Food And Agriculture Organization Research Articles

Is the concentration of heavy metals in sun-dried Engraulicypris sardella (Günther, 1868) in Malawi, a human health risk?

The effects of trophic cascades have made small-size pelagic fish species, such as Engraulicypris sardella, from Lake Malawi an important ecological and food system. However, human-induced activities can potentially pollute Lake Malawi exposing E. sardella to heavy metals contamination. This could pose a food system health risk to the population of Malawians and neighboring countries, which heavily rely on fish as a source of animal protein. Therefore, this study investigated the concentration levels of Lead (Pb), Cadmium (Cd), Zinc (Zn), Copper (Cu), Manganese (Mn), and Iron (Fe) in sun-dried E. sardella and conducted a health risk assessment associated with its consumption. E. sardella samples were collected from Karonga, Nkhata Bay, Nkhotakota, Salima, and Mangochi districts in Malawi between December 2023 and February 2024. The results revealed significant variations in Cd, Zn, Cu, Mn, and Fe concentrations among the sampled sites while Pb contamination was not detected. The concentrations of Zn, Cu, Mn, and Fe in E. sardella were within acceptable consumption limits set by the Food and Agriculture Organization (FAO) and the World Health Organization (WHO) in 2012. However, the fish's average Cd levels (0.17 mg kg−1 ww) were slightly above the recommended threshold of 0.1 mg kg−1 ww by FAO/WHO (2012) but remained below the limit of 0.5 mg kg−1 ww set by FAO in 1983. Furthermore, none of the analyzed heavy metals posed a health risk effect to people. Therefore, there is a need for regular monitoring of heavy metal concentrations in E. sardella and other mostly consumed fish species from Lake Malawi, both fresh and processed, for a sustained guarantee of the safety of the fish consumers.

Trend TSR 20 rubber prices between producing countries in Southeast Asia

Natural Rubber is one of the world's largest commodities used for industrial needs. The price of TSR 20 rubber continues to fluctuate, which has a significant impact on some farmers in various countries. This study analyzes the price trend of TSR 20 rubber in Southeast Asia. The purpose of this study is to analyze trends and fluctuations in STR 20 rubber prices in Southeast Asia, such as Standar Thailand Rubber (STR 20), Standar Indonesia Rubber (SIR 20), Standar Vietnam Rubber (SVR 20), and Standar Malaysia Rubber (SMR 20) for 72 months from January 2017 - December 2022. This research uses trend analysis with simple linear regression method. This research uses the historical method by conducting research on a source which is then critically analyzed. Data collection techniques are obtained by tracing data and documents that have been stored by agencies including the Ministry of Agriculture, Ministry of Trade, International Rubber Study Group (IRSG), Singapore Commodity Exchange (SICOM), Association of Natural Rubber Producing Countries (ANRPC), Food and Agriculture Organization (FAO), The World Bank, and Gapkindo as well as existing literature and sites. The results obtained are positive trends where each development between countries has experienced a positive price increase, such as, STR 20 has a polynomial line equation Y = 0.0331x2 – 95,28x + 68596, then SIR 20 Y = 0.0231x2 -66,443 + 47966, SVR 20 Y = 0,0301x2 – 86,824x+ 62648, and SMR 20 Y = 0,0279x2 – 80,411x + 58010.

Coupled weather and crop simulation modeling for smart irrigation planning: a review

ABSTRACT Efficient irrigation scheduling is essential for optimizing crop yields and water-use efficiency. This review examines crop simulation models and methods for improving irrigation management, with a focus on integrating weather forecast data. The FAO (Food and Agriculture Organization) developed models such as AquaCrop, WOFOST (WOrld FOod Studies), DSSAT (Decision Support System for Agrotechnology Transfer), and APSIM (Agricultural Production Systems sIMulator), exploring the incorporation of forecasted ETo (reference evapotranspiration) calculated based on forecasted values of weather through the Penman-Monteith method and rainfall data into the models using modified rule-based approaches with various forecast horizons, which enhances irrigation planning. Optimization methods, including genetic algorithms coupled with crop models, are also assessed and have shown significant water savings and profit gains compared with traditional farming practices. Emerging real-time irrigation scheduling tools, including simulation-optimization, field data assimilation, and human–machine interactions, further improve productivity and water conservation. Studies have also shown that web-based decision support using satellite remote sensing and crop models can be used to effectively monitor crop water status and predict real-time irrigation needs. Ongoing innovations like coupling crop models with optimization techniques, weather forecasting, remote sensing, and recommendations based on field experiments have shown promise for transforming irrigation planning and management.

Dietary free L-glutamate contributes to maintaining a low sodium intake among Vietnamese.

The World Health Organization (WHO) and the Food and Agriculture Organization (FAO) recommend the consumption of less than 2,000 mg of sodium/day to reduce blood pressure and the risk of conditions such as cardiovascular disease and coronary heart disease. The sodium intake among Vietnamese was reported to be 7,200 mg/d or more. Free L-glutamate enhances flavor when it is added to food and improves the taste of sodium-reduced foods. This study aims to investigate whether the intake of free L-glutamate-rich seasonings contributes to maintaining a low sodium intake in a cross-over study. From a total of 145 subjects, 42 participants were screened for participation in the cross-over design study. Subjects were randomly allocated to the Low free L-glutamate group (Low free L-Gl) and the Normal free L-glutamate group (Normal free L-Gl). Both received a direct educational guideline to reduce sodium intake. The Low free L-Gl group started with a restriction in the variety of free L-glutamate-rich seasonings, and the Normal free L-Gl group had no restriction in the variety of seasonings. Blood pressure was measured at week 0 (baseline), week 2, week 4, and week 6, while body weight, height, urine sodium and potassium excretion, chromogranin-A (CgA pmol/mg protein) from saliva, and free L-glutamate from food were measured at week 0, week 3, and week 6. In Low free L-Gl, the amount of free L-glutamate in food decreased significantly from baseline to week 6 (p < 0.00), while it did not change in the Normal free L-Gl (p > 0.05). However, the reduction of sodium excretion at week 6 was 22% in Low free L-Gl (5,875 mg/d vs. 4,603 mg/d, p < 0.01) and 46% in Normal free L-Gl (6,107 mg/d vs. 3,277 mg/d, p < 0.00), both lower than the baseline. CgA (pmol/mg protein) did not show any difference between the two groups. The group with Normal free L-Gl intake showed a 46% reduction in sodium excretion by week 6 compared to the baseline. This suggests that the consumption of L-glutamate-rich seasonings when complemented with direct educational guidelines, can contribute to maintaining a low sodium intake.

Occurrence of Abiotic and Biotic Stress Tolerance in Rice: A Multigene Approach

A sustainable food system ensures food security and nourishment for future generations. Rice (Oryza sativa L.) requires emergence stress tolerance for successful cultivation in germination and early establishment stages. According to the FAO (Food and Agriculture Organization) study, rice is one of the most important worldwide cereal crops and a staple food for more than half of the world’s population. Over the past few years, drastic climatic changes have been subjected to many abiotic and biotic stresses. Global estimates express that a total of 1000 million hectares of cultivated land is affected by abiotic and biotic stress. Besides this around 30% of the irrigated land area is also disturbed. This review discusses the mechanisms of stress-tolerant variants and understanding the recent developments of complex tolerance phenomena. Here, we have compiled the logical pieces as evidence of successful applications of potent molecular tools for boosting stress tolerance in rice, their prospects and limitation. This information would help researchers better understand the genetic enhancement of stress tolerance in rice.

A conceptual framework for characterization of agricultural heritage in desert-prone areas

PurposeThis study aims to propose a comprehensive conceptual framework for the characterization of agricultural heritage in desert-prone areas, with a focus on Siwa Oasis in Egypt.Design/methodology/approachThe research utilizes a multidimensional approach, integrating perspectives from sustainability principles, stakeholders and the agricultural heritage frameworks of the United Nations Educational, Scientific and Cultural Organization (UNESCO) and Food and Agricultural Organization (FAO). It involves thematic analysis of qualitative data collected through focus group discussions and interviews with a diverse range of participants, including community members, government officials, nongovernmental organizations (NGOs) and researchers.FindingsThe study identifies five key elements of agricultural heritage in Siwa Oasis: cultural, ecological, economic, social and scientific. Cultural elements include traditional farming practices, irrigation systems and architectural features, while ecological elements encompass crop biodiversity, wildlife habitats and traditional landraces. Economically, date palm cultivation, olive production and agritourism activities play crucial roles in livelihood security and local economies. Socially, community cohesion, gender roles and cultural practices shape the social fabric of the oasis, with festivals and rituals fostering a sense of belonging. From a scientific perspective, the integration of traditional knowledge with modern agricultural practices enhances sustainability and resilience.Research limitations/implicationsThe study focused solely on Siwa Oasis as a case study, limiting generalizability to other desert-prone areas. Further research could explore additional regions to enhance the understanding of agricultural heritage in diverse contexts. Additionally, the qualitative nature of the study may limit statistical analysis. Future studies could employ mixed-methods approaches for a more comprehensive understanding of agricultural heritage dynamics.Practical implicationsUnderstanding the multifaceted aspects of agricultural heritage in Siwa Oasis can inform sustainable development initiatives, tourism planning and cultural preservation efforts. Local policymakers and stakeholders can utilize these insights to develop policies that support traditional farming practices, ecotourism and community development. Furthermore, the promotion of agricultural heritage can enhance economic opportunities, food security and environmental sustainability in desert-prone regions.Social implicationsRecognition of the social elements embedded within Siwa Oasis’s agricultural heritage highlights the importance of community cohesion, gender roles and cultural practices. By acknowledging and preserving these aspects, initiatives can be developed to empower local communities, promote gender equality and preserve cultural identity. Such efforts can enhance social cohesion, strengthen cultural bonds and promote inclusivity in the development agenda of desert-prone areas.Originality/valueThis study contributes a novel conceptual framework that bridges multifunctionality concepts, sustainability principles and stakeholder perspectives to characterize agricultural heritage in desert-prone areas. It offers insights into the complex interplay of cultural, ecological, economic, social and scientific dimensions of agricultural heritage systems.

Assessing Soil and Land Suitability of an Olive–Maize Agroforestry System Using Machine Learning Algorithms

Exponential population increases are threatening food security, particularly in mountainous areas. One potential solution is dual-use intercropped agroforestry systems such as olive (Olea europaea)–maize (Zea mays), which may mitigate risk by providing multiple market sources (oil and grain) for smallholder producers. Several studies have conducted integrated agroforestry land suitability analyses; however, few studies have used machine learning (ML) algorithms to evaluate multiple variables (i.e., soil physicochemical properties and climatic and topographic data) for the selection of suitable rainfed sites in mountainous terrain systems. The goal of this study is therefore to identify suitable land classes for an integrated olive–maize agroforestry system based on the Food and Agriculture Organization (FAO) land suitability assessment framework for 1757 km2 in Khyber Pakhtunkhwa province, Pakistan. Information on soil physical and chemical properties was obtained from 701 soil samples, along with climatic and topographic data. After determination of land suitability classes for an integrated olive–maize-crop agroforestry system, the region was then mapped through ML algorithms using random forest (RF) and support vector machine (SVM), as well as using traditional techniques of weighted overlay (WOL). Land suitability classes predicted by ML techniques varied greatly. For example, the S1 area (highly suitable) classified through RF was 9%↑ than that of SVM, and 8%↓ than that through WOL. The area of S2 (moderately suitable) classified through RF was 18%↑ than that of SWM and was 17%↓ than the area classified through WOL; similarly, the S3 (marginally suitable) class area via RF was 27%↓ than that of SVM, and 45%↓ than the area classified through WOL. Conversely, the area of N2 (permanently not suitable class) classified through RF and SVM was 6%↑ than the area classified through WOL. Model performance was assessed through overall accuracy and Kappa Index and indicated that RF performed better than SVM and WOL. Crop suitability limitations of the study area included high elevation, slope, pH, and large gravel content. Results can be used for sustainable intensification in mountainous rainfed regions by expanding intercrop agroforestry systems in developing nations to close yield gaps.

Elemental Composition and Health Risk Assessment of Deep-Sea Teleost's of the Levantine Basin.

The determination of metal(loid) (As, Fe, Al, Sr, Zn, Pb, Mn, Cu, Cr, and Cd) levels in the muscle tissue of 23 different deep-sea bony fish sampled off Mersin Bay (NE Levantine Basin) and the assessment of health risks for human consumption were aimed. Tissue metal(loid) concentrations were determined as dry weight and analyzed by inductively coupled plasma mass spectrometry (ICP-MS). The tissue metal(loid) concentrations (µg g dw) were converted to wet weight prior to health risk assessment calculations. Standard mathematical formulas were used to determine the health risk assessment. There was a statistically significant difference between the fish species in terms of tissue metal(loid) levels (p < 0.05). The highest metal(loid) level was found in C. sloani among other species. As and Fe had the highest and Cd the lowest tissue concentrations in the examined species (p < 0.05). The relationships between the metal(loid)s analyzed in the tissue were significant (p < 0.01;0.05). Fe had an antagonistic effect with Cd, while other metal(loid)s had a synergetic effect with each other. Risk assessment analyses were performed for the consumable species, and it was found that the estimated daily and weekly intakes were below the tolerable limits established by the Food and Agriculture Organization (FAO) and the World Health Organization (WHO). The target hazard quotient (THQ) values exceeded the threshold of 1 (THQ > 1) only for As. The target cancer risk (TCR) was below the tolerable limits (> 10-5) except for As, Cd, and Al.

Agro-Silvo-Pastoral Heritage Conservation and Valorization—A Comparative Analysis of the Chinese Nationally Important Agricultural Heritage Systems and of the Italian Register of Historical Rural Landscapes

Agricultural heritage systems are receiving increasing attention due to their multifunctional role, their capability to provide ecosystem services, and for representing sustainable development models for rural areas. At the international level, the Food and Agriculture Organization (FAO) of the United Nations launched in 2002 the Globally Important Agricultural Heritage Systems (GIAHS) Program to identify and safeguard traditional agro-silvo-pastoral systems that are the result of the adaptation of rural communities to the surrounding environments. Following this approach, similar national programs have been developed, among which the Italian National Register of Historical Rural Landscapes and the China Nationally Important Agricultural Heritage Systems (China-NIAHS) initiative stand out. This research compares the China-NIAHS initiative and the Italian Register of Historical Rural Landscapes, highlighting similarities and differences and identifying strengths and weaknesses, to contribute to the development of proper tools for the conservation and valorization of agricultural heritage systems. Both initiatives were established in 2012 and share similar aims and inscription criteria, including historical and current significance, knowledge system and social structure, economic and productive framework, and causes of vulnerability. The main differences are related to the delimitation of the boundaries of the proposed sites and to the inscription process; in addition, while for the Italian National Register spatial analyses of land-use changes and landscape structure are mandatory according to a precise methodology, for the China-NIAHS no specific landscape analyses are required. The main critical issues are the lack of public participation and the lack of a monitoring plan after the inscription. The absence of monitoring is also the main vulnerability of the FAO GIAHS Programme. This research can offer important information for different stakeholders at the international, national, and local levels dealing with agricultural heritage conservation and valorization. In particular, it highlights the need of developing a multidisciplinary monitoring system with a standard methodology based on different indicators that can contribute to maximizing the impact of these initiatives. This research also provides useful information for the countries that are interested in developing a national initiative for agricultural heritage systems’ identification and valorization/conservation or for countries that intend to improve their national programs.

Hierarchical-modular framework for habitat mapping through systematic and informed integration of remote sensing data with contextual information

Accurate and up-to-date habitat maps at national or regional levels are critical for informing conservation and restoration actions. Land cover maps generated from Earth Observation (EO) data can, to varying degrees, indicate the extent of some habitat categories but these are often insufficient in terms of the level of detail required. This study introduces a hierarchical-modular framework based on the globally applicable Food and Agriculture Organization (FAO) Land Cover Classification System (LCCS) whereby the land cover classes can be systematically translated to habitat categories and further differentiated by referencing contextual information and expert knowledge. Application is showcased for Wales (United Kingdom) where 10 m spatial resolution land cover maps were first constructed nationally from time-series of Sentinel-1C-band radar and Sentinel-2 optical data (2018–2020). The contextual datasets derived from non-EO sources were utilised to associate dominant vegetation types to detailed habitat classes.The accuracy assessment done using field survey data highlights that habitat classes directly derived from EO, including cultivated/managed and forest types, demonstrated higher mapping accuracies (>70% User's and Producer's Accuracies) compared to those that were more heavily dependent on non-EO-derived contextual information. These included neutral grasslands and fen/marsh/swamp that demonstrated lower accuracies (<20%) but also other detailed wetland classes (user's and producer's accuracies ranging from 25 to 60%). These reduced accuracies were largely associated with discrepancies in the contextual datasets used for their differentiation and mapping, and those integrated within field validation datasets. Dependency on contextual datasets diminished as detailed habitat maps were generalized into broader categories. The study proposes that, for enhanced habitat mapping, efforts should focus not only on EO data but also on maximising the accuracy and minimizing inconsistencies in contextual datasets as well as taxonomical systems. The flexible structure of the FAO LCCS hierarchical framework is also highlighted, emphasizing its adaptability for future improvements in habitat mapping by incorporating contextual datasets and more advanced algorithms that can improve EO-derived land cover descriptions.

A survey on the knowledges, attitudes, behaviours and practices of goat farmers about peste des petits ruminants disease in goats at Haor and bordered areas in Sylhet district of Bangladesh.

Contagious and economically devastating, peste des petits ruminants (PPR) is a viral disease affecting goats and sheep, causing significant losses in livestock productivity and posing a threat to food security and rural livelihoods worldwide. This study was conducted to assess the status of goat farmer's knowledge, attitude and practice (KAP) about PPR disease at Sylhet district of Bangladesh. A comprehensive cross-sectional survey, conducted over 11 weeks, targeted 130 goat owners. Following a pilot study with 20 farmers, a set of 17 validated questions on PPR KAP was validated. Data collection was performed through face-to-face interviews by a trained team using KOBO Toolbox, with interpretation of responses based on established thresholds for knowledge (>65%), attitude (>75%) and practice (>70%). Overall, 67.7% of participants demonstrated a good level of knowledge about PPR disease. Males exhibited 1.42 times higher odds of knowledge compared to females (odds ratio=1.42). The middle age group (31-45 years) showed significantly higher knowledge levels (83.3%, p<0.001). Within this age group, positive practice levels were also notably higher (54.8%). Those with a higher secondary education background exhibited the most positive practice levels (>80%). Participants whose additional income came from non-governmental organization employment showed a higher positive practice level (71.4%), 1.46 times higher than other income sources. Strategic interventions should prioritize female farmers, educational empowerment and collaboration with non-governmental organizations to bolster livestock health and rural livelihoods in Bangladesh as part of national PPR control strategy to fulfil the goals of Office International des Epizooties/World Organization for Animal Health (OIE/WOAH) and Food and Agriculture Organization (FAO) PPR eradication by 2030.

Do green finance and digital technology matter for sustainable agricultural development? Insights from sub-Saharan Africa

Sustainable agricultural progress is one of the world’s greatest challenges in the twenty-first century as the global population is estimated to rise to over nine billion by 2050. Over the years, the Food and Agricultural Organization (FAO) and the African Union (AU) have sought prosperous African Policies based on sustainable agriculture and inclusive growth. Additionally, the AU has adopted the Comprehensive African Agricultural Development Programme (CAADP) policy framework. Given the growing need for innovative policies and studies to reduce the negative environmental effects of agricultural development in Africa, this paper investigates the significance of green finance and digital technologies on green agricultural growth in sub-Saharan Africa (SSA) from 2003 to 2018. Analysis of panel co-integration estimates indicates all variables are integrated. Using the panel-corrected standard errors estimator for long-run equilibrium co-integration assessment, the outcomes indicate mitigated green finance (MGF), internet and mobile phone use (IMU), as well as sustainable energy utilization (RE), individually and collectively exert a positive effect on agriculture, forestry and fishing value added (AVA). Additionally, panel causality estimates indicate (i) a bi-directional causality between MGF and AVA. (ii) A uni-directional causality running from IMU towards AVA without any rebound effect. For policy insights, the AU could urge member states to implement macro-policies to increase agricultural green credit to sustain food production and employment generation. Similarly, the FAO and AU could provide technical support in digital agricultural research and value chains towards ensuring sustainable agriculture development in SSA.

Assessing Food Loss and Waste in Chile: Insights for Policy and Sustainable Development Goals

The Food and Agriculture Organization (FAO) reports that Latin America and the Caribbean experienced the most rapid rise in food insecurity, with approximately 47.7 million individuals in the region affected by hunger in 2022. In Chile, almost three million people, 15.6% of the country’s population, do not have regular access to sufficient nutritious food and suffer from some form of food insecurity. Moreover, Chile is particularly susceptible to the impacts of climate change and contends with the depletion of several critical natural resources, notably water, stemming from severe and prolonged drought conditions. This article aims to comprehensively evaluate food loss and waste (FLW) in Chile and analyzes the implications of FLW on the sustainable development goal (SDG). This will be achieved by utilizing a top-down mass balance methodology that integrates various data sources and an in-depth analysis of the main food categories at different stages of the food supply chain (FSC). In 2021, Chile generated 5.18 million tons of FLW, with fruit being the largest contributor at 2.5 million tons (48% of total FLW). Vegetables accounted for 0.8 million tons (16%). Other food groups each contributed 1% to 10% of the total FLW. Per capita FLW was 295 kg. FLW varied by food group and FSC stage. Fruits, vegetables, starchy roots, and pulses had the most FLW early in the FSC, while cereals had it later. Comparing FLW with the domestic supply quantity of food, it is observed that 68% of the fruit available for the population was discarded. Vegetables and starchy roots also showed significant volumes of discarded food, with 48% and 29% of the availability of these products in Chile. Furthermore, we explore the implications of FLW on realizing SDG 2—zero hunger, particularly emphasizing its correlation with target 12.3. The research underscores the potential of its findings to significantly shape public policies and strategies concerning FLW and their alignment with the associated SDGs, making a tangible impact on the lives of millions.

Egg protein exposure estimation in risk assessment for Japanese food allergy labeling

To assess the risk of food allergies in foods processed under the Japanese food labeling system, estimating exposure to hidden allergens is necessary. We assessed exposure to egg protein in foods processed according to the Japanese food labeling system. First, we estimated the concentration distribution of egg protein by Bayesian methods using data from the literature and the measurement of food products with precautional declarations in the labeling margin. We then estimated the food-intake portion-size distribution under two scenarios: soft drink consumption as an example of single, high-intake consumption, and confections, which are frequently consumed by children, as a realistic example of low-intake consumption. Finally, we estimated the distribution of unexpected intake of egg proteins in the form of single consumption. The mean exposure to egg protein under the high-intake scenario was estimated to be 0.0164 mg for 1–15-year-olds, 0.0171 mg for 4–15-year-olds, 0.0181 mg for 7–15-year-olds, and ≥0.0188 mg for 16-year-olds. The mean exposure to egg protein under the low-intake scenario was estimated to be 0.0018 mg for 1–15-year-olds, 0.0019 mg for 4–15-year-olds, 0.0020 mg for 7–15-year-olds, and ≥0.0022 mg for 16-year-olds. Compared to the reference dose of 2.0 mg proposed by the Joint the Food and Agriculture Organization (FAO)/World Health Organization (WHO) Expert Committee, the risk of onset of food allergies due to egg protein contamination from foods without egg labeling is considered to be extremely low under the current Japanese food labeling system.

Estimating fisheries catch from space: Comparing catch estimates derived from AIS fishing effort with reported catches for Indian Ocean industrial fisheries

Indian Ocean Rim countries (IOR) rely on fisheries for socio-economic well-being and food security. Monitoring fisheries equipped with Automatic Identification Systems (AIS) enables the evaluation of fishing activities. However, only small fractions of large vessels use AIS, and increasingly vessels are avoiding or circumventing AIS use. We used Global Fishing Watch AIS fishing effort data for 2018–2020, combined with independently derived gear- and country-specific catch rates to estimate catch volumes by AIS equipped industrial vessels in the Indian Ocean. We compared these estimates to the catches reported by countries to the Food and Agriculture Organization (FAO), which represent global accountability. Results suggest that AIS-equipped industrial vessels caught an average of 400,000 t∙year−1, of which 57% was by Distant-Water Fishing (DWF) vessels from countries outside the region. Spain, France and South Korea had AIS derived catch estimates substantially lower than catches officially reported by these countries, suggesting these vessels may turn off AIS transponders to potentially elude detection either by authorities or for other operational reasons. In contrast, Taiwan and China had 6 and 4 times more AIS estimated catches than they reported to the FAO. This suggests that these countries may not meet their international reporting obligations. Underreporting fisheries catches undermines management efforts and contributes to the unsustainable use of marine resources. Our study revealed an important role AIS technology can play in estimating fishing activities in the Indian Ocean, despite its currently limited adoption and the increasing evasion tactics by some fleets. Discrepancies between AIS-derived catch estimates and officially reported data underline the challenges in fisheries monitoring and enforcement, and highlight the lack of compliance enforcement by many flag countries.

Dual effects of additional food supply and threshold control on the dynamics of a Leslie–Gower model with pest herd behavior

Bemisia tabaci is a major agricultural pest and recognized by the United Nations Food and Agriculture Organization (FAO) as the second largest pest in the world. This paper aims to study the management of Bemisia tabaci from theoretical aspects. Firstly, considering the omnivorous nature of natural enemy species and pest herd behavior, a Leslie–Gower type pest-natural enemy model with additional food supply and non-differentiable rational uptake function is put forward, and the effects of additional food supply and aggregation efficiency on the dynamical behavior of the system are analyzed. Secondly, for the slowness of pest control by natural enemy species, a threshold control strategy is adopted to prevent the spread of Bemisia tabaci by spraying a certain intensity of insecticides and releasing a certain number of natural enemies. The complex dynamics of the system induced by the threshold control are discussed such as the existence of predator-extinction periodic solution, the existence and stability of coexisting order-1 periodic solution. Thirdly, from the perspective of cost control, an optimization problem is constructed based on the existence of the order-1 periodic solution, and the optimal control threshold, control strength and control frequency are determined. At last, to illustrate the theoretical results more intuitively, the numerical simulations in MATLAB program are presented to illustrate the effectiveness and practical significance of the control measures. The results of this study provide a reference for the scientific and reasonable management of Bemisia tabaci and is helpful to realize the sustainable development of agricultural production.

Maize yield prediction and condition monitoring at the sub-county scale in Kenya: synthesis of remote sensing information and crop modeling

Agricultural production assessments are crucial for formulating strategies for closing yield gaps and enhancing production efficiencies. While in situ crop yield measurements can provide valuable and accurate information, such approaches are costly and lack scalability for large-scale assessments. Therefore, crop modeling and remote sensing (RS) technologies are essential for assessing crop conditions and predicting yields at larger scales. In this study, we combined RS and a crop growth model to assess phenology, evapotranspiration (ET), and yield dynamics at grid and sub-county scales in Kenya. We synthesized RS information from the Food and Agriculture Organization (FAO) Water Productivity Open-access portal (WaPOR) to retrieve sowing date information for driving the model simulations. The findings showed that grid-scale management information and progressive crop growth could be accurately derived, reducing the model output uncertainties. Performance assessment of the modeled phenology yielded satisfactory accuracies at the sub-county scale during two representative seasons. The agreement between the simulated ET and yield was improved with the combined RS-crop model approach relative to the crop model only, demonstrating the value of additional large-scale RS information. The proposed approach supports crop yield estimation in data-scarce environments and provides valuable insights for agricultural resource management enabling countermeasures, especially when shortages are perceived in advance, thus enhancing agricultural production.

Drivers of Food Waste Reduction Intention Among Indonesian Young Generation

Solid waste management presents a significant challenge in Indonesia, with food waste accounting for 40.8% of all solid waste generated. The young generation is the largest producer of food waste compared to adults. The Food and Agriculture Organization (FAO) reports that consumer behavior is the main factor causing food waste in middle-income countries. Considering that the younger generation occupies 24.34% of Indonesia’s population, this study aimed to analyze the determinants of food waste reduction intention among the young generation in Indonesia. The Extended Theory of Planned Behavior (TPB) with four new introductory variables was used as a theoretical framework to understand the intentions of the young generation in Indonesia regarding food waste reduction. Data was collected from the young generation spread across Indonesia through an online survey using questionnaires, which resulted in 340 respondents. Data were then analyzed using descriptive analysis and partial least squares-structural equation modeling (PLS-SEM) to test the conceptual model and hypotheses proposed. The results showed that perceived behavioral control (PBC), food consumption, level of religious knowledge, and level of knowledge significantly influence food waste reduction intention. Religious knowledge was the most influential predictor. This is in line with the nature of the Indonesian community, which is highly religious, and religion profoundly guides daily lives. Based on the results, this study recommended three practical implications for reducing food waste and is expected to contribute to ensuring food security and achieving the Sustainable Development Goals.

Unveiling Climate Trends and Future Projections in Southeastern Brazil: A Case Study of Brazil’s Historic Agricultural Heritage

The intricate relationship between climate and society in a given region demands a profound understanding of climate patterns, especially in agricultural areas like Diamantina, Minas Gerais (MG), recognized by the Food and Agriculture Organization (FAO) as the birthplace of the first Globally Important Agricultural Heritage System (GIAHS) in Brazil, situated in the southwest region of the country. Given the growing concerns about climate change, we conducted a meticulous analysis of the climatic characteristics of Diamantina-MG. To achieve this, we examined historical meteorological data from 1973 to 2022, employing the Mann–Kendall and Sen’s slope tests to analyze trends. Additionally, we utilized three global climate models (GCMs) under different shared socioeconomic pathways (SSPs) to predict future climate scenarios (2021–2100) based on the projections of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Furthermore, we used Köppen and Thornthwaite climate classification methodologies to characterize both the current and future climate conditions of the region. Our results indicate that, historically, Diamantina-MG has experienced significant increases in minimum temperature, indicating a warmer climate in recent decades. For temperature, the projections show a consensus among models, projecting a continuous increase, potentially reaching up to 5.8 °C above the historical average temperature (19.2 °C) by the end of the century. Regarding rainfall projections, they show greater uncertainty, with discrepancies among models observed until 2060. However, specifically for the second half of the century (2060–2100), the models agree that there will be increases in annual rainfall. Regarding the climatic types of the region, we found that the current Köppen Cwb and Thornthwaite B3rB’3a’ classifications could shift to Aw and B1wA’a’, representing a humid tropical savanna climate with longer periods of water deficiency, considering the impacts resulting from increased air temperature and evapotranspiration. In summary, the study’s results indicate that climate changes are occurring and are likely to intensify in the Jequitinhonha Valley region, MG, in the future. The analysis of these data, from the perspective of the Brazilian GIAHS sustainability, reveals the importance of considering adaptation and mitigation measures to ensure the resilience of agricultural systems and local communities in the region that face these significant environmental changes.

Current Challenges and Future Outlook: Trends and Forecasts in the Mariculture Sector

Aquaculture, defined by the United Nations Food and Agriculture Organization (FAO), encompasses the farming of aquatic organisms for food production, offering a promising solution to global food security challenges. Over the past three decades, global aquaculture production has consistently grown at approximately 8% annually, outpacing other major animal food production sectors. Mariculture, a subset of aquaculture focusing on marine organisms, has emerged as a critical component, accounting for a third of global aquaculture production.However, mariculture faces numerous challenges, including environmental impacts, reliance on wild inputs, and concerns about genetic interactions with wild populations. Biotechnological advancements offer potential solutions but must be balanced with considerations of ecosystem health and societal impacts.Integrated mariculture techniques and bioremediation approaches present opportunities to mitigate environmental impacts, but legislative frameworks and monitoring procedures are essential for ensuring compliance and minimizing adverse effects. Collaborative efforts between the public and private sectors are crucial for advancing sustainable practices and unlocking the full potential of the mariculture sector.In conclusion, addressing the challenges facing mariculture requires a comprehensive approach that prioritizes environmental sustainability, regulatory compliance. By embracing sustainable practices and fostering collaboration, the mariculture sector can navigate its challenges and contribute to global food security in a responsible and resilient manner.