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China's gains in food production over the past four decades have been associated with substantial agricultural nitrogen losses, which contribute to air and water pollution, greenhouse gas emissions and damage to human health. Here, we explore the potential to improve agricultural production practices that simultaneously increase yields while addressing these environmental challenges. We link agronomic research with air quality modelling for an integrated assessment of four improved nitrogen management strategies: improved farm management practices with nitrogen use reductions; machine deep placement of fertilizer; enhanced-efficiency fertilizer use; and improved manure management. We find that simultaneous implementation of the four strategies provides the largest benefits, which include: reductions in PM concentrations and associated premature deaths; increases in grain yields and grain nitrogen use efficiency; reductions in NO leaching and runoff and greenhouse gas emissions. Total benefits of US$30 billion per year exceed the US$18 billion per year in costs. Our findings indicate that policies that improve farmers' agricultural nitrogen management in China will improve both food security and public health while addressing multiple environmental challenges. Similar increases in attention on agricultural policy around the world are likely to provide large benefits in food security, environmental integrity and public health.
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http://dx.doi.org/10.1038/s43016-020-00162-z | DOI Listing |
Genome Biol
September 2025
National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
Background: Soil salinization represents a critical global challenge to agricultural productivity, profoundly impacting crop yields and threatening food security. Plant salt-responsive is complex and dynamic, making it challenging to fully elucidate salt tolerance mechanism and leading to gaps in our understanding of how plants adapt to and mitigate salt stress.
Results: Here, we conduct high-resolution time-series transcriptomic and metabolomic profiling of the extremely salt-tolerant maize inbred line, HLZY, and the salt-sensitive elite line, JI853.
Theor Appl Genet
September 2025
Institute for Breeding Research on Agricultural Crops, Julius Kühn Institute (JKI) - Federal Research Centre for Cultivated Plants, Sanitz, 18190, Germany.
Low-cost and high-throughput RNA sequencing data for barley RILs achieved GP performance comparable to or better than traditional SNP array datasets when combined with parental whole-genome sequencing SNP data. The field of genomic selection (GS) is advancing rapidly on many fronts including the utilization of multi-omics datasets with the goal of increasing prediction ability and becoming an integral part of an increasing number of breeding programs ensuring future food security. In this study, we used RNA sequencing (RNA-Seq) data to perform genomic prediction (GP) on three related barley RIL populations.
View Article and Find Full Text PDFAm J Clin Nutr
September 2025
Cork Centre for Vitamin D and Nutrition Research, School of Food and Nutritional Sciences, University College Cork, Cork, Ireland. Electronic address:
Background: Data from dietary intervention studies to test the ability of sustainable diets to meet micronutrient (MN) requirements is required.
Objective: To compare MN intakes and status among adults who received dietary counselling to follow a sustainable diet or a standard healthy diet.
Methods: We conducted a single-blind, randomized controlled trial among 355 healthy adults aged 18-64 years in three centers over 12-weeks.
Methods
September 2025
School of Computer and Information Engineering, Henan University, Kaifeng, Henan, China; Henan Key Laboratory of Big Data Analysis and Processing, Henan University, Kaifeng, Henan, China. Electronic address:
Genomic selection (GS) is a breeding technique that utilizes genomic markers to predict the genetic potential of crops and animals. This approach holds significant promise for accelerating the improvement of agronomic traits and addressing food security challenges. While traditional breeding methods based on statistical or machine learning techniques have been useful in predicting traits for some crops, they often fail to capture the complex interactions between genotypes and phenotypes.
View Article and Find Full Text PDFHealth Place
September 2025
Edith Cowan University, School of Medical and Health Sciences, 270 Joondalup Dr, Joondalup, WA, 6027, Perth, Western Australia, Australia; Edith Cowan University, Nutrition and Health Innovation Research Institute, 270 Joondalup Dr, Joondalup, WA, 6027, Perth, Western Australia, Australia. Electroni
Food security is a particular challenge in rural, regional and remote locations due to complexities associated with food availability, access, utilisation, stability, agency and sustainability dimensions. Existing approaches, such as emergency food relief, have been found to inadequately address these challenges, suggesting that a comprehensive portfolio of solutions could be more effective. Understanding what food security initiative leaders operating in these areas consider important will help establish a shared goal to guide the development of a portfolio approach.
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