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The purpose of this study is to examine the relative importance of climate normals (average long-term temperature and precipitation) in explaining net farm revenue per hectare (NRh) for supplementary irrigated and rainfed cocoa farms in Nigeria.

NRh was estimated for 280 cocoa farmers sampled across seven Nigerian states. It was regressed on climate, household socio-economic characteristics and other control variables by using a Ricardian analytical framework. Marginal calculations were used to isolate the effects of climate change (CC) on cocoa farm revenues under supplementary irrigated and rainfed conditions. Future impacts of CC were simulated using Six CORDEX regional climate model (RCM) ensemble between 2036-2065 and 2071-2100.

Results indicate high sensitivity of NRh to Nigerian climate normals depending on whether farms use supplementary irrigation. Average annual temperature increases and precipitation decreases are associated with NRh losses for rainfed farms and gains for supplementary irrigated cocoa farms. Projections of future CC impacts suggest a wide range of NRh outcomes on supplementary irrigated and rainfed farm revenues, demonstrating the importance of irrigation as an effective adaptation strategy in Nigeria.

This paper uses novel data sets for simulating future CC impacts on land values in Nigeria. CORDEX data constitute the most comprehensive RCMs projections available for Africa.

This paper aims to assess how cocoa supply chain companies disclose sustainable development goals (SDGs) information in their sustainability reports. This assessment highlights strategic aspects of sustainable supply chain management and reveals leveraging sustainability points in the cocoa industry.

The two-step qualitative approach relies on text-mining company reports and subsequent content analysis that identifies the topics disclosed and relates them to SDG targets.

This study distinguishes 18 SDG targets connected to cocoa traders and 30 SDG targets to chocolate manufacturers. The following topics represent the main nexuses of connections: decent labour promotion and gender equity (social), empowering local communities and supply chain monitoring (economic) and agroforestry and climate action (environmental).

By highlighting the interconnections between the SDGs targeted by companies in the cocoa supply chain, this paper sheds light on the strategic SDGs for this industry and their relationships, which can help to improve sustainability disclosure and transparency. One interesting input for companies is the improvement of climate crisis prevention, focusing on non-renewable sources minimisation, carbon footprint and clear indicators of ecologic materiality.

This study contributes to policymakers to enhance governance and accountability of global supply chains that are submitted to different regulation regimes.

To the best of the authors’ knowledge, no previous study has framed the cocoa industry from a broader SDG perspective. The interconnections identified reveal the key goals of the cocoa supply chain and point to strategic sustainability choices for companies in an important global industry.

This paper examines the potential of “biomarkers” to provide immutable identification for food products (chocolate), providing traceability and visibility in the supply chain from retail product back to farm.

This research uses qualitative data collection, including fieldwork at cocoa farms and chocolate manufacturers in Ecuador and the Netherlands and semi-structured interviews with industry professionals to identify challenges and create a supply chain map from cocoa plant to retailer, validated by area experts. A library of biomarkers is created using DNA collected from fieldwork and the International Cocoa Quarantine Centre, holders of cocoa varieties from known locations around the world. Matching sample biomarkers with those in the library enables identification of origins of cocoa used in a product, even when it comes from multiple different sources and has been processed.

Supply chain mapping and interviews identify areas of the cocoa supply chain that lack the visibility required for management to guarantee sustainability and quality. A decoupling point, where smaller farms/traders’ goods are combined to create larger economic units, obscures product origins and limits visibility. These factors underpin a potential boundary condition to institutional theory in the industry’s fatalism to environmental and human abuses in the face of rising institutional pressures. Biomarkers reliably identify product origin, including specific farms and (fermentation) processing locations, providing visibility and facilitating control and trust when purchasing cocoa.

The biomarker “meta-barcoding” of cocoa beans used in chocolate manufacturing accurately identifies the farm, production facility or cooperative, where a cocoa product came from. A controlled data set of biomarkers of registered locations is required for audit to link chocolate products to origin.

Where biomarkers can be produced from organic products, they offer a method for closing visibility gaps, enabling responsible sourcing. Labels (QR codes, barcodes, etc.) can be swapped and products tampered with, but biological markers reduce reliance on physical tags, diminishing the potential for fraud. Biomarkers identify product composition, pinpointing specific farm(s) of origin for cocoa in chocolate, allowing targeted audits of suppliers and identifying if cocoa of unknown origin is present. Labour and environmental abuses exist in many supply chains and enabling upstream visibility may help firms address these challenges.

By describing a method for firms in cocoa supply chains to scientifically track their cocoa back to the farm level, the research shows that organizations can conduct social audits for child labour and environmental abuses at specific farms proven to be in their supply chains. This provides a method for delivering supply chain visibility (SCV) for firms serious about tackling such problems.

This paper provides one of the very first examples of biomarkers for agricultural SCV. An in-depth study of stakeholders from the cocoa and chocolate industry elucidates problematic areas in cocoa supply chains. Biomarkers provide a unique biological product identifier. Biomarkers can support efforts to address environmental and social sustainability issues such as child labour, modern slavery and deforestation by providing visibility into previously hidden areas of the supply chain.

Solar power forecasting will have a significant impact on the future of large-scale renewable energy plants. Predicting photovoltaic power generation depends heavily on climate conditions, which fluctuate over time. In this research, we propose a hybrid model that combines machine-learning methods with Theta statistical method for more accurate prediction of future solar power generation from renewable energy plants. The machine learning models include long short-term memory (LSTM), gate recurrent unit (GRU), AutoEncoder LSTM (Auto-LSTM) and a newly proposed Auto-GRU. To enhance the accuracy of the proposed Machine learning and Statistical Hybrid Model (MLSHM), we employ two diversity techniques, i.e. structural diversity and data diversity. To combine the prediction of the ensemble members in the proposed MLSHM, we exploit four combining methods: simple averaging approach, weighted averaging using linear approach and using non-linear approach, and combination through variance using inverse approach. The proposed MLSHM scheme was validated on two real-time series datasets, that sre Shagaya in Kuwait and Cocoa in the USA. The experiments show that the proposed MLSHM, using all the combination methods, achieved higher accuracy compared to the prediction of the traditional individual models. Results demonstrate that a hybrid model combining machine-learning methods with statistical method outperformed a hybrid model that only combines machine-learning models without statistical method.

Background: Commodity-driven deforestation is a major driver of forest loss worldwide, and globalisation has increased the disconnect between producer and consumer countries. Recent due-diligence legislation aiming to improve supply chain sustainability covers major forest-risk commodities. However, the evidence base for specific commodities included within policy needs assessing to ensure effective reduction of embedded deforestation.

Methods: We conducted a rapid evidence synthesis in October 2020 using three databases; Google Scholar, Web of Science, and Scopus, to assess the literature and identify commodities with the highest deforestation risk linked to UK imports. Inclusion criteria include publication in the past 10 years and studies that didn't link commodity consumption to impacts or to the UK were excluded. The development of a review protocol was used to minimise bias and critical appraisal of underlying data and methods in studies was conducted in order to assess the uncertainties around results.

Results: From a total of 318 results, 17 studies were included in the final synthesis. These studies used various methodologies and input data, yet there is broad alignment on commodities, confirming that those included in due diligence legislation have a high deforestation risk. Soy, palm oil, and beef were identified as critical, with their production being concentrated in just a few global locations. However, there are also emerging commodities that have a high deforestation risk but are not included in legislation, such as sugar and coffee. These commodities are much less extensively studied in the literature and may warrant further research and consideration.

Conclusion: Policy recommendations in the selected studies suggests further strengthening of the UK due diligence legislation is needed. In particular, the provision of incentives for uptake of policies and wider stakeholder engagement, as well as continual review of commodities included to ensure a reduction in the UK's overseas deforestation footprint.

Collaboration in agricultural value chains (AVCs) has the potential to increase smallholders’ participation in international value chains and increase their benefits from participation. This scoping review explores existing collaboration models among stakeholders of AVCs in developing countries, examines enablers and constraints of collaboration and identifies policy gaps.

We systematically searched three databases, CAB Abstracts, Econlit (EBSCO) and Agricola, for studies published between 2005 and 2023 and included 59 relevant studies on AVC collaboration.

The primary motivations for collaboration are to enhance market access and improve product quality. Key outcomes of collaboration include improvements in farmers’ welfare, market participation and increased production; only a few studies consider improved risk management as an important outcome. Robust support from government and non-governmental entities is a primary enabler of collaboration. Conversely, conflicts of interest among stakeholders and resource limitations constrain collaboration possibilities. Collaboration involving high-value crops prioritizes income increases, whereas collaboration involving staple crops focuses on improving household food security.

This study may have publication bias as unsuccessful instances of collaboration are less likely to be published.

This study is unique in highlighting collaboration models’ characteristics and identifying AVC policy and programmatic areas where private firms, farmers’ groups, local governments and donor agencies can contribute.

This study aims to assess gender-based differences on farmers’ perception of impacts and vulnerability to climate change and the implementation of adaptation strategies in the Pra River Basin of Ghana, while also providing lessons for other Sub-Saharan nations and regions with similar conditions.

The study used semi-structured interviews and questionnaires to collect data from 344 farmers, 64 participants in focus group discussions and 6 agriculture extension officers (key informants) from 10 districts in the Pra River Basin of Ghana.

Results showed several differences in how climate change is perceived and tackled by male and female genders. In the perception of male farmers, for example, they were found to be more vulnerable to increased temperature, and changes in rainfall and growing season, whereas female farmers on average were considered to be less resilient to floods and droughts for different reasons. Moreover, floods posed higher risks to farming than other climate change impacts. Gender roles had a significant correlation with the type of adaptation strategies practised. Men adopted agrochemicals more often than women, as an adaptation strategy.

Gender-differentiated interventions should be incorporated in the national climate change action plan for sustainable development in a rain-fed agricultural economy such as Ghana. The study recommends several actions to promote gender equity in the assessed region.

This research assessed the gender differentials in climate trends, impact, vulnerability and adaptation based on primary data collected between April and May 2019 and compared the results with climate data in the basin for the period 1991–2014. It is an empirical study focused on primary data analysis obtained in loco by authors, involving approximately 400 participants.

This study aims to explore possible ways to promote uptake and integration of climate-smart agriculture (CSA)-Technologies, Innovations and Management Practices (TIMPS) into policy and practice in Nigeria through the development of actionable roadmaps to facilitate the process.

Two hundred and fifty-two stakeholders for the policy discourse and survey were purposively drawn from both government and private agencies, NGOs and community-based associations from the six geo-political zones of the country. Data collection was done using a mixed method comprising questionnaire administration, in-depth interviews and panel discussion. Data collected was summarised using descriptive statistics.

The major findings were lack of existing policies on CSA, lack of farmers’ awareness of CSA-TIMPs, neglect of extension programmes that can help to enlighten farmers on the importance of CSA and insufficient extension personnel to cater for farmers’ needs. Challenges to CSA-TIMPs uptake in Nigeria were: insufficient funding and support by government in programme planning and implementation, policy inconsistencies and poor farmers’ attitude and resistance to change.

This research will facilitate CSA uptake and integration through the provision of data for informed decision and action by the responsible agencies.

Suggested actionable roadmaps across the zones were robust awareness campaign and advocacy on uptake of CSA-TIMPs through e-extension, community TV/radio in local dialects; revitalisation of policy programmes such as monthly meetings should be reintroduced and creation of CSA Departments/Stations in each state; increased budget allocation to a minimum of 10% for agriculture, revitalisation of Researchers-Extension Agents-Farmers Linkage, employment of qualified extension agents and retraining of extension agents.

The purpose of this study is to unravel the changing nature of climate change impact on the food and human security sector of the Nigerian State.

This study is an in-depth case study that involves the use of both quantitative and qualitative data. Statistical data on climate variability in Nigeria obtained from reliable databases were use in the making of analysis. Also, data derived from semi-structure interviews and special reports from International Non-governmental organizations on the subject matter were also used in the study. The findings of the study were based on an in-depth analysis of both primary and secondary sources of data. The secondary data were derived from existing published academic works. The primary data was developed using qualitative data that were collected from January to November, 2018 to 2019 in the different regions of Nigeria. For the South East, primary data was collected from Abakaliki, Ebonyi State. In the South-South, primary data was collected from Asaba, Delta State. In the South West, primary data was collected from Barutin, Kwara State. In the North East, primary data was collected from Maiduguri, while in North West, data was collected from Gusau, Zamfara State. In the North Central, data was collected from Markurdi, Benue State. During the data collection, 48 semi-structured Key Informant Interviews (KIIs) were carried out in the six selected research areas that represented their geo-political zones. Six Focus Group Discussions (FGDs) were carried out, one for each of these six selected cities. Each of the Focus Group Discussions comprised between five and seven respondents. The idea of KIIs and FGDs is to allow the respondents to freely express their ideas comprehensively. Again, in other to get varied forms of responses, the respondents are mainly farmers however, a number of NGOs, civil servants, fertilizer sellers, government officials, transporters and aged men and women/retirees. It should be noted that the respondents cut across male and female gender of all ages and ethnic configuration. The respondents were also randomly selected through social networking. To avoid having people of similar The KIIs were three academics; two community leaders; two small scale fish farmers; rice, cassava, fish, livestock and crop farmers. All KIIs ad TIs were transcribed and analysed using thematic content analysis.

The findings revealed that climate change has negatively affected food security in Nigeria. it has also led to continuous armed confrontations over natural resources thereby undermining human security in the country.

This study is 100% original and can be assessed through turn it in evaluation.