparagine, whereas withholding potassium or phosphorus alone did not cause increases in free asparagine when sulfur was applied. Multispectral measurements of plants in the field were able to predict the free asparagine content of grain with an accuracy of 71%, while a combination of multispectral, fluorescence, and morphological measurements of seeds could distinguish high free asparagine grain from low free asparagine grain with an accuracy of 86%. The acrylamide content of biscuits correlated strongly with free asparagine content and with color measurements, indicating that agronomic strategies to decrease free asparagine would be effective and that quality control checks based on product color could eliminate high acrylamide biscuit products.

Wheat ( Triticum aestivum L.) is a major source of nutrients for populations across the globe, but the amino acid composition of wheat grain does not provide optimal nutrition. The nutritional value of wheat grain is limited by low concentrations of lysine (the most limiting essential amino acid) and high concentrations of free asparagine (precursor to the processing contaminant acrylamide). There are currently few available solutions for asparagine reduction and lysine biofortification through breeding. In this study, we investigated the genetic architecture controlling grain free amino acid composition and its relationship to other traits in a Robigus × Claire doubled haploid population. Multivariate analysis of amino acids and other traits showed that the two groups are largely independent of one another, with the largest effect on amino acids being from the environment. Linkage analysis of the population allowed identification of quantitative trait loci (QTL) controlling free amino acids and other traits, and this was compared against genomic prediction methods. Following identification of a QTL controlling free lysine content, wheat pangenome resources facilitated analysis of candidate genes in this region of the genome. These findings can be used to select appropriate strategies for lysine biofortification and free asparagine reduction in wheat breeding programs.

ABSTRACT CONTEXT Global cocoa production is largely concentrated in West Africa where over 70% of cocoa is produced. Here, cocoa farming is largely a rain-fed, low-input system with low average yields, which are expected to reduce due to climate change. With increasing demand, there is a need to increase global cocoa production whilst avoiding deforestation and expansion to croplands. Thus, it is important to know how much additional cocoa can be produced on existing farmland, and what factors determine this potential for increased yield.OBJECTIVE The objective was to estimate the cocoa yield gap in Ghana. This was done by calculating water-limited potential yields for cocoa as the upper limit that can be achieved on existing land in a rain-fed system using a crop model and comparing this with farmer-based yields.METHODS We used CASE2, a physiological crop growth and production model for cocoa to simulate water-limited yields in 93 cocoa farm locations in Ghana. Yield gaps were calculated as the difference between simulated water-limited yield and average farmer yields. Both absolute and relative yield gaps were calculated. We then related the absolute and relative yield gap to environmental and management factors using mixed-effects models.RESULTS AND CONCLUSIONS There were considerable yield gaps on all cocoa farms. Absolute yield gaps ranged from 2,223 to 6,071 kg/ha across sites (mean=4,577 kg/ha) and relative yield gaps from 49 to 98% (mean= 86%). Thus, current farmer yields are only 14% of the potential under rain-fed conditions. Mixed-effects models showed that the absolute yield gaps were larger at sites with higher precipitation in the minor wet season and higher minimum temperature in the minor dry season. This model explained 22% of the variability in the yield gaps. In contrast, variation in the relative yield gaps was driven by management factors only, as normalizing water-limited yields results in a weak climate signal. The mixed-effect model showed that the relative yield gaps were reduced by increasing cocoa planting density and the application of fungicide against black pod, explaining 33% of the variability. In conclusion, the absolute cocoa yield gaps in Ghana are determined by climate with larger yield gaps in humid areas, whereas the relative yield gaps can be reduced by agronomic management practices.SIGNIFICANCE Our study is one of the first to quantify cocoa yield gaps in West Africa and shows that these can be closed by improved agronomic practices.

CONTEXT: Global cocoa production is largely concentrated in West Africa where over 70% of cocoa is produced. Here, cocoa farming is largely a rain-fed, low-input system with low average yields, which are expected to decline with climate change. With increasing demand, there is a need to evaluate opportunities to increase production whilst avoiding deforestation and expansion to croplands. Thus, it is important to know how much additional cocoa can be produced on existing farmland, and what factors determine this potential for increased yield.OBJECTIVE: The objective was to quantify the cocoa yield gap in Ghana and identify the factors that can contribute to narrowing the gap.METHODS: We calculated the cocoa yield gap as the difference between potential yield (i. water-limited potential (Yw) quantified using a crop model, ii. attainable yield in high-input systems(YE), iii. attainable yield in low -input systems(YF)) and actual farmer yield. Both absolute and relative yield gaps were calculated. We then related each yield gap (absolute & relative) as a function of environment and management variables using mixed -effects models.RESULTS AND CONCLUSIONS: There were considerable yield gaps on all cocoa farms. Maximum water-limited yield gaps (YGW) were very large with a mean absolute gap of 4577 kg/ha representing 86% of Yw. Attainable yield gap in high-input (YGE) was lower with mean absolute gap of 1930 kg/ha representing 73% of YE. The yield gap in low-input (YGF) was even lower with mean absolute gap of 469 kg/ha representing 42% of YF. Mixed -effects models showed that, absolute YGW were larger at sites with higher precipitation in the minor wet and minimum temperature in the minor dry season explaining 22% of the variability in YGW. These same factors and cocoa planting density explained 28% of variability in absolute YGE. Regardless of climate, absolute YGF and relative YGW, YGE and YGF were reduced by increasing cocoa planting density and application of fungicide against black pod. The models explained 25% of the variability in absolute YGF, and 33%, 33% and 25% in relative YGW, YGE and YGF respectively. In conclusion, climate determined absolute YGW in Ghana whilst absolute YGE were determined by both climate and management. In contrast, absolute YGF and relative YGW, YGE and YGF can be reduced by agronomic management practices.SIGNIFICANCE: Our study is one of the first to quantify cocoa yield gaps in West Africa and shows that these can be closed by improved agronomic practices.

Background Understanding the determinants of free asparagine concentration in wheat grain is necessary to reduce levels of the processing contaminant acrylamide in baked and toasted wheat products. Although crop management strategies can help reduce asparagine concentrations, breeders have limited options to select for genetic variation underlying this trait. Asparagine synthetase enzymes catalyse a critical step in asparagine biosynthesis in plants and, in wheat, are encoded by five homeologous gene triads that exhibit distinct expression profiles. Within this family, TaASN2 genes are highly expressed during grain development but TaASN-B2 is absent in some varieties. Results Natural genetic diversity in the asparagine synthetase gene family was assessed in different wheat varieties revealing instances of presence/absence variation and other polymorphisms, including some predicted to affect the function of the encoded protein. The presence and absence of TaASN-B2 was determined across a range of UK and global common wheat varieties and related species, showing that the deletion encompassing this gene was already present in some wild emmer wheat genotypes. Expression profiling confirmed that TaASN2 transcripts were only detectable in the grain, while TaASN3.1 genes were highly expressed during the early stages of grain development. TaASN-A2 was the most highly expressed TaASN2 homeologue in most assayed wheat varieties. TaASN-B2 and TaASN-D2 were expressed at similar, lower levels in varieties possessing TaASN-B2 . Expression of TaASN-A2 and TaASN-D2 did not increase to compensate for the absence of TaASN-B2, so total TaASN2 expression was lower in varieties lacking TaASN-B2 . Consequently, free asparagine concentrations in field-produced grain were, on average, lower in varieties lacking TaASN-B2 , although the effect was lost when free asparagine accumulated to very high concentrations as a result of sulphur deficiency. Conclusions Selecting wheat genotypes lacking the TaASN-B2 gene may be a simple and rapid way for breeders to reduce free asparagine concentrations in commercial wheat grain.

Additional file 2 Mean TPM expression data for each ASN gene in RNA-seq datasets.

AbstractA survey was conducted of Indonesian cocoa farms to assess the extent of yield variation and factors associated with this variation. The survey of 120 farms during the course of 3 years encompassed four provinces in Sulawesi (South, South-East, West and Central), Western Sumatra, Lampung, East Java and West Papua. A high degree of yield variation was observed between farms, the average over 3 years ranged from 39 to 3586 kg ha−1. Overall, yields were greater on farms that were classified as ‘highly managed’, compared to ‘moderately’ and ‘less managed’. Seasonal variability in yields was generally greater in districts with a more pronounced dry season such as South Sulawesi and Lampung. Multiple regression analyses revealed particular husbandry practices that were linked with higher cocoa yields. Specifically, the use of inorganic fertilisers, application of fungicides against blackpod and weeding were all practices that were associated with higher yields. A positive association between rainfall and yield was observed for the years 2014/15 and 2015/16 but not 2016/17, which was a La Niña year (when rainfall totals were higher). Some of the farms surveyed were planted with cocoa at very low densities implying an opportunity for yield improvement through gap filling or replanting at higher densities (although it was noted that some farmers maintained lower planting densities due to the cultivation of companion crops). Given the smallholder status of most cocoa farms in Indonesia (mean area in this study was 0.71 ha) it is important that farmers are able to maximise returns from their land in order to maintain a livelihood. This study illustrated the potential for yield improvement on Indonesian cocoa farms through adoption of best agronomic practice.

Cocoa (Theobroma cacao) is an economically important crop grown by approximately six million of smallholder farmers throughout the tropics and sub-tropics. However, farm level yields are often very low, and sustainable intensification is urgently required. Assessing the impact of on-farm interventions of farm productivity and profitability requires an understanding of the contribution of inter-annual climate variability to cocoa yields. A Delayed Differential Equation model (DDE) was used to simulate the effect of rainfall on cocoa yields. A DDE model is an ordinary differential equation model that incorporates time lags, and is therefore able to incorporate the delay in yield response to rainfall due interactions with the cocoa flowering and the pod development processes. The DDE was constructed and based on regional rainfall and farm-level cocoa yield data from 96 farms across the main cocoa growing regions in Ghana. Model outputs indicate that a good likeness of seasonality in crop production was achieved. The potential to conduct a detailed parameterisation and extend this model to include other parameters such as agrochemical inputs and farm management practices are discussed. By further developing this model into a useful tool to predict and understand variability in cocoa yield, the sustainable intensification of small holder cocoa farming is supported.

Sustainable high productivity cocoa farming requires the holistic combination of the best planting material with appropriate fertilizer supply, comprehensive farm management practises, and sufficient knowledge. Many farmers currently do not achieve high productivity due to limitations in their farming situation. To aid the transition of farmers from a low input – low output situation to a highly profitable, high productivity situation there is a need to provide farmers with a detailed plan with which they can effectively develop their farm. We have developed a decision support framework that integrates the key activities that farmers should take, and the impact of each activity on farm performance. This framework includes a calendar indicating the optimum time to conduct work; the amounts of resources required in terms of funding and labour, and an understanding of the impact of each activity in terms of increases to farm performance. Importantly, the level of risk, based on measurements of on-farm year-to-year variation in performance, are included. Comparing the financial implications of inputs vs. the benefits in yield and profit to the farmer allows a detailed and fully budgeted pathway to be provided for each individual farm. Here we present an overview of current tracks of research focusing on the promotion of Good Agricultural Practice. The research tracks are united in a conceptual decision support framework including a detailed economic understanding, which maps out the renovation of small holder cocoa farms.

The future of the world cocoa economy depends on the availability of genetic diversity and the sustainable use of this broad genetic base to breed improved varieties. Decreasing cacao genetic diversity (in situ, on-farm and conserved in collections) is a serious problem, and all its many causes need to be urgently addressed: the destruction of the Amazonian rainforests, changing patterns of land use, the spread of pests and diseases, sudden changes in climate and threats from natural disasters and extreme weather. These factors are resulting in an irreversible loss of the cacao genetic diversity so essential for farmers, breeders and consumers. A Global Strategy was published in 2012 to optimize the conservation and maximize the use of cacao genetic resources as the foundation of a sustainable cocoa economy. The chapter describes the key challenges, how they are being addressed and the priorities for further research and actions.

In order to obtain an understanding of farm practices and drivers of on-farm cocoa yields, a survey and a programme of regular crop monitoring was conducted across a range of farms in the top three cocoaproducing countries: Côte d’Ivoire, Ghana and Indonesia. For each country, groups of farms were sampled from key cocoa-growing regions or provinces and their physical characteristics were mapped (120 farms in Indonesia, 96 in Ghana and 48 in Côte d’Ivoire). Farm practices were determined by a farmer interview and crop development on selected trees from each farm was observed every six weeks over a period of four years in Ghana, three years in Indonesia and one year in Côte d’Ivoire. Farms in Ghana and Côte d’Ivoire were older and larger than those in Indonesia. In all three countries, planting density varied considerably (276 to 3626 trees ha in Ghana, 556 to 1848 trees ha in Côte d’Ivoire and 272 to 2598 trees ha in Indonesia) and often deviated from recommendations. Trees on all of the farms in Ghana and Côte d’Ivoire were seed derived, whilst a mixture of seed-derived and clonal material was cultivated in Indonesia. A larger proportion of farms (96%) were owner-operated in Indonesia compared with Côte d’Ivoire and Ghana (58% and 69%, respectively). Soil analyses in Ghana and Indonesia showed that nutrient levels were below threshold levels on many farms, illustrating the need for fertiliser applications to be matched to local conditions. Considerable farm-to-farm variation in yield was recorded for each country. For example, in Ghana 30 and 10-fold differences in yield were observed between farms for the years 2012/13 and 2013/14, respectively. Geographical variation in yield was much greater in Indonesia, where cocoa cultivation is spread over a larger area than in Ghana and Côte d’Ivoire. Farm to farm variation within each country was partially explained by a number of common factors. These included planting density (many farms were planted below recommendations), whether or not the farmers fertilise their farms and whether or not they sprayed fungicides. In Ghana, insufficient soil phosphorus was another factor underlying yield variation between farms. Overall, the results of this study demonstrated the potential for yield improvement on existing cocoa farms, without significant expansion of the area cultivated, through husbandry practices (such as gap-filling/ replanting of low density farms), targeted fertiliser application and carefully timed pest and disease control.

Cocoa self-compatibility is an important yield factor and has been described as being controlled by a late gameto-sporophytic system expressed only at the level of the embryo sac. It results in gametic non-fusion and involves several loci. In this work, we identified two loci, located on chromosomes 1 and 4 (CH1 and CH4), involved in cocoa self-incompatibility by two different processes. Both loci are responsible for gametic selection, but only one (the CH4 locus) is involved in the main fruit drop. The CH1 locus acts prior to the gamete fusion step and independently of the CH4 locus. Using fine-mapping and genome-wide association studies, we focused analyses on restricted regions and identified candidate genes. Some of them showed a differential expression between incompatible and compatible reactions. Immunolocalization experiments provided evidence of CH1 candidate genes expressed in ovule and style tissues. Highly polymorphic simple sequence repeat (SSR) diagnostic markers were designed in the CH4 region that had been identified by fine-mapping. They are characterized by a strong linkage disequilibrium with incompatibility alleles, thus allowing the development of efficient diagnostic markers predicting self-compatibility and fruit setting according to the presence of specific alleles or genotypes. SSR alleles specific to self-compatible Amelonado and Criollo varieties were also identified, thus allowing screening for self-compatible plants in cocoa populations.

A range of physiological parameters (canopy light transmission, canopy shape, leaf size, flowering and flushing intensity) were measured from the International Clone Trial, typically over the course of two years. Data were collected from six locations, these being: Brazil, Ecuador, Trinidad, Venezuela, Cote d’Ivoire and Ghana. Canopy shape varied significantly between clones, although it showed little variation between locations. Genotypic variation in leaf size was differentially affected by the growth location; such differences appeared to underlie a genotype by environment interaction in relation to canopy light transmission. Flushing data were recorded at monthly intervals over the course of a year. Within each location, a significant interaction was observed between genotype and time of year, suggesting that some genotypes respond to a greater extent than others to environmental stimuli. A similar interaction was observed for flowering data, where significant correlations were found between flowering intensity and temperature in Brazil and flowering intensity and rainfall in Cote d’Ivoire. The results demonstrate the need for local evaluation of cocoa clones and also suggest that the management practices for particular planting material may need to be fine-tuned to the location in which they are cultivated.

Tricker, P., Gibbings, G., Cryer, N., Hadley, P., Wilkinson, M. J. (2008). Epigenetic control of stomatal number in response to humidity environment. Comparative Biochemistry and Physiology A - Molecular & Integrative Physiology 150, (3), S190-S191. Proceedings of the Annual Main Meeting of the Society of Experimental Biology, Marseille, France, 6-10 July 2008. IMPF: 01.71 RONO: 00

Standardisation of microsatellite allele profiles between laboratories is of fundamental importance to the transferability of genetic fingerprint data and the identification of clonal individuals held at multiple sites. Here we describe two methods of standardisation applied to the microsatellite fingerprinting of 429 L. trees representing 345 accessions held in the worlds largest Cocoa Intermediate Quarantine facility: the use of a partial allelic ladder through the production of 46 cloned and sequenced allelic standards (AJ748464 to AJ48509), and the use of standard genotypes selected to display a diverse allelic range. Until now a lack of accurate and transferable identification information has impeded efforts to genetically improve the cocoa crop. To address this need, a global initiative to fingerprint all international cocoa germplasm collections using a common set of 15 microsatellite markers is in progress. Data reported here have been deposited with the International Cocoa Germplasm Database and form the basis of a searchable resource for clonal identification. To our knowledge, this is the first quarantine facility to be completely genotyped using microsatellite markers for the purpose of quality control and clonal identification. Implications of the results for retrospective tracking of labelling errors are briefly explored.

Standardisation of microsatellite allele profiles between laboratories is of fundamental importance to the transferability of genetic fingerprint data and the identification of clonal individuals held at multiple sites. Here we describe two methods of standardisation applied to the microsatellite fingerprinting of 429 Theobroma cacao L. trees representing 345 accessions held in the worlds largest Cocoa Intermediate Quarantine facility: the use of a partial allelic ladder through the production of 46 cloned and sequenced allelic standards (AJ748464 to AJ48509), and the use of standard genotypes selected to display a diverse allelic range. Until now a lack of accurate and transferable identification information has impeded efforts to genetically improve the cocoa crop. To address this need, a global initiative to fingerprint all international cocoa germplasm collections using a common set of 15 microsatellite markers is in progress. Data reported here have been deposited with the International Cocoa Germplasm Database and form the basis of a searchable resource for clonal identification. To our knowledge, this is the first quarantine facility to be completely genotyped using microsatellite markers for the purpose of quality control and clonal identification. Implications of the results for retrospective tracking of labelling errors are briefly explored.

Background Large-scale genetic profiling, mapping and genetic association studies require access to a series of well-characterised and polymorphic microsatellite markers with distinct and broad allele ranges. Selection of complementary microsatellite markers with non-overlapping allele ranges has historically proved to be a bottleneck in the development of multiplex microsatellite assays. The characterisation process for each microsatellite locus can be laborious and costly given the need for numerous, locus-specific fluorescent primers. Results Here, we describe a simple and inexpensive approach to select useful microsatellite markers. The system is based on the pooling of multiple unlabelled PCR amplicons and their subsequent ligation into a standard cloning vector. A second round of amplification utilising generic labelled primers targeting the vector and unlabelled locus-specific primers targeting the microsatellite flanking region yield allelic profiles that are representative of all individuals contained within the pool. Suitability of various DNA pool sizes was then tested for this purpose. DNA template pools containing between 8 and 96 individuals were assessed for the determination of allele ranges of individual microsatellite markers across a broad population. This helped resolve the balance between using pools that are large enough to allow the detection of many alleles against the risk of including too many individuals in a pool such that rare alleles are over-diluted and so do not appear in the pooled microsatellite profile. Pools of DNA from 12 individuals allowed the reliable detection of all alleles present in the pool. Conclusion The use of generic vector-specific fluorescent primers and unlabelled locus-specific primers provides a high resolution, rapid and inexpensive approach for the selection of highly polymorphic microsatellite loci that possess non-overlapping allele ranges for use in large-scale multiplex assays.

The level of mislabelling of cocoa clones in germplasm collections is fairly high. Although not a new problem, the availability of genetic fingerprinting technologies has allowed projects to be developed that use microsatellite markers to compare clones. However, it is important that when clones with the same name are found to have different profiles, one is determined to be the true type (with reference to the most original material). Off-types should be kept for their potential agronomic value, but with a unique new name. We have proposed a format for renaming that highlights the mislabelling event and which includes references to the source germplasm collection and the name originally given to the clone. (Resume d'auteur)