Food and Energy Security最新文献

Crop growth models, such as the WOrld FOod STudies (WOFOST) model, mimic the mechanistic processes involved in crop development, growth, and yield production. The accuracy of simulation is decreased in unfavorable low-temperature settings because these models do not accurately represent crop response processes in low-temperature stress. Enhancing the WOFOST crop growth model's accuracy in simulating crops' responses to cold temperatures is the aim of this work. Given its vulnerability to low temperatures, the inquiry uses winter wheat in Henan Province as a focal point. It integrates the WHEATGROW wheat phenology model with the Frost model of Lethal Temperature 50 (FROSTOL) inside the framework of the crop growth model. This link aims to improve simulation accuracy and supplement the model's mechanisms, particularly when it comes to the impact of low temperatures on crop development. The study uses Long Short-Term Memory networks to build a yield model that integrates remote sensing data with information from simulated crop models. Under low temperatures, the leaf area index, total above ground biomass, and total weight of storage organs of the model WWF—which combines FROSTOL and WHEATGROW with WOFOST—show a considerable decline. It was discovered that there is a greater improvement in simulation accuracy of the linked model WWF relative to the WOFOST model in frost years than in normal years, based on a comparison analysis between typical frost years and normal years. To be more precise, the improvement is 8.03% in frost years and 1.98% in regular years. When all is said and done, the coupled model advances our knowledge of how winter wheat is impacted by low temperatures.

The cover image is based on the Review Article Building forests for the future by A. Robert MacKenzie et al., https://doi.org/10.1002/fes3.518. Image Credit: Ian Crompton.

Xinyu Li, Wenzhen Liu, Gaoliang Wang, Samuel Sai-Ming Sun, Ling Yuan, Jingxue Wang. Food Energy Security. (2023) 00:e506.

The original version of this article contained an error in Figure 2, where the graph of Figure 2d is incorrect and does not match the figure legend. The error does not affect the rest of the article.

The corrected Figure 2 and accompanying legend appear below.

Increasing the application of nitrogen fertilizer is the main approach to increase rice production, but it also brings problems of environmental pollution and increases agricultural production costs. Cultivating high-yielding and high nitrogen use efficiency (NUE) rice varieties is an important approach to solving this problem. The rice varieties carrying dep1 (dense and erect panicle 1) have both high grain yield and high NUE. However, their plant traits have not been fully explored. In this study, two rice near-isogenic lines carrying dep1 (NIL-DEP1 and NIL-dep1) were grown in paddy fields under 0, 120 and 270 kg N ha⁻¹. We analyzed agronomic traits of panicle type, plant type, leaves and roots, and physiological traits of vascular bundles, photosynthetic rate and carbon and nitrogen transport. The results showed that the NIL-dep1 exhibited higher grain yield and NUE than NIL-DEP1, mainly due to the higher spikelet number per panicle, grain filling percentage and dry matter production. Compared with NIL-DEP1, NIL-dep1 had improved flag leaf morpho–physiological traits, including erect flag leaves, greater leaf thickness and specific leaf weight, higher root dry weight, root length, root volume and root surface area, and a better canopy structure, as reflected by a lower light interception percent and canopy extinction coefficient, leading to better photosynthetic performance and dry matter production. In addition, NIL-dep1 exhibited better vascular bundle traits of peduncle and enhanced dry matter, stem carbon and nitrogen translocation during grain filling. In conclusion, NIL-dep1 had high grain yield and NUE by improved agronomic and physiological traits and increasing carbon and nitrogen translocation during grain filling. These traits mentioned above could be used to select and breed high grain yield with high NUE rice varieties.

This review explores the potential of genetically engineering cyanobacteria with the aim of synthesizing high-value protein directly from atmospheric nitrogen. The article examines numerous techniques that may enhance protein synthesis in cyanobacteria, and discusses advantages, barriers, and opportunities for this strategy going forward. Genetic manipulation of cyanobacteria shows promise in sustainably raising protein production via reduced greenhouse gas emissions and lower dependence on synthetic fertilizers, but also potentially fewer environmental implications traditionally caused by conventional protein production methods. The article uncovers many difficulties in genetically modifying cyanobacteria for protein production. For example, genetically modified organisms (GMOs) have legal and regulatory ramifications that must be accounted for if ethical, moral and secure use of these technologies is to be ensured. Economic viability, too, must be evaluated, taking into consideration production costs, scalability, market demand and future market potential. We suggest that processing of cyanobacterial proteins in downstream stages need further development. Effective and economical methods are needed for protein extraction, purification, and formulation into commercially viable products. For successful application of cyanobacterial protein production at scale, such obstacles must be overcome. We conclude that genetic engineering of cyanobacteria for protein synthesis has a great deal of potential to offer a resource-effective and sustainable replacement for the synthesis of high-value proteins, so promoting a more sustainable and environmentally conscious future.

Fusarium disease and the consequent mycotoxin accumulation pose significant problem in maize cultivation, with fumonisins produced by Fusarium verticillioides posing a global health concern. To address this issue, a range of preventive measures (e.g. crop management techniques) can be implemented to minimize fungal infections. A promising strategy to counteract this issue involves the selection of genotypes with greater resistance to fungal pathogens. This approach has the potential to reduce the reliance on chemical inputs for controlling fungus growth or indirect infection vectors. Leveraging genetic approaches can help improve the economic sustainability of agriculture in the face of climate change challenges. In the present work, we assessed the importance of two husk leaf traits (coverage and number), their association with F. verticillioides infection, fumonisin content, and their potential influence on crop yield. The study was conducted in three locations in the North of Italy and 38 hybrids with varying resistance to F. Verticillioides were compared. The results obtained showed that husk coverage has a pivotal role not only in protecting maize ears from Fusarium infection but have also a significant impact on crop yield: a significant positive correlation was found between husk coverage and yield in all three locations (r = 0.33185; r = 0.51327 and r = 0.51207, respectively). Furthermore, in the field of Vicenza, a significant negative correlation was found between husk coverage and Fusarium severity (r = −0.41492). Husk coverage emerges as an important trait that merits inclusion in maize breeding programs, given its protective role against fungal infections and its favourable influence on both yield and grain quality.

Agricultural intensification affects natural and crop ecosystems, and increases the risk of agricultural pests in agroecosystems. Helicoverpa armigera Hübner (Lepidoptera: Noctuidae) is an important pest that damages a wide range of crops. However, the effect of agricultural intensification on the genetic diversity of this pest is still unclear. In this study, we investigated the effects of the composition and configuration of the landscape on the genetic diversity of the agricultural pest H. armigera based on cytochrome oxidase subunit I (COI) analyses. In total, 10 haplotypes were found in 2016 and 15 haplotypes in 2021 based on COI genes. The haplotype diversity and nucleotide diversity were the highest in the Anqiu (AQ) region during 2016 and in the Bincheng (BC) region during 2021. Haplotype 2 and haplotype 3 (Hap2 and Hap3) were the dominant haplotypes in the H. armigera population. Agricultural intensification had no effect on the genetic diversity of H. armigera between 2016 and 2021. Our study highlights the effect of agricultural intensification on the genetic diversity of H. armigera. Understanding the genetic consequences of agricultural intensification is essential for the green control of agricultural pests and the sustainable development of agriculture.

Many governments have set ambitious targets for tree planting and increased woodland cover as a key part of actions to reach net-zero carbon emissions by 2050. However, many uncertainties remain concerning how and where to expand tree cover, what species to plant, and how best to manage new plantations. Much contemporary forestry has been based on even-aged monocultures, largely because of perceived advantages for timber production. However, in order to play a key role in climate change mitigation future forests will have to achieve timber production (and wider ecosystem service provision) alongside resilience to biotic and abiotic challenge. It is therefore crucial that appropriate informed decisions are made with regard to the structure, composition, and planning of future forests, in order to provide sustainable solutions that provide environmental, economic, and health benefits to society. Genetically diverse, mixed, and irregular forests, with their higher biodiversity and niche complementarity, are promising new forest configurations for regulating the water cycle, storing carbon, and delivering other goods and services. In the following discussion, we have used UK information to illustrate the benefits of mixed woodland versus monocultures and highlighted current issues related to government initiatives and policies for current and future forests. However, similar issues and problems are encountered globally.

Different social protection programs are designed in low-income countries to eradicate poverty and improve the food security of poor people. Currently, the Urban Productive Safety Net Program (UPSNP) is designed to support those who are living in poverty and face food insecurity with predictable and reliable support through food, cash, or vouchers. However, limited empirical evidence has been presented about the significant impact of the program on the well-being of households who participated in the program and the factors that affect the households' decision to participate in the program. Hence, this study aims to evaluate the impact of participation in UPSNP on well-being using household survey data gathered from three main cities of Ethiopia: Dire Dawa, Harar, and Jigjiga in 2022. This study employed both propensity score matching (PSM) and endogenous switching regression (ESR) models to assess the impact of the UPSNP. The result shows that the probability of a household's participation decision is determined by the age of the household head, number of children, savings, house ownership, employment status of the household head, and shock. Furthermore, we found a consistently positive impact across models, indicating that participation in UPSNP reduces poverty and increases food security of households.