Food And Agriculture Organization Research Articles

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.

Balancing economic and environmental goals: A novel strategy for growing items acquisition in livestock farming under an incremental discount and a power demand pattern

The human food supply chain is significantly influenced by growing items (GIs) like beef, sheep, hog, chicken, turkey, and other species, as these provide major contributions to food security worldwide. Industrial farming businesses carry out their operations by purchasing a certain species of baby GIs from a supplier, feeding and caring for them until they reach an acceptable living weight, and then selling them after they have been slaughtered and processed. In addition, the production of livestock worldwide accounts for 14.5% of all anthropogenic greenhouse gas (GHG) emissions, according to the Food and Agriculture Organization (FAO), making it a substantial contributor to GHG emissions. Thereby, to regulate emissions, governments from several countries have imposed a tax scheme on the farm’s emission volume. Due to the discrete nature of purchase numbers, using a differentiation-based optimization approach is not appropriate for determining the optimal GI procurement for an industrial farm, making the decision significantly more challenging. The primary goal of this study is to identify the optimal number of GIs for a farm to enhance financial and environmental performance when the cost per weight unit of procurement depends on the volume of purchases and the consumption of processed commodities follows a power demand pattern. A comparison tactic is employed only for the discrete decision variable, while the classical optimization tactic, based on differentiation, is adopted for the remaining continuous decision variable of the derived problem. Our method, which is quite straightforward in its operation, enables the creation of a rule to distinguish between instances in which there is only one optimum solution and those in which there are two. The results from the execution of the novel solution technique reveal that the farm reduces the overall cost of the order while keeping the integrality of the purchased GIs by taking into account the regulation for carbon emissions, the discount, and the power demand pattern.

Estimation of Evaporation and Drought Stress of Pistachio Plant Using UAV Multispectral Images and a Surface Energy Balance Approach

Water scarcity is a critical abiotic stress factor for plants in arid and semi-arid regions, impacting crop development and production yield and quality. Monitoring water stress at finer scales (e.g., farm and plant), requires multispectral imagery with thermal capabilities at centimeter resolution. This study investigates drought stress in pistachio trees in a farm located in Yazd province, Iran, by using Unmanned Aerial Vehicle (UAV) images to quantify evapotranspiration and assess drought stress in individual trees. Images were captured on 10 July 2022, using a Matrix 300 UAV with a MicaSense Altum multispectral sensor. By employing the Surface Energy Balance Algorithm for Land (SEBAL), actual field evapotranspiration was accurately calculated (10 cm spatial resolution). Maps of the optimum crop coefficient (Kc) were developed from the Normalized Difference Vegetation Index (NDVI) based on standard evapotranspiration using the Food and Agriculture Organization (FAO) 56 methodology. The comparison between actual and standard evapotranspiration allowed us to identify drought-stressed trees. Results showed an average and maximum daily evaporation of 4.3 and 8.0 mm/day, respectively, in pistachio trees. The real crop coefficient (Kc) for pistachio was 0.66, contrasting with the FAO 56 standard of 1.17 due to the stress factor (Ks). A significant correlation was found between Kc and NDVI (R2 = 0.67, p < 0.01). The regression model produced a crop coefficient map, valuable to support precise irrigation management and drought prevention, considering the heterogeneity at the farm scale.

Physicochemical Characteristics of Water in the Bontanga Irrigation Dam in the Guinea Savannah Agro-Ecological Zone of Ghana

Fresh water resource is one of the most significant natural assets of a country. Irrigation dams are usually used for irrigation purposes and also often serve as a source of water for domestic use. Due to this, there is a need for proper maintenance, assessment, and sustainable use of irrigation dams. This study assessed the physicochemical properties of the water in the reservoir of Bontanga irrigation dam situated in the Guinea Savannah Agro-Ecological Zone of Ghana. The study assessed four (4) physical and fourteen (14) chemical water quality parameters of the water for irrigation to know whether they are within the acceptable threshold set by the Food and Agriculture Organization (FAO) and the World Health Organization (WHO). Sampling techniques used in this study were stratified and purposive samplings. The reservoir of the dam was divided into nine (9) strata and in each stratum, 5 samples were taken making a total of 45 samples. Samples taken in each strata were composited making it a total of 9 samples. The water samples were collected into well-labelled polythene bottles and kept in an ice chest with ice cubes. The samples were transported to the Ecological Laboratory of the University of Ghana for analysis. The parameters analyzed were pH, electrical conductivity (EC), temperature, total dissolved solutes (TDS), chloride (Cl-), sulphate (SO42-), bicarbonate (HCO3-), carbonate, PO4-P, nitrites/nitrate (NO3-N), total dissolved solids (TDS), magnesium (Mg2+), calcium (Ca2+), sodium (Na+), boron, total alkalinity, ammonia (NH4-N) and potassium (K+). A greater percentage of the results obtained were within acceptable limits except potassium which was slightly higher. This could be the result of farming activities in the catchment of the dam. In general, the water in Bontanga irrigation dam can be considered suitable for irrigation purposes.

Linking farmers' perceptions and management decision toward sustainable agroecological transition: evidence from rural Tunisia.

Global food systems face sustainability challenges like undernourishment, inequity, resource degradation, and pollution. Food production and consumption drive environmental change with greenhouse gas emissions, biodiversity loss, and land-system shifts. The climate change crisis has intensified concerns about the ecological impact of these systems. Sustainable food networks, such as community-supported agriculture, are promoting sustainable production and consumption through short supply chains. International bodies like the Food and Agriculture Organization (FAO) and the Consultative Group for International Agricultural Research (CGIAR) are also spearheading initiatives for more equitable and sustainable food systems. In Tunisia, where dryland areas predominate, the ongoing implementation of the Agroecology Initiative provides the context for this study, which explores the drivers and barriers of agroecological transformation in this challenging environment. The research focuses on stakeholder engagement, with a gender perspective to explore farmer perceptions. The study, conducted in the northwest of Tunisia in 2022-2023, involved focus groups, workshops, surveys, and questionnaires with various stakeholders. Findings highlight farmer organizations' potential in promoting sustainable farming, with clear goals, diversified systems, and collaborations. However, challenges such as input scarcity, water shortage, low income, and marketing must be addressed. Results also indicate that over 90% of farmers who received assistance with agroecological practices reported a change in their ideas and practices. Fifty seven percent of the workshops participants identified the olive oil value chain as having the greatest potential for agroecological transformation, but it faces constraints such as climate, lack of policy incentives, training, funding, and difficulty in adopting technical innovations. Women's inclusion in agriculture, environmental, social, and economic challenges were also highlighted. Despite these obstacles, key drivers for agroecological transition were identified. These include the compatibility of many agroecological practices with existing farmer capabilities, their cultural and economic benefits, and the positive outcomes for environmental sustainability and health. The study advocates for a socio-technical systems analysis to address the root causes hindering Tunisia's agroecological transformation. A participatory approach is crucial to understanding priorities and developing a sustainable and resilient food system. Furthermore, the research underscores the importance of considering diverse farmer perspectives and tailoring strategies to support this critical transition effectively.

Feed Friend: Fostering Community Involvement in Food Assistance

According to the Food and Agriculture Organization (FAO) of the United Nations, approximately one-third of all food produced for human consumption worldwide is wasted annually. Food wastage occurs at various stages of the supply chain, including production, processing, distribution, and consumption. FeedFriend is an innovative website which was designed to combat food-wastage by fostering a vibrant community of donors and recipients. Donor Registration Individuals or Businesses can sign up as Donors on FeedFriend, providing details about the surplus food they have available for donation. This includes restaurants with excess inventory, grocery stores with perishable items nearing expiration, or individuals with leftover food from events or meals. Food Listings Donors can create listings within the website, specifying the type and quantity of food they wish to donate, include relevant details such as expiration dates etc. In Feed Friend, Users can filter the Donation requests based on their location. This type of service is used to match donors with nearby recipients in need. Recipients may include food banks, shelters, community centers, or individuals facing food insecurity. Feed Friend facilitates communication between donors and recipients, coordinates pickup or delivery logistics directly by providing donor’s contact details. So that it enables a better communication between Donors and Receivers.

The Progress/Status of Ecological Assessment on the Intensive Land Use in Selenge and Darkhan-Uul Province, Mongolia

Abstract. The study area, it includes Darkhan-Uul and Selenge provinces of Mongolia, is included in the most favourable natural-geographical areas, and the migration of people with livestock from the peripheral areas has led to an increase in the population, as well as a sharp increase in the number of grazing animals, resulting in the effects of natural and human activities. give an evaluation, develop the basis for the proper use of the land in the future. In Mongolia, the methods and principles of land evaluation differ depending on the general classification and purpose of land, so considering these characteristics, land evaluation is carried out by (1) the Department of Agriculture, (2) the Department of Urban Development, Industry and Mines, (3) the Department of Roads and Networks, (4) it is divided into types of land with forest reserves (Tserenbaljir, B. Naranchimeg, 2004). In the "instructions for land evaluation" issued by the United Nations Food and Agriculture Organization (FAO) in 1976, in the assessment of land quality, in addition to the main indicators of soil fertility and moisture, climate, land cover and use, chemical pollutions such as an alkaline acidity. In the ecological assessment study, data on land use, soil, vegetation, climate, natural conditions, resources, socio-economic, satellite and field studies were collected in numerical and tabular form. The Ecological assessment in intensive land use is divided into qualitative and quantitative assessment. The Qualitative assessment predicts ecological properties. The Quantitative methods use multi-species numerical methods to record ecological elements and calculate the overall percentage of ecological characteristics.

Evaluation of the Microorganism Present in Garri Sold within Local Market and Garri Producers in Ozoro Community

This study evaluated the microorganisms (bacteria and fungi) present in garri sold within local market and garri producers at Ozoro Community. This was achieved through microbial analysis of samples to determine microbial count and strains available. Contamination of sample was observed for garri sold at different locations with the bacteria count seen to be higher at the local market 1 (42x106cfu/10g) and garri producer (41x106cfu/10g) than at local market 2 (38x106cfu/10g) which shows that market activity may not be the contamination source. Bacteria isolates indicated the presence of pathogen associated with disease and food poisoning syndrome such as E. coli, Staphylococcus, Bacilli and Pseudomonas. Staphylococcus and Escherichia coli were observed to be the dominant strains of microbes in garri sold across all assessed location which poses health risk due to their pathogenicity. Fungi were detected in garri samples assessed from all three locations with an increasing trend from producer to sales point which is an indication that garri contamination with fungi must have occurred from post production activities in the market and sales point. The fungi isolates obtained from the samples areAsperillus flavus Penicilum spp.and Candida albican. Asperillus flavus andPenicilum spp. were observed to be the dominant strains of microbes in garri sold across all assessed location. The samples of garri sold around Ozoro are unsafe since they did not meet with the recommended limit by Food and Agriculture Organization (FAO) of 1x104cfu/g for bacteria count and 1x104cfu/g for fungi count and E.coli count of 0. Hygienic practices should be strictly adhered to prevent contamination of garri produced.

The effects of climate extreme events on selected food crop yields in Sub-Saharan Africa

The agricultural sector is essential for economic growth. However, agricultural performance can be limited by factors such as climatic risks. This paper aims to analyse the effect of climate extreme events on selected food crop yield in sub-Saharan Africa (SSA). The study uses data from the Food and Agriculture Organisation (FAO) database for maize, rice, and sorghum yields. Also, we used data obtained from the International Disaster Database of the Centre for Research on the Epidemiology of Disasters (CRED) for floods and droughts over the period 1990–2020. The data were analysed based on the Fully Modified Ordinary Least Squares (FMOLS). The results showed that climate extreme events negatively affected maize, rice and sorghum yields. Also, the findings showed that floods and droughts in past years negatively influence current yields of maize, rice and sorghum. Moreover, agricultural labour force, fertilizer and financial development are the main transmission channels through which floods and droughts can affect maize, rice and sorghum yields. The study concludes by recommending that policies aimed at promoting climate change adaptation measures as well as agricultural insurance could make the agriculture sector more resilient to climate extreme events and in turn that could improve agricultural productivity and reduce food insecurity.

International application of global forest product model and the reference to China

PurposeThis article summarizes the international scientific research output of global forest product models, infers future research trends and provides reference for quantitative analysis and mathematical modeling of Chinese forest product problems, with the aim of contributing to promoting domestic production of Chinese forest products and strengthening international trade competitiveness of forest products.Design/methodology/approachIn 1999, Joseph Buongiorno, a scholar at the University of Wisconsin in the United States of America, proposed the global forest products model (GFPM), which was first applied to research in the global forestry sector. GFPM is a recursive dynamic model based on five assumptions: macroeconomics, local equilibrium, dynamic equilibrium, forest product conversion flow and trade inertia. Using a certain year from 1992 to present as the base period, it simulates and predicts changes in prices, production and import and export trade indicators of 14 forest products in 180 countries (regions) through computer programs. Its advantages lie in covering a wide range of countries and a wide variety of forest products. The data mainly include forest resource data, forest product trade data, and other economic data required by the model, sourced from the Food and Agriculture Organization (FAO) of the United Nations and the World Bank, respectively.FindingsCompared to international quantitative and modeling research in the field of forest product production and trade, China's related research is not comprehensive and in-depth, and there is not much quantitative and mathematical modeling research, resulting in a significant gap. This article summarizes the international scientific research output of global forest product models, infers future research trends, and provides reference for quantitative analysis and mathematical modeling of Chinese forest product problems, with the aim of contributing to promoting domestic production of Chinese forest products and strengthening international trade competitiveness of forest products.Originality/valueOn the basis of summarizing and analyzing the international scientific research output of GFPM, sorting out the current research status and progress at home and abroad, this article discusses potential research expansion directions in 10 aspects, including the types, yield and quality of domestic forest product production, international trade of forest products, and external impacts on the forestry system, in order to provide new ideas for global forest product model research in China.

Zerohunger Link-Bridging Food Waste and Hunger Gaps-An Integrated Approach

The Food and Agriculture Organisation (FAO) of the UN estimates that 1.3 billion tonnes, or one-third, of the food produced for human consumption is lost or wasted, making food waste a major global issue. About 40% of food produced in India is wasted, and homes, restaurants, hotels, weddings, and other gathering places are major contributors to this problem. In India, a large number of nonprofit organisations are actively trying to collect excess food and provide it to people in need in order to alleviate hunger, malnutrition, and food waste. The objective of this proposed project is to manage a prepared food supply chain through the development of an innovative application, with the goal of addressing urban excess food waste and hunger-related fatalities. This programme will make it easier to connect surplus and deficient food resources within a community network by using an ERP paradigm. Administrators will be able to monitor donor and recipient information, assess hotels according on their contributions and input, and efficiently manage logistics thanks to the technology. Trusts and beneficiaries will be able to register, use a matching algorithm to find local food resources, choose and request food, communicate directly with donors, and offer insightful feedback. Donors will have the ability to sign up, enter the information of the food that is provided, reply to requests, and get in touch with recipients and trusts. Additionally, staff members and delivery persons will be equipped with the necessary tools to register, oversee pickups and deliveries, and send out timely alerts when they are finished. In the end, this all-encompassing strategy seeks to reduce food waste and lessen hunger in communities by establishing an effective and transparent method for the redistribution of excess food resources

Precision Estimation of Crop Coefficient for Maize Cultivation Using High-Resolution Satellite Imagery to Enhance Evapotranspiration Assessment in Agriculture.

The estimation of crop evapotranspiration (ETc) is crucial for irrigation water management, especially in arid regions. This can be particularly relevant in the Po Valley (Italy), where arable lands suffer from drought damages on an annual basis, causing drastic crop yield losses. This study presents a novel approach for vegetation-based estimation of crop evapotranspiration (ETc) for maize. Three years of high-resolution multispectral satellite (Sentinel-2)-based Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Red Edge Index (NDRE), and Leaf Area Index (LAI) time series data were used to derive crop coefficients of maize in nine plots at the Acqua Campus experimental farm of Irrigation Consortium for the Emilia Romagna Canal (CER), Italy. Since certain vegetation indices (VIs) (such as NDVI) have an exponential nature compared to the other indices, both linear and power regression models were evaluated to estimate the crop coefficient (Kc). In the context of linear regression, the correlations between Food and Agriculture Organization (FAO)-based Kc and NDWI, NDRE, NDVI, and LAI-based Kc were 0.833, 0.870, 0.886, and 0.771, respectively. Strong correlation values in the case of power regression (NDWI: 0.876, NDRE: 0.872, NDVI: 0.888, LAI: 0.746) indicated an alternative approach to provide crop coefficients for the vegetation period. The VI-based ETc values were calculated using reference evapotranspiration (ET0) and VI-based Kc. The weather station data of CER were used to calculate ET0 based on Penman-Monteith estimation. Out of the Vis, NDWI and NDVI-based ETc performed the best both in the cases of linear (NDWI RMSE: 0.43 ± 0.12; NDVI RMSE: 0.43 ± 0.095) and power (NDWI RMSE: 0.44 ± 0.116; NDVI RMSE: 0.44 ± 0.103) approaches. The findings affirm the efficacy of the developed methodology in accurately assessing the evapotranspiration rate. Consequently, it offers a more refined temporal estimation of water requirements for maize cultivation in the region.

A Smart Food Donation System using Mobile Technology to Reduce Food Waste

Food wastage is a significant global challenge, with approximately one third of food produced for human consumption, amounting to 1.3 billion tonnes, being lost or wasted according to the Food and Agriculture Organization (FAO) of the UN. In India, around 40% of food produced goes to waste, with sources such as weddings, events, restaurants, hostels, and households contributing substantially to this issue. Numerous non-profit organizations in India are actively working to combat hunger, malnutrition, and food wastage by collecting surplus food and distributing it to those in need. This proposed project aims to tackle urban excess food waste and hunger-related deaths by developing an innovative application designed to manage a cooked food supply chain. Using an ERP model, this application will facilitate the connection between surplus and deficient food resources within a community network. The system will empower administrators to oversee donor and recipient details, evaluate hotels based on their contributions and feedback, and coordinate logistics effectively. Trusts and recipients will have the ability to register, locate nearby food resources through a matching algorithm, select and request food, engage in direct communication with donors, and provide valuable feedback. Donors will be able to register, input available food details, respond to requests, and communicate with trusts and recipients. Furthermore, employees and delivery personnel will have the tools to register, manage pickups and deliveries, and provide timely notifications upon completion. This comprehensive approach aims to establish an efficient and transparent solution for the redistribution of surplus food resources, ultimately contributing to the reduction of food waste and alleviation of hunger in communities

Boosting enabled efficient machine learning technique for accurate prediction of crop yield towards precision agriculture

Due to the limited availability of natural resources, it is essential that agricultural productivity keep pace with population growth. Despite unfavorable weather circumstances, this project's major objective is to boost production. As a consequence of technological advancements in agriculture, precision farming as a way for enhancing crop yields is gaining appeal and becoming more prevalent. When it comes to predicting future data, machine learning employs a number of methods, including the creation of models and the acquisition of prediction rules based on past data. In this manuscript, we examine various techniques to machine learning, as well as an automated agricultural yield projection model based on selecting the most relevant features. For the purpose of selecting features, the Grey Level Co-occurrence Matrix method is utilised. For classification, we make use of the AdaBoost Decision Tree, Artificial Neural Network (ANN), and K-Nearest Neighbour (KNN) algorithms. The data set that was used in this study is simply a compilation of information about a variety of topics, including yield, pesticide use, rainfall, and average temperature. This data collection consists of 33 characteristics or qualities in total. The crops soya beans, maze, potato, rice, paddy, wheat, and sorghum are included in this data collection. This data collection was made possible through the collaboration of the Food and Agriculture Organisation (FAO) and the World Data Bank, both of which make their data available to the public. The AdaBoost decision tree has achieved the highest level of accuracy possible when used to anticipate agricultural yield. Both the accuracy rate and the recall rate are quite high at 99 percent.

Systematic Assessment of Bottomland Resources Influenced by Waste Disposal

In Ile-Oluji, Nigeria, issues with waste disposal brought on by population growth have resulted in contamination of the bottomland resources that sustain humankind. Random soil samples were taken from a solid dumpsite and its adjacent closed bottomland at depths of 0–15, 15–30, and 30–75 cm and analyzed in the laboratory. Soil texture, soil moisture content (MC), porosity, bulk density, pH, electrical conductivity (EC), organic carbon (OC), potassium (K), calcium (Ca), magnesium (Mg), and sodium (Na) were measured. Also examined was the concentration of heavy metals such as lead (Pb), cadmium (Cd), arsenic (As), nickel (Ni), chromium (Cr), and manganese (Mn) in the samples. Soil moisture content (MC), porosity, bulk density, pH, and electrical conductivity (EC) ranged from 8.52 to 16.08%, 30.14 to 51.19%, 1.16 to 1.46 g/cm3, 6.98 to 7.58, and 299.82 to 432.61 μS/cm, respectively. The concentrations of nutrients and heavy metals (OC, K, Ca, Mg, and Na) and (Pb, Cd, As, Ni, Cr, and Mn) in the soil samples collected from the solid waste dumpsite and bottomland ranged respectively from 2.13–3.10%,, 3.98–6.57, 5.08–8.11, 5.41–7.11, and 0.98–2.61 Cmol/kg, and 6.83– 29.04, 0.00–0.35, 0.41–3.92, 0.89–3.46, 0.00–0.63, and 13.74–74.38 mg/kg. The highest concentrations of nutrients and heavy metals were found in the soil sample collected from the solid waste dumpsite between 0 and 15 cm of soil depth, and it was closely followed by the sample obtained from the bottomland at the same soil depth compared to other locations. The concentration of heavy metals did not exceed the limits established by the World Health Organization (WHO) and the Food and Agricultural Organization (FAO), but persistent dumping of waste in the area may eventually increase the concentration of heavy metals beyond the acceptable limit. There is a need for the locals to be aware that the growing of crops on dumpsites and closed adjacent bottomland due to its fertility status could result in the uptake of heavy metals and eventually end up in human or animal bodies. A measure to avoid dumping waste close to the bottomland should be put in place by ensuring the immediate construction of a standard environmental sanitary dumpsite in combination with the waste recycling strategy in the study area.

Food-Based Dietary Guidelines for Infants in Latin America and the Caribbean: A Systematic Review.

Food-based dietary guidelines (FBDGs) are tools for promoting healthy eating habits. For the population of children under two years old in Latin America and the Caribbean (LAC), there is a lack of reviews analyzing the quality of these guidelines. The objective of this systematic review is to evaluate publicly available FBDGs for the population under two years old in LAC until mid-2023. Guidelines aimed at caregivers of children were included, sourced from government websites in LAC countries and the Food and Agriculture Organization (FAO) portal. Documents targeted at healthcare professionals were excluded. For qualitative analysis, the Agree II guidelines assessment tool and the FAO guide principles for developing healthy and sustainable diets were used. The results showed that more recently released and revised FBDGs with a greater number of pages obtained better scores in both assessments. Additionally, out of the 32 LAC countries, only 13 had these FBDGs available on websites for public access. As a limitation, this study faced challenges in standardizing the searches on government websites. The authors emphasize the need to develop FBDGs for the population under two years old that align with current health and sustainability needs and promote health education.

The effect of carbon farming training on food security and development resilience in Northern Ghana

ABSTRACT Carbon farming has recently been advocated for as climate change and variability mitigation and/or adaptation strategy in global agriculture. In this study, we address an important research question of whether carbon farming training can improve household resilience capacity as well as food security by employing internationally standardized indicators. Household resilience capacity and its components are measured using the Food and Agriculture Organisation (FAO)’s resilience capacity index while the food security measures used include household and child food insecurity experience scale (FIES and CFIES), food consumption score (FCS) and household dietary diversity score (HDDS). We relied on doubly robust treatment effect estimators to account for potential selection bias and heterogeneity. We find that carbon farming training has no statistically significant effect on overall household resilience capacity. However, we find a large and statistically significant effect on key components of resilience (specifically, access to basic services, assets and social safety nets) and a marginal improvement in adaptive capacity. We also find statistically significant effect on FCS and HDDS but not for the other food security indicators (FIES and CFIES). Overall, the results suggest that agricultural training programs, particularly climate change adaptation capacity building initiatives, could improve important welfare measures in developing countries.

Revisiting the contribution of different factors in determining the changes in potential evapotranspiration over China.

In this paper, a daily gridded observation data across China from 1961 to 2022 were used to calculate daily potential evapotranspiration (PET). The observed variables included daily temperature, sunshine hours, average wind speed, and average relative humidity. PET was determined using the Penman-Monteith method recommended by the Food and Agriculture Organization (FAO). The long-term trend of PET was investigated in six regions of China during different seasons. To further compressed the influence of various meteorological factors on the PET trend, the contribution of each meteorological element to the long-term trend of PET was analyzed. The results indicate the following: (1) PET reaches its peak during summer which values from 145 to 640 mm, while it is lowest during winter from 21 to 244 mm. (2) The spatial patterns of PET trend changes are relatively similar across the four seasons, characterized by a decrease in the eastern regions and an increase in the western regions. The reduction is most significant during the summer and the range of trend is from -2.04 to 1.48 mm/day, while the increase becomes more pronounced in the winter which trend is from -0.34 to 0.53 mm/day. (3) The contribution of factors varies significantly across different regions. In spring and autumn, RH and U have little difference in contribution from other factors. But tsun is varies different from regions, the contribution value is largest in the northwest and smallest in the northeast. However, during summer, tsun become the most significant contributor in the YZ and SE regions, while in winter, Tm emerges as the most significant contributor to the PET trend in all six subregions. In SW, the contribution from U2 is the smallest in all seasons, with RH and Tm being the two crucial factors determining the PET trend in this region.

Assessment of Quality, Fungal Population and Diversity, of Irrigation Water in Selected Areas of Minna, Niger State, Nigeria

Water samples were collected at 3 slope positions (upper, middle and lower) from four locations practising irrigation agriculture in Minna as follows; Fadikwe, Mechanic village in keterin-gwari, Soje-A in kpakungu and Bali in Chanchaga and fitted to a Completely Randomized Design (CRD) having slope positions as replicates for each treatment. Water sampling, Physical and chemical properties and Fungi population and diversity were determined using standard methods. Data generated were subjected to Analysis of Variance (ANOVA) and means were separated using Least Significance Differences (LSD) and Duncan Multiple Range Test. Result obtained revealed that Chanchaga irrigation water recorded the highest fungi population of 1.6 x 107 CFU/ml why fungi diversity was the least at Chanchaga. The presence of _Geotrichum species_ (2.33 x 106CFU/ml), _Candida tropicalis_ (4.33 x 106CFU/ml) and _Torulopsis glabrata_ (1.67 x 106CFU/ml) in water obtained from Mechanic village may be due to the presence of hydrocarbons in the oil polluting the water. They are potential degraders of crude oil hydrocarbons. They may therefore be responsible for the value of Biochemical Oxygen Demand of 261 mg/l recorded at Mechanic village. The Biochemical Oxygen Demand values of 342 mg/l and 360.00mg/l recorded at Fadikwe and Soje A respectively may be due to the presence of _Aspergillus niger.Aspergillus niger_ is a utility biological indicator of level of degradation of pollutant. These values were however higher than the Food and Agriculture organisation (FAO) standards for irrigation water. Further studies should however be carried out to investigate the bioremediating potentials of the fungi species identified in irrigation water obtained from Chanchaga.

Challenges and opportunities when moving food production and consumption toward sustainable diets in the Nordics: a scoping review for Nordic Nutrition Recommendations 2023.

The terms 'Nordic countries' or 'The Nordics' include the five countries Denmark, Finland, Island, Norway, and Sweden. This review includes evaluation of the Nordic countries against Food and Agricultural Organisation (FAO)/World Health Organizations' (WHO) guiding principles for healthy, sustainable diets with respect to environmental impact (principles #9 - #13) and sociocultural aspects (principles #14 - #16). A food systems perspective is taken to summarize and discuss the most important challenges and opportunities for achieving sustainable diets. Food system, food security, self-sufficiency, and resilience perspectives are applied. The information can underpin decisions when developing and implementing Food Based Dietary Guidelines (FBDG) in the Nordics. None of the Nordic countries are on track to reach the 2030 UN climate and biodiversity goals. We describe how food production, processing, and consumption contribute to these and other environmental challenges, and what kinds of dietary changes/transitions consistent with these goals are required. A major challenge is the high production and consumption of meat and too low consumption of fish, vegetables, and fruits. Meat production is a major source of emissions and, together with farmed fish, heavily dependent on imported feed ingredients, leaving a large land-use and water footprint in exporting countries while domestic land resources are not used optimally. Dietary patterns have changed drastically over the past 50 years, and in large parts of the population, meat consumption has doubled since the 1970s, rendering historic food culture less useful as a basis for present-day recommendations. The Nordics have Europe's lowest use of antibiotics in animal and fish production and have made some progress in reducing food waste along the food chain. A major opportunity is better alignment of food production and consumption based on local or regional production potentials, in conjunction with better and more constructive integration with the global food system while integrating novel technologies to reduce emissions and resource use.