Antimicrobial resistance (AMR) is currently regarded by the World Health Organization (WHO) as one of the most significant risks to global public health. The most critical causes of AMR infections in humans are the misuse and overuse of antimicrobials in humans and farmed animals. The rising global demand for food of animal origin encourages the increase of animal production worldwide, especially in developing countries. Simultaneously, current farming practices often extensively use antimicrobials on animals, influencing bacterial AMR incidence. This study aims to evaluate the correlation between antimicrobial use (AMU) in farmed animals and the detection of AMR infections in humans, the effects of enforcing laws in animal farming in a country on AMR situation in the neighbors, and the potential of AMR to spread from one country to another. Using data from 30 largest animal-producing countries in different regions of the world, between 2010 and 2020, and a Spatial Durbin Model (SDM), we found that AMU in farmed animals increases AMR in humans and there is a spatial dependence between countries regarding AMR spreading. Such findings indicate that a globally coordinated strategy regulating AMU on farmed animals may reduce AMR emergence and worldwide spreading.

Livestock farming substantially contributes to the global economy and food security. However, it poses crucial environmental, animal welfare, and public health challenges. The main objective of this study is to quantify the global antimicrobial use (AMU) in cattle, chicken, and pig farming. This information is important for understanding the potential impact of farm AMU on the emergence and spread of antimicrobial resistance among animals and humans. Using the United States Department of Agriculture Production, Supply, and Distribution and the Food and Agriculture Organization databases, we estimated the total supply of cattle (in heads) and its distribution into four weight categories: calves (26%), cows (41%), heifers (4%), and bulls of more than one year (29%). Similarly, we calculated the total supply of pigs (in heads) and divided it into two weight categories: pigs (96%) and sows (4%). For chickens, we considered one weight category. We attributed to each category a standard weight according to the parameters set by the European Medicines Agency (EMA) to determine the animal biomass at risk of antimicrobial treatment, or population correction unit (PCU). Finally, we estimated the global PCUs and then the global AMU based on the average administered to the three species (in mg of active ingredients per kg PCU). With this method, we estimated a global annual AMU of 76 060 tonnes of antimicrobial active ingredients (2019-2021 average), of which 40 697 tonnes (or 53.5%) for cattle, 4 243 tonnes (or 5.6%) for chickens, and 31 120 tonnes (or 40.9%) for pigs. According to our assessment, global AMU leads to almost 20 000 tonnes less than the previous estimates due to a different evaluation of PCUs. In previous studies, PCUs were calculated on the liveweight at slaughtering of animals, while our method considers the age and sex of animals and their average weight at treatment. Our results are consistent with the World Organization for Animal Health (WOAH) estimate of 76 704 tonnes of veterinary antimicrobials globally consumed in 2018 for the total of food-producing animals (the WOAH estimation is based on sales and import data).

Global warming is the immediate consequence of increased greenhouse gasses emission. Agriculture is a significant source in terms of greenhouse gasses emission and on the other hand, the main sector in terms of producing food. As global food demand grows, the share of agriculture in the total greenhouse gasses emission will rise too. Therefore, agriculture needs to cut the greenhouse gasses emission. A response to the two important issues today, i.e. achieving food security and reducing greenhouse gasses emission is climate-smart agriculture. According to the Paris Agreement, an international effort to reduce greenhouse gasses emission, Iran has to decrease 12 percent of its greenhouse gasses emission by 2050, which all sectors have to contribute. Since the pathway to define strategies, is to explore the challenges; in this study, a seemingly unrelated regression technique has been used to model the climate-smart agriculture in Iran. Three main sub-sectors of agriculture; i.e. crops, livestock, and aquatics production, have been considered in the model to find the role of them in delivering food security and emitting greenhouse gasses. The findings show livestock and aquaculture sectors have had a positive significant impact in achieving food security. On the other hand, these sectors have had a positive significant effect on the emitting greenhouse gasses. Cropping system was not found to have a significant role in achieving food security and emitting greenhouse gasses in Iran although the expected signs (+) has been confirmed by the model. New research to explore appropriate technical and behavioral innovations needs to do on the specific-product-sector to be climate-friendly and sustainable. On the consumers hand, an encouragement to a more healthy diet with more vegetable, where is possible, also can reduce emissions. Finally, the key message from the assessments is the future legislative outlines for mitigation, adaptation and resource management as well as consumer behavior for how agriculture can deal with climate change.

This article aims to show the potential contribution of high-yielding rice varieties to achieve sustainable intensification in paddy farming, by focusing on a developing country. A comparative life cycle assessment of traditional vs. high-yielding varieties is carried out by comparing the area-based and yield-based results. Primary data are collected through a farm survey (49 farms in the Mazandaran province, Iran; spring 2018). The results highlight that high-yielding varieties can reduce the yield-scaled impacts. However, area-scaled impacts are subject to increase for most impact categories. Statistically significant trade-offs involve global warming potential (+13% per ha and −28% per t in high-yielding varieties) and fossil resource depletion (+15% per ha and −26% per t in high-yielding varieties). Pesticide management is the most alarming practice. High-yielding varieties increase pesticide consumption and related toxicity impacts both per t and per ha. This study is a new contribution to the literature by improving and broadening the mainstream productivity perspective of current life cycle assessment research about crop varieties. The lessons learnt from this study suggest that the trade-offs between yield-scaled and area-scaled impacts should be carefully considered by decision-makers and policymakers, especially in developing countries that, like Iran, are affected by the overexploitation of natural resources. Targeted policy and the development of farmer education and advisory services are needed to create the enabling conditions for farm management changes, including conscious use of production inputs while avoiding heuristics.

Purpose: Food is a basic need for human life. Ensuring food security requires guaranteeing adequate food availability, accessibility, and utilization along with the sustainability of the food system. Food availability can be improved by decreasing food losses. The goal of this study is to document the causes and quantify the amount of losses in Iran’s rice supply chain. Research method: A cross-sectional survey method was used to collect data through interviews with some actors of the rice production chain operating in Mazandaran province, Qaemshahr, in 2015, to approximate percentage weight losses at the different stages in the supply chain. Main findings: The rice losses are estimated to be about one-third of the production that could feed 18 million people per year. On the other hand, the rice losses imply an economic loss of 1,403 million U.S. dollars, annually, and losing some scare resources, such as water, in Iran. Limitations: It is not easy to apply the ways to collect the useful and more accurate data in order to find the most important reasons of food losses for each stage and process of the food supply chains. Originality/Value: It was found that it is necessary to invest in the marketing systems, renew the supply chain and improve knowledge of the actors of the rice chain -from producing to consuming- in Iran’s rice system to reduce the physical and economical estimated losses of rice.