Deciphering the key factors affecting pesticide residue risk in vegetable ecosystem.

Soil contamination, particularly from pesticide residues, presents a significant challenge to the sustainable development of agricultural ecosystems. Identifying the key factors influencing soil pesticide residue risk and implementing effective measures to mitigate their risks at the source are essential. Here, we collected soil samples and conducted a comprehensive survey among local farmers in the Three Gorges Reserve Area, a major agricultural production region in Southwest China. Subsequently, employing a dual analytical approach combining structural equation modeling (SEM) and random forest modeling (RFM), we examined the effects of various factors on pesticide residue accumulation in vegetable ecosystems. Our SEM analysis revealed that soil characteristics (path coefficient 0.85) and cultivation factor (path coefficient 0.84) had the most significant effect on pesticide residue risk, while the farmer factors indirectly influenced pesticide residues by impacting both cultivation factors and soil characteristics. Further exploration using RFM identified the three most influential factors contributing to pesticide residue risk as cation exchange capacity (CEC) (account for 18.84%), cultivation area (account for 14.12%), and clay content (account for 13.01%). Based on these findings, we carried out experimental trials utilizing Integrated Pest Management (IPM) technology, resulting in a significant reduction in soil pesticide residues and notable improvements in crop yields. Therefore, it is recommended that governmental efforts should prioritize enhanced training for vegetable farmers, promotion of eco-friendly plant protection methods, and regulation of agricultural environments to ensure sustainable development.

Nitrogen in the Yangtze River Basin: Pollution Reduction through Coupling Crop and Livestock Production.

Livestock production poses a threat to water quality worldwide. A better understanding of the contribution of individual livestock species to nitrogen (N) pollution in rivers is essential to improve water quality. This paper aims to quantify inputs of dissolved inorganic nitrogen (DIN) to the Yangtze River from different livestock species at multiple scales and explore ways for reducing these inputs through coupling crop and livestock production. We extended the previously developed model MARINA (Model to Assess River Input of Nutrient to seAs) with the NUFER (Nutrient flows in Food chains, Environment, and Resource use) approach for livestock. Results show that DIN inputs to the Yangtze River vary across basins, sub-basins, and 0.5° grids, as well as across livestock species. In 2012, livestock production resulted in 2000 Gg of DIN inputs to the Yangtze River. Pig production was responsible for 55-85% of manure-related DIN inputs. Rivers in the downstream sub-basin received higher manure-related DIN inputs than rivers in the other sub-basins. Around 20% of the Yangtze basin is considered as a manure-related hotspot of river pollution. Recycling manure on cropland can avoid direct discharges of manure from pig production and thus reduce river pollution. The potential for recycling manure is larger in cereal production than in other crop species. Our results can help to identify effective solutions for coupling crop and livestock production in the Yangtze basin.

Modeling the Contribution of Crops to Nitrogen Pollution in the Yangtze River.

Agriculture contributes considerably to nitrogen (N) inputs to the world's rivers. In this study, we aim to improve our understanding of the contribution of different crops to N inputs to rivers. To this end, we developed a new model system by linking the MARINA 2.0 (Model to Assess River Input of Nutrient to seAs) and WOFOST (WOrld FOod STudy) models. We applied this linked model system to the Yangtze as an illustrative example. The N inputs to crops in the Yangtze River basin showed large spatial variability. Our results indicate that approximately 6,000 Gg of N entered all rivers of the Yangtze basin from crop production as dissolved inorganic N (DIN) in 2012. Half of this amount is from the production of single rice, wheat, and vegetables, where synthetic fertilizers were largely applied. In general, animal manure contributes 12% to total DIN inputs to rivers. Three-quarters of manure-related DIN in rivers are from vegetable, fruit, and potato production. The contributions of crops to river pollution differ among sub-basins. For example, potato is an important source of DIN in rivers of some upstream sub-basins. Our results may help to prioritize the dominant crop sources for management to mitigate N pollution in the future.

Prediction of the global occurrence of maize diseases and estimation of yield loss under climate change.

BACKGROUND: Climate change significantly impacts global maize production via yield reduction, posing a threat to global food security. Disease-related crop damage reduces quality and yield and results in economic losses. However, the occurrence of diseases caused by climate change, and thus crop yield loss, has not been given much attention. RESULTS: This study aims to investigate the potential impact of six major diseases on maize yield loss over the next 20 to 80 years under climate change. To this end, the Maximum Entropy model was implemented, based on Coupled Model Intercomparison Project 6 data. The results indicated that temperature and precipitation are identified as primary limiting factors for disease onset. Southern corn rust was projected to be the most severe disease in the future; with a few of the combined occurrence of all the selected diseases covered in this study were predicted to progressively worsen over time. Yield losses caused by diseases varied per continent, with North America facing the highest loss, followed by Asia, South America, Europe, Africa, and Oceania. CONCLUSION: This study provides a basis for regional projections and global control of maize diseases under future climate conditions. © 2024 Society of Chemical Industry.

Increasing cascade dams in the upstream area reduce nutrient inputs to the Three Gorges Reservoir in China.

The upstream cascade dams play an essential role in the nutrient cycle in the Yangtze. However, there is little quantitative information on the effects of upstream damming on nutrient retention in the Three Gorges Reservoir (TGR) in China. Here, we aim to assess the impact of increasing cascade dams in the upstream area of the Yangtze on Dissolved Inorganic Nitrogen and Phosphorus (DIN and DIP) inputs to the TGR and their retention in the TGR and to draw lessons for other large reservoirs. We implemented the Model to Assess River Inputs of Nutrients to seAs (MARINA-Nutrients China-2.0 model). We ran the model with the baseline scenario in which river damming was at the level of 2009 (low) and alternative scenarios with increased damming. Our scenarios differed in nutrient management. Our results indicated that total water storage capacity increased by 98 % in the Yangtze upstream from 2009 to 2022, with 17 new large river dams (>0.5 km3) constructed upstream of the Yangtze. As a result of these new dams, the total DIN inputs to the TGR decreased by 15 % (from 768 Gg year-1 to 651 Gg year-1) and DIP inputs decreased by 25 % (from 70 Gg year-1 to 53 Gg year-1). Meanwhile, the molar DIN:DIP ratio in inputs to the TGR increased by 13 % between 2009 and 2022. In the future, DIN and DIP inputs to the TGR are projected to decrease further, while the molar DIN:DIP ratio will increase. The Upper Stem contributed 39 %-50 % of DIN inputs and 63 %-84 % of DIP inputs to the TGR in the past and future. Our results deepen our knowledge of nutrient loadings in mainstream dams caused by increasing cascade dams. More research is needed to understand better the impact of increased nutrient ratios due to dam construction.

Co-benefits for net carbon emissions and rice yields through improved management of organic nitrogen and water.

Returning organic nutrient sources (for example, straw and manure) to rice fields is inevitable for coupling crop-livestock production. However, an accurate estimate of net carbon (C) emissions and strategies to mitigate the abundant methane (CH4) emission from rice fields supplied with organic sources remain unclear. Here, using machine learning and a global dataset, we scaled the field findings up to worldwide rice fields to reconcile rice yields and net C emissions. An optimal organic nitrogen (N) management was developed considering total N input, type of organic N source and organic N proportion. A combination of optimal organic N management with intermittent flooding achieved a 21% reduction in net global warming potential and a 9% rise in global rice production compared with the business-as-usual scenario. Our study provides a solution for recycling organic N sources towards a more productive, carbon-neutral and sustainable rice-livestock production system on a global scale.

Global food nutrients analysis reveals alarming gaps and daunting challenges.

Eliminating both overt and hidden hunger is at the core of the global food and nutrition security agenda. Yet, the collective state of nutrition security at the population level is not known. Here we quantify food-based availability of 11 essential nutrients for 156 countries using a food production-consumption-nutrition model, followed by assessment of the nutrient availability status as a ratio of recommended intake. For the baseline year 2017, global per capita availability was adequate for calorie and protein but in severe deficit for vitamin A and calcium (intake ratios, <0.60, where 1.0 is adequate) and moderate deficit for vitamin B12 (intake ratio, 0.76). At the country level, more than half of the 156 countries were in various degrees of deficit for all nine micronutrients. Disparities across regions or countries were enormous. We explore intervention strategies from an agriculture-food system perspective and discuss the daunting challenges of addressing nutrition security broadly.

Mitigating phosphorus pollution from detergents in the surface waters of China.

Phosphorus (P) from detergents contributes to water pollution and eutrophication. Understanding the impacts of detergent use on P inputs to surface waters and their main drivers is vital for supporting Sustainable Development Goals on clean water. This study aims to quantify past and future trends in P inputs to surface waters from detergent use in China. We modify the Model to Assess River Input of Nutrient to seAs (MARINA) model to assess the effects of past policies and explore options for the future on mitigating detergents P losses in China. The total consumption of detergents tripled from 2000 to 2018. However, P inputs to surface waters from detergent use decreased by 35% during these years. Although P losses vary across regions, most losses occurred in rural areas. Clearly, the P-free detergent policy which was initiated in the year 2000 has been effective. Without this policy, the detergent P losses would likely have increased fourfold during 2000-2018. In the future, detergent P inputs to surface waters in China may be further reduced to very low levels (95% reduction relative to 2018) by a combination of completely P-free detergents, an increasing urbanized population connected to sewage systems, and improving P removal in sewage treatment systems. Our results enhance the understanding of P pollution in surface waters from detergents and, illustrate the effectiveness of measures to control detergent P losses.

Hesperetin inhibits foam cell formation and promotes cholesterol efflux in THP-1-derived macrophages by activating LXRα signal in an AMPK-dependent manner.

Cholesterol efflux from macrophages is the first step of reverse cholesterol transport (RCT), whose increase inhibits cholesterol accumulation and foam cell formation to suppress atherogenesis. Hesperetin has been reported to exert several protective effects on cardiovascular diseases, while little is known about the role of hesperetin and its underlying mechanism in macrophage foam cell formation. In this study, we sought to investigate the potential effects of hesperetin on foam cell formation and cholesterol efflux by using human macrophages, focusing on liver X receptor alpha (LXRα) and AMPK. We found that hesperetin treatment reduced foam cell formation, intracellular cholesterol levels and the cholesterol esterification rate, and increased cholesterol efflux in THP-1 macrophages. Hesperetin increased the levels of LXRα protein and its targets, including ABCA1, ABCG1, SR-BI, and phosphorylated-AMPK. Meanwhile, the hesperetin-induced increase in LXRα expression was further increased by the AMPK agonist and inhibited by an AMPK inhibitor. Meanwhile, hesperetin increased the levels of LXRα mRNA and its target genes, all of which were decreased in cells transfected with the AMPKα1/α2 small interfering RNA (siRNA). Furthermore, the hesperetin-induced inhibition of foam cell formation and promotion of cholesterol efflux were decreased by transfection of AMPKα1/α2 siRNA. In conclusions, We are the first to report that hesperetin activate AMPK in THP-1-derived macrophages. This activation upregulats LXRα and its targets, including ABCA1, ABCG1 and SR-BI, which significantly inhibits foam cell formation and promotes cholesterol efflux. Our results highlight the therapeutic potential of hesperetin to possibly reduce foam cell formation. This new mechanism might contribute the anti-atherogenic effects of hesperetin.

Multi-pollutant assessment of river pollution from livestock production worldwide.

Livestock production is often a source of multiple pollutants in rivers. However, current assessments of water pollution seldomly take a multi-pollutant perspective, while this is essential for improving water quality. This study quantifies inputs of multiple pollutants to rivers from livestock production worldwide, by animal types and spatially explicit. We focus on nitrogen (N), phosphorus (P), and Cryptosporidium (pathogen). We developed the MARINA-Global-L (Model to Assess River Inputs of pollutaNts to seAs for Livetsock) model for 10,226 sub-basins and eleven livestock species. Global inputs to land from livestock are around 94 Tg N, 19 Tg P, and 2.9 × 1021 oocysts from Cryptosporidium in 2010. Over 57% of these amounts are from grazed animals. Asia, South America, and Africa account for over 68% of these amounts on land. The inputs to rivers are around 22 Tg Total Dissolved Nitrogen (TDN), 1.8 Tg Total Dissolved P (TDP), and 1.3 × 1021 oocysts in 2010. Cattle, pigs, and chickens are responsible for 74-88% of these pollutants in rivers. One-fourth of the global sub-basins can be considered pollution hotspots and contribute 71-95% to the TDN, TDP, and oocysts in rivers. Our study could contribute to effective manure management for individual livestock species in sub-basins to reduce multiple pollutants in rivers.