Food And Agriculture Organization Research Articles

Study Evapotranspiration in Iraq Using the Penniman-Monteith Equation for the Period (2008-2020)

Evapotranspiration is considered an essential element for the stability of the ecosystem due to its importance in many aspects, including the water cycle, which is an important source of fresh water for humans, animals and plants. It also influences climate and temperatures and regulates weather. It also enters into the design of crop irrigation networks, knowing their water needs to prevent drought and desertification. The Penman-Monteith method is effective and accurate for calculating daily reference evapotranspiration and has been adopted by the Food and Agriculture Organization (FAO) as a standard method. This study aims to calculate the variation in evapotranspiration rates in Iraq using the Penman-Monteith method over the past thirteen years (2008-2020) in five equal periods (2008, 2011, 2014, 2017, and 2022). This study showed that the total rates of evapotranspiration are decreasing, and these values ​​peaked in 2008 and then decreased significantly in subsequent years. The reason for this decrease is the decrease in wind speed and the increase in relative humidity. It was found that evapotranspiration rates in the central and southern governorates are higher than in the northern governorates. However, there are deviations in the rates for some stations, such as in 2020, which witnessed a general decrease in evapotranspiration rates, except for some stations that recorded an increase. For example, Khanaqin station recorded the highest increase in evapotranspiration rates, which amounted to 23.6%. The reason for this increase is the increase in temperatures by 5.2% and the decrease in relative humidity by -6.5%.

A Review on Plant Leaf Disease Classification Using Deep Learning

The Food and Agriculture Organization (FAO) claims that plants provide more than 80% of the world's food supply. The report (2023), found that plant diseases are responsible for an estimated 40% of global crop losses each year. Therefore, it was necessary to find a solution that detects and classifies plant diseases early in the plant growth stage, using deep learning techniques. In this review, we will discuss the techniques for detecting plant diseases using leaves that have been studied in previous years. An overview of the articles cited in this review reveals that EfficientNet outperforms all other CNN models for plant leaf disease classification. It achieves an impressive accuracy rate that surpasses even the best-performing VGG, ResNet, and DenseNet models. DenseNet is also a good option, especially when computing resources are limited.

Regional calibration of the Hargreaves model for estimation of reference evapotranspiration

Abstract Estimation of reference evapotranspiration values is crucial in climatological and hydrological research, agricultural engineering, and irrigation design. The Penman-Monteith method, endorsed by the Food and Agriculture Organization (FAO) of the United Nations and numerous research studies, is widely regarded as the gold standard. However, its extensive data requirements limit its applicability in regions with sparse meteorological networks or limited measurement capabilities. The Hargreaves method, which requires only basic air temperature inputs, offers an alternative solution. The aims of this study were to calibrate the Hargreaves model for Central European climate conditions, considering altitudinal dependence, and to evaluate the temporal stability of the model parameters. In the first part of the research, we regionalized the Hargreaves coefficients using a curve-fitting method to ensure the best accuracy across 60 climatological stations in Slovakia. The regionalization of the Hargreaves coefficient improved accuracy by 10.1%, reducing the weighted absolute percentage error (WAPE) to 17.9%. However, our results showed that the accuracy of the modified Hargreaves model decreased with the increasing altitude of a climatological station. Incorporating altitude into the Hargreaves equation significantly improved model accuracy in stations at higher altitudes, providing a consistent level of accuracy across all climatological stations, regardless of their location and altitude. The results also indicated that the optimal model coefficient values change over time, showing a decreasing trend of –0.5 for the B coefficient and –0.1 for the C coefficient between the periods 1981–2000 and 2001–2020. Although regionalizing the Hargreaves model coefficients for local conditions can achieve good model performance, the model’s accuracy is not stable over time. Thus, periodic validation of the model is necessary for short-term applications.

A global analysis of portion size recommendations in food-based dietary guidelines.

Since large food portion sizes (PS) lead to overconsumption, our objective was to review PS recommendations for commonly consumed food groups reported in Food-Based Dietary Guidelines (FBDGs) globally and to assess variation in PS across countries and regions. Consumer-oriented FBDGs from the Food and Agriculture Organization (FAO) online repository were used to evaluate dietary recommendations, PS and number of portions for common food groups. Guidelines were classified for each group as qualitative, quantitative, or missing. A standardized approach was applied to convert PS recommendations given as household measures, cup equivalents, pieces and other measures into grams for cross comparison. Variation of recommended PS of common food groups within and across regions was examined. Among 96 FBDGs, variations were found both across and within regions. At a regional level, the highest median PS recommendations were seen in Europe for Meat, Fish and Pulses, in the Near East for Dairy products, and in Africa for most grain-based foods. Recommendations for Fruits and Vegetables showed the highest consistency across FBDGs worldwide, whereas guidance on Meat, fish & eggs and Cooked cereals/grains showed discrepancies in the classification of foods into categories, as well as in the number of portions per day. While some variation in PS recommendations across countries can be expected due to cultural and regional dietary practices, inconsistent definitions to refer to a portion and varied derivation methods may further produce discrepancies. Harmonizing development methods for FBDG could help establish more consistent reference portion sizes and therefore provide clearer guidance to consumers.

Assessing the impact of structural modifications in the construction of surveillance network for Peste des petits ruminants disease in Nigeria: The role of backbone and sentinel nodes.

Peste des petits ruminants (PPR) is a highly contagious disease affecting mainly sheep and goats. Livestock movements contribute to the spread of the disease by introducing it to naive areas or exposing susceptible animals to it in infected regions. Because of its socio-economic impact, the Food and Agriculture Organisation (FAO) and the World Organization for Animal Health (WOAH) have set the goal to eradicate it by 2030, one of the key steps being the improvement of surveillance networks. The present study aimed to provide tools to identify areas that could serve as sentinel nodes, i.e. areas that may be rapidly infected at the onset of epidemics. Using data from a market survey conducted in Northern Nigeria, we reconstructed the small ruminants mobility network and simulated the diffusion of PPR virus through animal movement. From the analysis of simulation outcomes, we investigated which nodes could act as sentinel nodes under specific conditions for disease transmission. We considered several modified networks to get around the problem of data only being available for part of the overall network structure and to account for potential errors made during the field study. For each configuration, we simulated the spread of PPR using a stochastic Susceptible-Infectious (SI) model based on animal movements to assess the epidemics' extent and the presence of recurrent patterns to identify potential sentinel nodes. We extracted the backbone of the reference network and checked for the presence of sentinel nodes within it. We investigated how the origin (seed) of the epidemics could affect the propagation pattern by comparing and grouping seeds based on their respective transmission paths. Results showed that the isolated backbone contains 45% of sentinel nodes that remain stable or undergo only minor changes in 9 out of 11 configurations. On top of that, the characteristics of sentinel nodes identified in the backbone are not influenced by the severity of the disease. The H index, in-degree, and eigenvector are the most essential variables. This study provides an overview of the major axes of animal movements in Nigeria and the most vulnerable locations that should be prioritized for monitoring livestock diseases like PPR.

Application of Natural Antioxidants from Fruits Waste for Improving Egg Quality Characteristics

Fruit waste poses a significant global challenge, with the Food and Agriculture Organization (FAO) reporting that about 1.3 billion tons of food is wasted annually, contributing to environmental and economic challenges. The major fruit-producing countries (United States, China, India, and Brazil) are responsible for a large portion of this waste. Fruit waste contains different bioactive compounds like polyphenols, flavonoids, vitamins, and carotenoids, which are, in large part, underutilized regardless of their antioxidant properties. These compounds can play an important function in poultry nutrition, offering natural alternatives to synthetic antioxidants. Reintegrating fruit waste into poultry diets might have potent benefits on the nutritional quality and shelf life of eggs. Some studies reported that bioactive compounds from fruit waste improve the oxidative stability of eggs and the nutritional content, potentially extending shelf life during storage. Additionally, antioxidant compounds from fruit waste have been shown to improve yolk coloration and some egg quality parameters while reducing reactive oxygen species, which cause lipid oxidation. Their inclusion in poultry diets can lower feed costs, promote animal welfare, and reduce the environmental impact of fruit waste. This review highlights some key fruit wastes, such as citrus, apple, grape, rosehip, sea buckthorn, and banana, among others, which are natural reservoirs of bioactive compounds beneficial for poultry nutrition. This strategy aligns with FAO sustainability goals, addressing both food waste and animal nutrition challenges. Future studies should focus on optimizing the inclusion rates of these natural antioxidants in poultry diets to maximize their benefits.

Seroprevalence and associated risk factors of peste des petits ruminants in sheep and goats in three districts of the Central Oromia Region, Ethiopia.

Peste des petits ruminants (PPR) is a viral disease that affects domestic and wild small ruminants and camels in Africa, the Middle East, and Asia. Following the successful eradication of rinderpest, the World Organization for Animal Health (WOAH) and the Food and Agriculture Organization (FAO) have undertaken to eradicate PPR by 2030. Regular surveillance and monitoring of the disease in various regions of Ethiopia are crucial to achieving this goal. This study aimed to estimate the prevalence of PPR, assess community awareness of PPR infection, and examine the associated risk factors of the disease in selected districts of the Central Oromia Region, Ethiopia. The study collected 384 serum samples from 73 flocks containing 217 sheep and 167 goats using a multi-stage sampling technique. A competitive enzyme-linked immunosorbent assay (c-ELISA) was used to detect antibodies against the PPR virus. Additionally, a pre-tested questionnaire was used to gather information on community awareness and potential risk factors for PPRV infection in the study area. The study found that the overall prevalence of PPR in flocks was 71.2% [95% confidence interval (CI): 59.4%-81.2%]. The prevalence of PPR at the animal level was 50% (95% CI: 44.9%-55.1%), with sheep having a prevalence of 54.4% (95% CI: 47.0%-60.6%) and goats having a prevalence of 44.3% (95% CI: 36.6%-52.2%). The study also found that districts, flock size, and agroecology were independent predictors of PPRV seropositivity in sheep, whereas districts, origin, and mixed species were independent predictors of PPRV seropositivity in goats. The study revealed a high prevalence of PPR in sheep and goats in the study area. To prevent the spread of the disease, the study suggests quarantining animals before introducing them to districts, regular PPR vaccination, and isolation and molecular characterization of the PPR virus circulating in the study area.

A Comprehensive Analysis of the Relationship Between GDP and the Global Hunger Index Over the Last 20 Years

This study examines the relationship between Gross Domestic Product (GDP) per capita and the Global Hunger Index (GHI) over the past two decades. By analyzing data from various countries across different income levels, the research explores how economic growth intersects with hunger dynamics. The study utilizes reputable sources, including reports from the Food and Agriculture Organization (FAO), the International Food Policy Research Institute (IFPRI), and the World Bank. The findings highlight that while GDP per capita is an important factor in reducing hunger, other elements such as income inequality, education, health expenditure, agricultural productivity, and governance significantly influence hunger outcomes. The research underscores the necessity for holistic approaches that integrate economic growth with social equity and effective policy interventions to eradicate hunger globally.

Association between dietary diversity and lipid indices among Indian Kho-Kho players

Purpose Dietary diversity (DD) is a proxy indicator of nutrient adequacy and has been propagated as a health beneficial component of dietary behavior. This study aims to understand DD and its association with lipid indices among Indian Kho-Kho players. Design/methodology/approach In all, 50 Indian Kho-Kho players aged between 16 years and 31 years belonging to different regions of India were recruited. Dietary diversity score (DDS; food groups/day) and food variety score (FVS; number of food items/day) were considered to assess the DD. The United Nations Food and Agricultural Organization food frequency questionnaire was used as a tool. Serum total cholesterol (TC), triglycerides (TG), LDL, VLDL and HDL were measured. Findings The DDS and FVS showed that athletes were consuming approximately 7 of 9 food groups (Mean ± SD: 6.5 ± 1.3) and 27 varieties of foods (Mean ± SD:27.0 ± 8.6) from 9 food groups per day. This study could not find significant differences for DDS and FVS among athletes belonging to different regions. FVSs of organ meat, eggs and spices and condiments were significantly positively associated with TG (p < 0.036, p < 0.020 and p < 0.001) and VLDL (p < 0.054, p < 0.021 and p < 0.001). LDL was inversely significantly associated with FVS of cereals, white root and tubers (p < 0.032). Research limitations/implications DDS and FVS were not associated with lipid indices among Kho-Kho players. However, individual FVS of organ meat, eggs and spices and condiments may increase TG and VLDL. Optimum consumption of cereals and root tubers may help to maintain LDL levels among Kho-Kho players. Originality/value It was found that daily consumption of organ meat and eggs may increase TG and VLDL, and optimum consumption of cereals and white roots and tubers may help to maintain LDL. High energy and fat foods may act as mediators along with spices and condiments in increasing TG and VLDL.

Polycaprolactone-zinc oxide biocomposite membranes for wastewater treatment by ultrafiltration process: Synthesis, characterization and removal of inorganic pollutants

The severe droughts impacting North Africa have intensified the pressure on potable water supplies and agricultural irrigation, highlighting the urgent need for sustainable water management solutions. This study explores the potential of poly(ε-caprolactone)/zinc oxide (PCL/ZnO) biocomposites as ultrafiltration membranes for treating urban wastewater, with the goal of enabling water reuse in agriculture. PCL/ZnO membranes, fabricated using the solvent-casting method, were thoroughly characterized using FTIR, XRD, EDAX, SEM, AFM, DSC, TGA, and water contact angle (WCA) measurements. Key findings revealed that increasing ZnO content (1–4 wt%) significantly enhanced membrane thickness, crystallinity, mechanical robustness, and surface roughness, while lowering WCA values to improve hydrophilicity. These enhanced properties are critical for ultrafiltration, as they contribute to higher contaminant rejection and improved water permeability. Performance tests demonstrated ion retention rates of 32–61 % post-filtration, including for toxic metals, effectively reducing pollutant levels. Notably, the treated water met the Food and Agriculture Organization (FAO) standards for irrigation quality, indicating its suitability for agricultural applications. This work highlights the efficacy of PCL/ZnO membranes in facilitating sustainable wastewater recycling under drought conditions, presenting a promising, adaptable solution for water reclamation in water-scarce regions. The results underscore the potential of these biocomposite membranes to advance sustainable water treatment practices, supporting both environmental resilience and agricultural productivity.

LocustLens: leveraging environmental data fusion and machine learning for desert locust swarm prediction

The desert locust is one of the most destructive locusts recorded in human history, and it has caused significant food shortages, monetary losses, and environmental calamities. Prediction of locust attacks is complicated as it depends on various environmental and geographical factors. This research aims to develop a machine-learning model for predicting desert locust attacks in 42 countries that considers three predictors: soil moisture, maximum temperature, and precipitation. We developed the Global Locust Attack Database for 42 countries (GLAD42) by integrating TerraClimate’s environmental data with locust swarm attack data from the Food and Agriculture Organization (FAO). To improve the usability of spatial data, reverse geocoding which is the process of converting geographic coordinates (longitude and latitude) into human-readable location names (such as countries and regions) was employed. This step enhances the clarity and interpretability of the data by providing meaningful geographic context. This study’s initial dataset focused on instances where locust attacks were recorded (positive class). To ensure a comprehensive analysis, we also incorporated negative class instances, representing periods (specific years and months) in the same countries and regions where locust attacks did not occur. This research utilizes the benefits of lazy learners by employing the K-nearest neighbor algorithm (K-NN), which provides high accuracy and the benefit of no time-consuming retraining even if real-time updated data is periodically added to the system. This research also focuses on building an eco-friendly machine learning model by evaluating carbon emissions from ML models. The results obtained from LocustLens are compared with other machine learning models, including baseline–K-NN, decision trees (DT), Logistic regression (LR), AdaBoost Classifier, BaggingClassifier, and support vector classifier (SVC). LocustLens outperformed all competitors with an accuracy of 98%, while baseline-K-NN achieved 96%, SVC gave 91%, DT gave 97%, AdaBoost has accuracy of 91%, BaggingClassifier gave 94% and LR gave 83%, respectively. Carbon emissions from RAM and CPU electricity consumption are measured in kg gCO2. They are a minimum for AdaBoost Classifier equal to 0.02 and 0.07 for DT and a maximum of 9.03 for SVC. The carbon footprint of LocustLens is 4.87 kg gCO2.

Integrating environmental sustainability within national food-based dietary guidelines: a qualitative analysis from five case study countries

Abstract Background The incorporation of environmental sustainability principles into national food-based dietary guidelines (FBDGs) has gained prominence as a strategy to address both human health and environmental concerns. This study aims to identify and explore the processes and considerations to integrate environmental sustainability in food-based dietary guidelines. Methods Countries that have integrated environmental sustainability in FBDGs since 2016 were identified from the UN FAO website. Background documents and interviews with key stakeholders involved in the development of FBDGs from case study countries (The Netherlands, Denmark, Chile, France and Belgium (Flanders)) were thematically analysed using the Framework Method. A coding framework explored the rationale for integration, data sources and analysis methods, stakeholder and expert engagement, synergies and trade-offs, translation into public messaging, and key learnings. Results Eight background documents and six interviews were analysed. Approaches to integrating environmental sustainability varied, from inclusion in dietary modelling optimisation to changes to consumer messaging. Nearly all countries adjusted guidelines to reduce red and processed meat and emphasise the role of plants in diets. However, issues of cultural significance, affordability, and access limited ambitions to reduce overall meat intake. Novel plant-based alternatives remain contentious due to concerns about their ultra-processed nature and potential nutrient inadequacies as substitution foods. Key barriers to integrating environmental sustainability into FBDGs include consumer acceptance, data quality and availability, stakeholder involvement and conflict, timelines, and resource constraints. Conclusions Several countries have successfully integrated environmental sustainability into their dietary guidelines, but there is still variation in the integration and acceptance of FBDGs including environmental sustainability.

Econometric analysis of factors influencing export performance of soybean (Glycine max) production in NIGERIA: An auto-regressive distributive lag (ARDL) approach

This study presents an econometric analysis of factors influencing the export performance of soybean (Glycine max) production in Nigeria using an auto-regressive distributive lag (ARDL) approach. The study used a secondary data covering the period from 2011 to 2022. The used data were collected from CBN (Central Bank of Nigeria), NBS (National Bureau of Statistics), FAO (Food and Agriculture Organization), and the General Household Survey-Panel (GHS-P) in conjunction with the Federal Ministry of Agriculture and Rural Development, and the World Bank publication. The data analysis included descriptive statistics, Augmented Dickey-Fuller (ADF) unit root test, Bound test, ARDL, and principal component model. The result of the ADF unit root test showed that the trade openness, consumer price index, exchange rate, population growth, world trade in oil seeds, agricultural labor, and soybean production were stationary at first difference I (1), while agricultural machinery was stationary at level I (0). The results of ARDL method showed that the consumer price index, population growth rate, world trade in oil seeds, agricultural labor, and agricultural machinery were significant factors influencing export performance of soybean in Nigeria. The trade openness and exchange rate were not different significantly from zero. The trade openness could not expand market access due to non-competitiveness of the Nigerian’s soybean. The exchange rate has lost its role with respect to soybean seed partners in international trade. The policies that would encourage exportation of this crop should be pursued by provision of storage facilities, granting of tax holidays, long term export credit at concessionary interest rate to exporters, and research activities towards improving the quality of produced agricultural products. Keywords: Export Performance, Augmented Dickey-Fuller, Auto-Regressive Distributive Lag, Soybean Production, Nigeria

An integrated food management framework: A preventive measure for food scarcity during the Prabowo Subianto administration

The Food and Agriculture Organization (FAO) reported in 2024 that Indonesia is at risk of facing a future food crisis if adequate food supply is not ensured. A critical aspect of food management in Indonesia lies in its management systems. Thus, this study aims to review the extent to which food management under the Joko Widodo administration has been integrated to address food shortages. Further, this study will develop an integrated food management system as an alternative to prevent food scarcity during the Prabowo Subianto administration. The methodology involves a literature review and in-depth interviews with stakeholders involved in managing the national food reserve. Findings indicate that food management in Indonesia remains fragmented and lacks integration between central and local governments, hindering effective food management during periods of scarcity. Based on an online website, the proposed integrated food management framework aims to simplify national food management and prevent food shortages.

Disaggregating animal welfare risks in aquaculture.

Aquaculture, fueled partly by claims of supporting food security, is experiencing unprecedented growth. Framing aquaculture as a monolith, however, overlooks its extreme taxonomic diversity. This paper assesses the welfare risks associated with that diversity, establishing seven species-level risk factors from involved parental care to long lifespans. Investigating these welfare risks across all aquatic species reported to the Food and Agriculture Organization (FAO) revealed an uneven distribution of risk, with extreme species-level risks in chordates, crustaceans, and cephalopod mollusks. Compared to species with fewer risks, species with extreme welfare risks were found to cost more and contribute the least to global production. This work challenges the notion that prioritizing animal welfare is incompatible with addressing food security and creates the possibility of identifying certain plant and invertebrate species, like seaweeds and bivalves, that minimize welfare concerns while providing affordability and accessibility. Going forward, proactive welfare approaches are needed to inform consumer choice and shape just and sustainable aquaculture policy.

Exponential Mean Modeling of Coping Strategies and Dietary Diversity During the COVID-19 Pandemic in Mozambique

The COVID-19 pandemic has brought significant socioeconomic problems to many developing countries. In Mozambique, the impacts of the pandemic were felt in different spheres of households’ livelihoods. This study contributes to the existing body of knowledge by analyzing the effects of coping strategies and other factors on households’ dietary diversity scores (HDDS). The data were collected in two non-longitudinal waves in 2021 and 2022 from 3975 households by the Food and Agriculture Organization (FAO). The instrumental Poisson regression model was used for data analysis. The results showed that across the two periods, cereals were mostly consumed (96.93%), while meats (15.75%), milk and dairy (13.99%), and eggs (9.16%) were the least consumed. There was an increment in the proportion of households that consumed between zero and four food groups. Furthermore, there were declines in the utilization of coping strategies, while depletion of savings (50.62%) and credit (45.21%) were mostly used. The instrumental variable Poisson regression results revealed that expected HDDS decreased significantly (p<0.05) with sold animals, eating elsewhere, consumption of seed stock, decreased agricultural input expenditures, and emergency begging, whereas illegal activities increased it. In addition, household incomes, crop farming, and being younger than 35 years significantly increased (p<0.05) the expected HDDS, while all regions except Gaza had significantly higher expected HDDS than Cabo Delgado. It was concluded that adopted coping mechanisms could not offset households’ food problems during the pandemic, although some regional differences existed. Therefore, initiatives to promote human nutrition in Mozambique should enhance households’ resilience to income shocks through region-specific income-promoting activities.

Fields, Frontiers, and the Making of the Food and Agriculture Organization

ABSTRACT The UN’s Food and Agriculture Organization (FAO), once the overlooked stepchild of post-war global governance, is now at the centre of attention among historians, parsing the key figures, central policies, and ongoing challenges across the FAO’s embattled life-time. However, to date, there has been little engagement with the material, territorial and ecological preconditions that required the construction of global food governance in the first place. The present article contributes to FAO scholarship via a more grounded historical sociology of agriculture and international (dis)order. To do so, I frame the evolution of the modern ‘global countryside’ through four distinct yet inter-locking frontiers: territory, commodity, technology, institutions. In using the case of US state-formation as a springboard, I argue that the contradictory entanglement of territorial and commodity frontiers during the settler-colonial period led to a collective anxiety about US (and global) agrarian development, which called forth ever-more innovative solutions through the expansion of technological and institutional frontiers. This spiral of emergence, entanglement, crisis, and resolution culminated in the first post-war conference on international cooperation, and the eventual consecration of the FAO. Yet the contradictions of the post-war international system – at once deeply inter-dependent yet radically hierarchical – ultimately doomed the hopes for a more cooperative global food order. A more critical approach to the making of the FAO thus offers important lessons on the current dilemmas facing today’s global food system.

Current methodologies available to evaluate the virulence potential among Listeria monocytogenes clonal complexes.

Listeria monocytogenes is a foodborne pathogen that causes listeriosis in humans, the severity of which depends on multiple factors, including intrinsic characteristics of the affected individuals and the pathogen itself. Additionally, emerging evidence suggests that epigenetic modifications may also modulate host susceptibility to infection. Therefore, different clinical outcomes can be expected, ranging from self-limiting gastroenteritis to severe central nervous system and maternal-neonatal infections, and bacteremia. Furthermore, L. monocytogenes is a genetically and phenotypically diverse species, resulting in a large variation in virulence potential between strains. Multilocus sequence typing (MLST) has been widely used to categorize the clonal structure of bacterial species and to define clonal complexes (CCs) of genetically related isolates. The combination of MLST and epidemiological data allows to distinguish hypervirulent CCs, which are notably more prevalent in clinical cases and typically associated with severe forms of the disease. Conversely, other CCs, termed hypovirulent, are predominantly isolated from food and food processing environments and are associated with the occurrence of listeriosis in immunosuppressed individuals. Reports of genetic traits associated with this diversity have been described. The Food and Agriculture Organization (FAO) is encouraging the search for virulence biomarkers to rapidly identify the main strains of concern to reduce food waste and economical losses. The aim of this review is to comprehensively collect, describe and discuss the methodologies used to discriminate the virulence potential of L. monocytogenes CCs. From the exploration of in vitro and in vivo models to the study of expression of virulence genes, each approach is critically explored to better understand its applicability and efficiency in distinguishing the virulence potential of the pathogen.

Urgency of Implementing Indonesian Halal Certification in International Trade (Case Study of Chicken Meat Imports from Brazil)

Discussions regarding the halal industry have been very prominent in recent years. Therefore, many issues related to the halal industry are written about and used as research objects. Halal products must have certain specifications so they can play in the halal market. These specifications require certain qualifications that are closely related to halal standards. This research aims to explain the urgency of implementing halal certification in Indonesia in international trade (case study of chicken meat imports from Brazil). The first research result is that as a global food organization, the Food and Agriculture Organization (FAO) has the idea of halal products. Nevertheless, FAO's main focus is currently limited to food products. FAO has not fully protected regulations relating to the guarantee of halal products for countries around the world. FAO provides ratification to each country regarding halal product regulatory policies. The only FAO requirement is that the exporting country must receive halal certification to demonstrate that the product is halal, although this can still be requested by the importing country. The second is that Indonesia has stipulated that although not all products in circulation must have halal certification, some must. Article 135 PP No. 39 of 2021 and Article 125 PP No. 39 of 2021.

Developing mathematical models to calculate annual evapotranspiration rates in Iraq using climate data.

Abstract Evapotranspiration is considered the fuel that controls the water cycle in the natural world. It is necessary for the stability of ecosystems and is involved in many important aspects in calculating groundwater quantities, determining optimal locations for building dams and reservoirs and knowing the water needs of crops. The work is divided into two main parts. The first includes the use of The Penman-Monteith method, which is considered the most standard method in the world according to the Food and Agriculture Organization (FAO), for calculating the annual rate of evapotranspiration in Iraq for the past fifteen years (2008-2022). The second part is a modification of a simple method for calculating evapotranspiration, which is the Thornthwaite method, to give results close to the accuracy of the Penman-Monteith method, as the modification was made using different statistical methods. The study showed the possibility of using the modified Thornthwaite method as an alternative to the Penman-Monteith method to calculate evapotranspiration in all regions of Iraq.