Introduction: Sesame is an important cash crop that can be grown with limited resources. In recent decades it has drawn interests of many researchers and developers. This study analyzed the economics of Sesame (Sesamum indicumL.) produced in northern region of the Republic of Benin.Methods: Structured questionnaire was used to gather primary data from 120 farmers who made up the sample size and were chosen using a multistage sampling technique. Data were analyzed using descriptive statistics, profitability analytical tools, multiple regression analysis and Likert scale rating technique. Profitability analytical tools were used to assess the economic performance of the sesame production; a multiple regression model was used to analyze factors that determine the output of the production in the study area; a 5-point Likert scale rating technique was utilized to rank the production's challenges according to farmers' observations.Results: The findings revealed that sesame is mainly produced in sole cropping system and in rotation with other crops. The net farm income analysis showed that sesame farming was a profitable venture in the study area. The study also showed that factors like age, household size, crop rotation, and capital input influence the revenue of sesame production. While age, household size and capital input have a beneficial and significant influence on the farms' net revenue from sesame produce, crop rotation has a negative effect on it. Amongst the various constraints identified, the most significant ones are access to labor and land, uneven ripening, lack of storage facilities and access to improved seed.Discussion: Based on these results, authorities in agricultural sector should develop and promote this value chain at the national level as it will greatly boost the country's economy.

Rice plays a major role in the fight against food insecurity in developing countries such as Benin. The objective of this research is to evaluate the determinants of technical efficiency, the factors influencing this efficiency, as well as the constraints related to rice production in Benin. The technical efficiency levels were obtained from the Data Envelopment Analysis (DEA) method and were regressed in a Tobit regression model to assess the determinants of the efficiency of rice producers. Production constraints were identified using Kendall’s W concordance test and descriptive statistics. The technical efficiency rate obtained was 51%. Inferential analysis showed that parameters such as the age of the rice producer, household size, the amount of agricultural credit obtained, and the use of inputs impact the technical efficiency of rice production. In addition, most rice producers suffer from limited access to agricultural credit and adequate agricultural equipment, while their production is subject to climatic hazards. Agricultural development policies related to the determinants of the technical efficiency of rice production should be formulated in order to improve the efficiency of the producers in Benin Republic.

Globally, agriculture is facing significant challenges due to climate change, which is seriously affecting grain yields. This research aims to analyze the significant effect of climate change (temperature and rainfall) on cereal production in Benin. The choice of Benin is explained by its strong dependence on agriculture and its vulnerability to climatic variations. This study employed climate and agricultural data from FAO and ASECNA (1990–2020) to evaluate the impacts of climate change on cereal production. SARIMA time-series models were used for forecasting, while the PLS-SEM approach assessed the relationships between climate variables and cereal production. The findings reveal a rise in temperatures and a gradual decline in precipitation. Despite these challenges, the time-series analysis suggests that Beninese farmers are expanding cultivated areas, successfully increasing production levels, and improving yields. Projections to 2050 indicate an increase in areas and production for maize and rice, while sorghum shows a constant trend. However, even with these projections, it is recommended to explore, in more depth, the resilience strategies used by cereal producers to better understand their influence and refine the orientations of future agricultural policies.

This study delves into the intricate nexus of climatic, demographic, economic, and environmental variables, collectively shaping the availability of animal protein in Europe and Asia. The study analyzes interrelationships and reveals compelling outcomes. Notably, the global phenomenon of climate change, unmistakably linked to human activities, surfaces as a pressing concern. Temperature escalation, manifesting with regional nuances, underscores the urgency of collective efforts to combat climate impact, particularly pronounced in areas like Indonesia and the Mediterranean. This underscores the imperative for immediate collaborative action to ameliorate climate consequences. Meanwhile, the surging emissions of CH₄, CO₂, and N₂O pollutants, primarily from industrial and agricultural sectors, pose a critical challenge. This mandates robust regulation within global environmental strategies and ongoing dialogues. In the realm of demography, relentless global population growth exerts formidable stress on natural resources and animal reserves. This burgeoning populace poses formidable tests for ensuring forthcoming food security and sustained animal protein availability. Economic analyses disclose variances in national gross incomes and animal protein prices, reflecting geographic distinctions. Heightened incomes signify enhanced purchasing power, while price oscillations correlate with health issues like avian flu. Multivariate analyses employing mixed linear regression models unveil the profound influence of select parameters such as temperature, pollutant emissions, population density, and production indicators on animal protein availability. This underscores the pivotal role of these factors in devising comprehensive food and environmental policies. Projections for forthcoming years anticipate augmented animal protein availability in certain Asian regions (Indonesia and Japan), though still beneath requisite demands, juxtaposed against a gradual decrement in Europe. Faced with these realities, the necessity to cultivate innovative strategies with alternative solutions comes to the fore. Exploring dairy and plant-based protein substitutes can meet rising demands while conserving the environment and public health.

Geospatial technologies like Remote Sensing (RS) and Geographic Information Systems (GIS) provide a platform for swiftly evaluating terrestrial Carbon Stock (CS) across extensive regions. Employing an integrated RS-GIS method for estimating Above-Ground Biomass (AGB) and precise carbon management emerges as a timely and economical strategy for implementing effective management plans on a localized and regional level. This study reviews different RS-related techniques utilized in CS assessment, particularly in arid lands, shedding light on the challenges, opportunities, and future trends associated with the process. As global warming poses adverse impacts on major ecosystems through temperature and precipitation changes, professionals have a call to develop evidence-based interventions to mitigate them. Carbon sequestration involves harnessing and storing carbon stocks from the atmosphere to minimize the adverse effects of climate change. The review explores the effectiveness of integrating remote sensing and GIS methodologies in quantifying carbon sequestration within agroforestry landscapes. In addition, this review also assesses the traditional methods, including their limitations, and deeply delves into recent techniques, emphasizing key remote sensing (RS) variables for biophysical predictions. This study showcases the efficacy of geospatial technologies in evaluating terrestrial carbon stock, particularly in arid regions. The study reviews diverse techniques and sensors, like optical Radio Detection and Ranging (RADAR), and Light Detection and Ranging (LiDAR), extensively employed for above-ground biomass (AGB) estimation and carbon stock assessment with RS data, introducing and discussing new methods. Existing literature was examined to present knowledge and evidence on the effectiveness of these technologies in carbon sequestration. The key findings of this review will inform future research and integration of technology, policy formulation, and carbon sequestration management to mitigate the impacts of climate change.