Climate change could threaten cocoa production: Effects of 2015-16 El Niño-related drought on cocoa agroforests in Bahia, Brazil

Multi-trait selection for nutritional and physiological quality of cacao genotypes in irrigated and non-irrigated environments

Water is a scarce, strategic resource and the most important input for economic development, especially in agricultural countries such as Brazil. Cocoa production is directly related to water availability, and, as climate changes, selecting drought-tolerant genotypes is vital to keep cacao crops sustainable. Here, we evaluated cacao genotypes under irrigated and water-stressed conditions and selected drought-tolerant ones based on nutritional and physiological traits. Thirty-nine genotypes were monitored for three years for agronomic traits and higher fruit yield. After this evaluation, the 18 most promising genotypes were evaluated in a randomized block design, under a 2 (with and without irrigation)  ×  18 (genotypes) factorial arrangement, with three replicates and five plants per plot. We evaluated seven physiological and 11 nutritional traits, selecting genotypes based on the Genotype-by-Trait Biplot approach. Significant effects (p < 0.05) were observed for the nutritional traits N, P, Mg, S, Zn, Cu, Mn and for the physiological traits CO2 assimilation rate (A), stomatal conductance (gs), transpiration (E), intercellular and atmospheric CO2 concentrations (Ci/Ca), intrinsic water use efficiency (A/gs), instantaneous water use efficiency (A/E), and instantaneous carboxylation efficiency (A/Ci), as determined by analysis of variance. The genotype  ×  irrigation treatment interaction was significant (p < 0.05) for the traits A, gs, and E. Genotypes CP 41, CP 43, and CCN 51 exhibited superior performance for both nutritional and physiological traits (A, gs, and E). In the irrigated environment, CP 41 showed superiority in traits such as P, A/E, A/gs, Mn, S, and Zn. Conversely, under non-irrigated conditions, CP 43 exhibited better performance in nutritional properties, specifically Mn, Mg, and Zn. Notably, in both irrigated and non-irrigated environments, CCN 51 excelled in key physiological traits, including A/Ci, A/E, and A/gs. This robust performance across diverse conditions suggests that these three genotypes possess physiological mechanisms to endure water-stressed conditions. Our research can generate valuable insights into these genotypes informing suitable choices for cocoa cultivation, especially in the context of global climate change.

Effects of ENSO events on the intensity, seasonality, and diversity of reproductive phenology of Miconia (Melastomataceae) species in tropical rainforest

We evaluated the phenology and reproductive phenological diversity of three sympatric species of Miconia in a gallery forest in the Chapada Diamantina mountains, Bahia, Brazil. The reproductive phenophases (bud, flower, immature fruit, and mature fruit) of M. alborufescens (N=38), M. holosericea (N=46), and M. prasina (N=44) were evaluated monthly, between June/2008 and June/2015. The Fournier index was used to assess the intensities of the reproductive phenophases; synchrony and seasonality were analyzed using circular statistics and the Rayleigh (Z) test. The Frideman and Wilcoxon tests were used to verify interannual variations in phenological patterns. Reproductive phenological diversity was measured by calculating the Shannon-Wiener index; ANOVA tested possible differences in the means of diversity among the different years. The reproductive phenophases of the studied Miconia species occurred sequentially (M. alborufescens, then M. holoserica, followed by M. prasina), in the transition between the dry and rainy seasons, with little overlap between them. In general, the species showed seasonal and synchronic phenological patterns, with some variations that coincided with El Niño and/or La Niña events, e.g., demonstrating changes in the periodicity, synchrony, and intensity of their phenophases. The intensity of fruiting, for example, showed increases during La Niña years. Reproductive phenological diversity appears to respond to climate changes resulting from El Niño events and periods of prolonged drought, with high Shannon-Wiener index values. The results also suggest that the effects of global climatic phenomena (El Niño and La Niña) that alter regional climatic seasonality can also cause variations in the reproductive phenological rhythms of the Miconia species studied.

Integrating GIS and remote sensing for land use/land cover mapping and groundwater potential assessment for climate-smart cocoa irrigation in Ghana

Although Ghana is a leading global cocoa producer, its production and yield have experienced declines in recent years due to various factors, including long-term climate change such as increasing temperatures and changing rainfall patterns, as well as drought events. With the increasing exposure of cocoa-producing regions to extreme weather events, the vulnerability of cocoa production is also expected to rise. Supplemental irrigation for cocoa farmers has emerged as a viable adaptation strategy to ensure a consistent water supply and enhance yield. However, understanding the potential for surface and groundwater irrigation in the cocoa-growing belt remains limited. Consequently, this study aims to provide decision-support maps for surface and groundwater irrigation potential to aid planning and investment in climate-smart cocoa irrigation. Utilizing state-of-the-art geospatial and remote sensing tools, data, and methods, alongside in-situ groundwater data, we assess the irrigation potential within Ghana's cocoa-growing areas. Our analysis identified a total area of 22,126 km2 for cocoa plantations and 125.2 km2 for surface water bodies within the cocoa-growing regions. The multi-criteria analysis (MCA) revealed that approximately 80% of the study area exhibits moderate to very high groundwater availability potential. Comparing the MCA output with existing borehole locations demonstrated a reasonable correlation, with about 80% of existing boreholes located in areas with moderate to very high potential. Boreholes in very high potential areas had the highest mean yield of 90.7 l/min, while those in low groundwater availability potential areas registered the lowest mean yield of 58.2 l/min. Our study offers a comprehensive evaluation of water storage components and their implications for cocoa irrigation in Ghana. While groundwater availability shows a generally positive trend, soil moisture and surface water have been declining, particularly in the last decade. These findings underline the need for climate-smart cocoa irrigation strategies that make use of abundant groundwater resources during deficit periods. A balanced conjunctive use of surface and groundwater resources could thus serve as a sustainable solution for maintaining cocoa production in the face of climate change.

Implementation of pre-harvest techniques in emerging agroforestry systems to increase the yield of cocoa tree (Theobroma cacao L.)

Cocoa is one of the most important tropical fruits worldwide, its importance lies in its use in the food, cosmetic and pharmaceutical industries. Cocoa yield has been affected by different environmental, cultural and phytosanitary aspects. The emergence of new growing areas allows exploring the possibility of generating new economic and ecological systems that comply with current trends in organic farming. For them, pre-harvest practices such as pruning and soil fertilization are two necessary tools to control the productivity of cocoa agroecosystems. Therefore, the objective of this research was to analyses the implementation of pre-harvest techniques and the quality soil to increase the yield in a cocoa agroecosystem in an emerging zone in the Huasteca Potosina of Mexico. The work was carried out in an emerging zone in the cultivation of cocoa in three different zones delimited in 30 × 30 m. Thinning and pruning practices were carried out to keep the space clear and observe the influence on fruit yield. In addition, the quality of the soil was measured in terms of physical conditions and nutrient content. 25 kg/ha of nitrogen, 22 kg/ha of P2O5, 24 kg/ha of K2O and 4 kg/ha of magnesium were added following the recommendation of the fertilization laboratory. The physical properties of the pod were also analyzed, such as size, weight, number of grains and color. And some of the cocoa bean such as size, weight and hardness, all these parameters to measure the average yield of cocoa pods. The results show a clear influence of the soil quality and pre-harvest practices on the physical properties of the fruit and the total yield from 472.36 ± 52.01 to 520.06 ± 104.91 kg. However, other aspects are also modified, such as the increase in the size of the pod and the cocoa bean. Other aspects such as the color of the pod and the hardness of the grain do not present statistical difference. In conclusion, pre-harvest practices together with the application of fertilizers are factors that positively influence the yield of cocoa fruit. Some of the limitations of this research were the age of the plants and the local plant species.

Climate change alters impacts of extreme climate events on a tropical perennial tree crop

Anthropogenic climate change causes more frequent and intense fluctuations in the El Niño Southern Oscillation (ENSO). Understanding the effects of ENSO on agricultural systems is crucial for predicting and ameliorating impacts on lives and livelihoods, particularly in perennial tree crops, which may show both instantaneous and delayed responses. Using cocoa production in Ghana as a model system, we analyse the impact of ENSO on annual production and climate over the last 70 years. We report that in recent decades, El Niño years experience reductions in cocoa production followed by several years of increased production, and that this pattern has significantly shifted compared with prior to the 1980s. ENSO phase appears to affect the climate in Ghana, and over the same time period, we see corresponding significant shifts in the climatic conditions resulting from ENSO extremes, with increasing temperature and water stress. We attribute these changes to anthropogenic climate change, and our results illustrate the big data analyses necessary to improve understanding of perennial crop responses to climate change in general, and climate extremes in particular.

Screening for drought tolerance potential of nine cocoa (Theobroma cacao L.) genotypes from Ghana

This study was conducted with a view to screen nine genotypes of Cacao from The Cocoa Research Institute of Ghana (CRIG) to test their abilities to withstand drought stress conditions using parameters such as leaf relative water content (RWC), proline accumulation in leaves and trichomes. The experimental design consisted of three replicates of the genotypes used and these were laid out in Complete Randomized Block Design (CRBD) to determine the drought tolerance potentials of the nine genotypes of cocoa at the seedling stage. Two water treatments were used which involved withholding water from one day after full saturation with water prior to the first appearance of drought symptoms (FADS) and watering every two days to the completion of the experiment. Results in this research revealed that proline was found to gather in water-stressed seedlings, and the differences in the mean proline amounts in the genotypes was found to be significant. Genotype T63/971 x Sca9 had the most elevated concentration of free proline at FADS (4 μg/g DW) followed by genotype T60 x Pound10 (3.5 μg/g DW) whereas genotype PA150 × 9006 had the smallest amount of accumulated proline in leaves. Genotype PA150 × 6020 had the highest RWC and SMC of 65% and 1.5% respectively at FADS whilst genotype PA7 x 6035 had the lowest RWC of 43%. There was a direct relationship between the amounts of free proline of genotypes T63/971 x SCA9 and T60 x POUND10 and their respective RWC of the leaves. Genotypes T63/971 x SCA9 and PA150 × 9006 had the highest and lowest numbers of trichomes respectively. Inference from this study revealed that T63/971 x SCA9 and T60 x POUND10 genotypes appear to be the most drought-tolerant genotypes in view of their relatively high values of free proline content, leaf RWC, trichomes and lower values of soil water use (SMC).

Functional yeast starter cultures for cocoa fermentation

The quest to develop a performant starter culture mixture to be applied in cocoa fermentation processes started in the 20th century, aiming at achieving high‐quality, reproducible chocolates with improved organoleptic properties. Since then, different yeasts have been proposed as candidate starter cultures, as this microbial group plays a key role during fermentation of the cocoa pulp‐bean mass. Yeast starter culture‐initiated fermentation trials have been performed worldwide through the equatorial zone and the effects of yeast inoculation have been analysed as a function of the cocoa variety (Forastero, Trinitario and hybrids) and fermentation method (farm‐, small‐ and micro‐scale) through the application of physicochemical, microbiological and chemical techniques. A thorough screening of candidate yeast starter culture strains is sometimes done to obtain the best performing strains to steer the cocoa fermentation process and/or to enhance specific features, such as pectinolysis, ethanol production, citrate assimilation and flavour production. Besides their effects during cocoa fermentation, a significant influence of the starter culture mixture applied is often found on the cocoa liquors and/or chocolates produced thereof. Thus, starter culture‐initiated cocoa fermentation processes constitute a suitable strategy to elaborate improved flavourful chocolate products.

Cacao (Theobroma cacao L.) Response to Water Stress: Physiological Characterization and Antioxidant Gene Expression Profiling in Commercial Clones

The increase in events associated with drought constraints plant growth and crop performance. Cacao (Theobroma cacao L.) is sensitive to water deficit stress (DS), which limits productivity. The aim of this research was to characterise the response of seven (CCN51, FEAR5, ICS1, ICS60, ICS95, EET8, and TSH565) commercially important cacao clones to severe and temporal water deficit stress. Ten-month-old cacao trees were submitted to two treatments: well-watered and water-stressed until the leaf water potential (Ψ leaf) reached values between -3.0 and -3.5 MPa. The effects of hydric stress on water relations, gas exchange, photochemical activity, membrane integrity and oxidative stress-related gene expression were evaluated. All clones showed decreases in Ψ leaf, but TSH565 had a higher capacity to maintain water homeostasis in leaves. An initial response phase consisted of stomatal closure, a general mechanism to limit water loss: as a consequence, the photosynthetic rate dropped by approximately 98% on average. In some clones, the photosynthetic rate reached negative values at the maximum stress level, evidencing photorespiration and was confirmed by increased intracellular CO2. A second and photosynthetically limited phase was characterized by a drop in PSII quantum efficiency, which affected all clones. On average, all clones were able to recover after 4 days of rewatering. Water deficit triggered oxidative stress at the early phase, as evidenced by the upregulation of oxidative stress markers and genes encoding ROS scavenging enzymes. The effects of water deficit stress on energy metabolism were deduced given the upregulation of fermentative enzyme-coding genes. Altogether, our results suggest that the EET8 clone was the highest performing under water deficit while the ICS-60 clone was more susceptible to water stress. Importantly, the activation of the antioxidant system and PSII repair mechanism seem to play key roles in the observed differences in tolerance to water deficit stress among clones.

Quality differentiation of cocoa beans: implications for geographical indications

Geographical indications may stimulate collective actions of governance for quality control, trade and marketing as well as innovation based on the use of local resources and regional biodiversity. Cocoa production, however, dominated by small family agriculture in tropical regions, has rarely made use of such strategies. This review is aimed at understanding major research interests and emerging technologies helpful for the origin differentiation of cocoa quality. Results from literature search and cited references of publications on cocoa research were imported into VOSviewer for data analysis, which aided in visualizing major research hotpots. Co-occurrence analysis yielded major research clusters which guided the discussion of this review. Observed was a consensus recognizing cocoa quality resulting from the interaction of genotype, fermentation variables and geographical origin. A classic view of cocoa genetics based on the dichotomy of 'fine versus bulk' has been reexamined by a broader perspective of human selection and cocoa genotype evolution. This new approach to cocoa genetic diversity, together with the understanding of complex microbiome interactions through fermentation, as well as quality reproducibility challenged by geographical conditions, have demonstrated the importance of terroir in the production of special attributes. Cocoa growing communities around the tropics have been clearly enabled by new omics and chemometrics to systematize producing conditions and practices in the designation of specifications for the differentiation of origin quality. © 2021 Society of Chemical Industry.

Crop response to El Niño-Southern Oscillation related weather variation to help farmers manage their crops

Although weather is a major driver of crop yield, many farmers don't know in advance how the weather will vary nor how their crops will respond. We hypothesized that where El Niño-Southern Oscillation (ENSO) drives weather patterns, and data on crop response to distinct management practices exists, it should be possible to map ENSO Oceanic Index (ENSO OI) patterns to crop management responses without precise weather data. Time series data on cacao farm yields in Sulawesi, Indonesia, with and without fertilizer, were used to provide proof-of-concept. A machine learning approach associated 75% of cacao yield variation with the ENSO patterns up to 8 and 24 months before harvest and predicted when fertilizer applications would be worthwhile. Thus, it's possible to relate average cacao crop performance and management response directly to ENSO patterns without weather data provided: (1) site specific data exist on crop performance over time with distinct management practices; and (2) the weather patterns are driven by ENSO OI. We believe that the principles established here can readily be applied to other crops, particularly when there's little data available on crop responses to management and weather. However, specific models will be required for each crop and every recommendation domain.

The Role of Fungi in the Cocoa Production Chain and the Challenge of Climate Change

Background: The role of fungi in cocoa crops is mainly associated with plant diseases and contamination of harvest with unwanted metabolites such as mycotoxins that can reach the final consumer. However, in recent years there has been interest in discovering other existing interactions in the environment that may be beneficial, such as antagonism, commensalism, and the production of specific enzymes, among others. Scope and approach: This review summarizes the different fungi species involved in cocoa production and the cocoa supply chain. In particular, it examines the presence of fungal species during cultivation, harvest, fermentation, drying, and storage, emphasizing the factors that possibly influence their prevalence in the different stages of production and the health risks associated with the production of mycotoxins in the light of recent literature. Key findings and conclusion: Fungi associated with the cocoa production chain have many different roles. They have evolved in a varied range of ecosystems in close association with plants and various habitats, affecting nearly all the cocoa chain steps. Reports of the isolation of 60 genera of fungi were found, of which only 19 were involved in several stages. Although endophytic fungi can help control some diseases caused by pathogenic fungi, climate change, with increased rain and temperatures, together with intensified exchanges, can favour most of these fungal infections, and the presence of highly aggressive new fungal genotypes increasing the concern of mycotoxin production. For this reason, mitigation strategies need to be determined to prevent the spread of disease-causing fungi and preserve beneficial ones.

Does Sentinel-1A Backscatter Capture the Spatial Variability in Canopy Gaps of Tropical Agroforests? A Proof-of-Concept in Cocoa Landscapes in Cameroon

A reliable estimation and monitoring of tree canopy cover or shade distribution is essential for a sustainable cocoa production via agroforestry systems. Remote sensing (RS) data offer great potential in retrieving and monitoring vegetation status at landscape scales. However, parallel advancements in image processing and analysis are required to appropriately use such data for different targeted applications. This study assessed the potential of Sentinel-1A (S-1A) C-band synthetic aperture radar (SAR) backscatter in estimating canopy cover variability in cocoa agroforestry landscapes. We investigated two landscapes, in Center and South Cameroon, which differ in predominant vegetation: forest-savannah transition and forest landscape, respectively. We estimated canopy cover using in-situ digital hemispherical photographs (DHPs) measures of gap fraction, verified the relationship with SAR backscatter intensity and assessed predictions based on three machine learning approaches: multivariate bootstrap regression, neural networks regression, and random forest regression. Our results showed that about 30% of the variance in canopy gap fraction in the cocoa production landscapes was shared by the used SAR backscatter parameters: a combination of S-1A backscatter intensity, backscatter coefficients, difference, cross ratios, and normalized ratios. Based on the model predictions, the VV (co-polarization) backscatter showed high importance in estimating canopy gap fraction; the VH (cross-polarized) backscatter was less sensitive to the estimated canopy gap. We observed that a combination of different backscatter variables was more reliable at predicting the canopy gap variability in the considered type of vegetation in this study—agroforests. Semi-variogram analysis of canopy gap fraction at the landscape scale revealed higher spatial clustering of canopy gap, based on spatial correlation, at a distance range of 18.95 m in the vegetation transition landscape, compared to a 51.12 m spatial correlation range in the forest landscape. We provide new insight on the spatial variability of canopy gaps in the cocoa landscapes which may be essential for predicting impacts of changing and extreme (drought) weather conditions on farm management and productivity. Our results contribute a proof-of-concept in using current and future SAR images to support management tools or strategies on tree inventorying and decisions regarding incentives for shade tree retention and planting in cocoa landscapes.