Hasil untuk "Agriculture"

Qianqi Yang, Zhiyuan Li, Xiaoning Lu et al.

Soil heavy metal pollution has been becoming serious and widespread in China. To date, there are few studies assessing the nationwide soil heavy metal pollution induced by industrial and agricultural activities in China. This review obtained heavy metal concentrations in soils of 402 industrial sites and 1041 agricultural sites in China throughout the document retrieval. Based on the database, this review assessed soil heavy metal concentration and estimated the ecological and health risks on a national scale. The results revealed that heavy metal pollution and associated risks posed by cadmium (Cd), lead (Pb) and arsenic (As) are more serious. Besides, heavy metal pollution and associated risks in industrial regions are severer than those in agricultural regions, meanwhile, those in southeast China are severer than those in northwest China. It is worth noting that children are more likely to be affected by heavy metal pollution than adults. Based on the assessment results, Cd, Pb and As are determined as the priority control heavy metals; mining areas are the priority control areas compared to other areas in industrial regions; food crop plantations are the priority control areas in agricultural regions; and children are determined as the priority protection population group. This paper provides a comprehensive ecological and health risk assessment on the heavy metals in soils in Chinese industrial and agricultural regions and thus provides insights for the policymakers regarding exposure reduction and management.

Samir K. Banerjee, Florian Walder, L. Büchi et al.

Root-associated microbes play a key role in plant performance and productivity, making them important players in agroecosystems. So far, very few studies have assessed the impact of different farming systems on the root microbiota and it is still unclear whether agricultural intensification influences the structure and complexity of microbial communities. We investigated the impact of conventional, no-till, and organic farming on wheat root fungal communities using PacBio SMRT sequencing on samples collected from 60 farmlands in Switzerland. Organic farming harbored a much more complex fungal network with significantly higher connectivity than conventional and no-till farming systems. The abundance of keystone taxa was the highest under organic farming where agricultural intensification was the lowest. We also found a strong negative association (R2 = 0.366; P < 0.0001) between agricultural intensification and root fungal network connectivity. The occurrence of keystone taxa was best explained by soil phosphorus levels, bulk density, pH, and mycorrhizal colonization. The majority of keystone taxa are known to form arbuscular mycorrhizal associations with plants and belong to the orders Glomerales, Paraglomerales, and Diversisporales. Supporting this, the abundance of mycorrhizal fungi in roots and soils was also significantly higher under organic farming. To our knowledge, this is the first study to report mycorrhizal keystone taxa for agroecosystems, and we demonstrate that agricultural intensification reduces network complexity and the abundance of keystone taxa in the root microbiome.

D. Hou, David O’Connor, A. Igalavithana et al.

B. Glick

D. Holzworth, N. Huth, P. Voil et al.

R. Bommarco, D. Kleijn, S. Potts

N. Mueller, J. Gerber, M. Johnston et al.

P. Pingali

G. Qin, Zhaodong Niu, Jiangdong Yu et al.

Soil plays a fundamental role in food safety and the adverse effects of contaminants like heavy metal (loid)s on crop quality have threatened human health. Therefore, it is important to focus on the food safety and agricultural soil pollution by heavy metals, especially for China where the demand for food production is increasing. This review comprehensively introduced the current status of agricultural soil pollution by heavy metals in China, analyzed the main sources of contaminants, including the applications of pesticides and fertilizers, atmospheric deposition related to vehicle emissions and coal combustion, sewage irrigation and mining. Food safety and agricultural soil pollution by heavy metals, the removal technologies for soil remediation such as soil amendments, phytoremediation and foliar sprays were also introduced. The review can provide significant insights for policymakers, environmental engineers, and agro-technicians regarding soil contamination control and management strategies and technologies.

Yifen Shang, M. Hasan, G. Ahammed et al.

In the era of climate change, global agricultural systems are facing numerous, unprecedented challenges. In order to achieve food security, advanced nano-engineering is a handy tool for boosting crop production and assuring sustainability. Nanotechnology helps to improve agricultural production by increasing the efficiency of inputs and minimizing relevant losses. Nanomaterials offer a wider specific surface area to fertilizers and pesticides. In addition, nanomaterials as unique carriers of agrochemicals facilitate the site-targeted controlled delivery of nutrients with increased crop protection. Due to their direct and intended applications in the precise management and control of inputs (fertilizers, pesticides, herbicides), nanotools, such as nanobiosensors, support the development of high-tech agricultural farms. The integration of biology and nanotechnology into nonosensors has greatly increased their potential to sense and identify the environmental conditions or impairments. In this review, we summarize recent attempts at innovative uses of nanotechnologies in agriculture that may help to meet the rising demand for food and environmental sustainability.

Zhou Du, Xin Zhou, Yi Ling et al.

Gene Ontology (GO), the de facto standard in gene functionality description, is used widely in functional annotation and enrichment analysis. Here, we introduce agriGO, an integrated web-based GO analysis toolkit for the agricultural community, using the advantages of our previous GO enrichment tool (EasyGO), to meet analysis demands from new technologies and research objectives. EasyGO is valuable for its proficiency, and has proved useful in uncovering biological knowledge in massive data sets from high-throughput experiments. For agriGO, the system architecture and website interface were redesigned to improve performance and accessibility. The supported organisms and gene identifiers were substantially expanded (including 38 agricultural species composed of 274 data types). The requirement on user input is more flexible, in that user-defined reference and annotation are accepted. Moreover, a new analysis approach using Gene Set Enrichment Analysis strategy and customizable features is provided. Four tools, SEA (Singular enrichment analysis), PAGE (Parametric Analysis of Gene set Enrichment), BLAST4ID (Transfer IDs by BLAST) and SEACOMPARE (Cross comparison of SEA), are integrated as a toolkit to meet different demands. We also provide a cross-comparison service so that different data sets can be compared and explored in a visualized way. Lastly, agriGO functions as a GO data repository with search and download functions; agriGO is publicly accessible at http://bioinfo.cau.edu.cn/agriGO/.

X. Ju, G. Xing, Xin-ping Chen et al.

Hongkun Tian, Tianhai Wang, Yadong Liu et al.

Abstract Computer vision is a field that involves making a machine “see”. This technology uses a camera and computer instead of the human eye to identify, track and measure targets for further image processing. With the development of computer vision, such technology has been widely used in the field of agricultural automation and plays a key role in its development. This review systematically summarizes and analyzes the technologies and challenges over the past three years and explores future opportunities and prospects to form the latest reference for researchers. Through the analyses, it is found that the existing technology can help the development of agricultural automation for small field farming to achieve the advantages of low cost, high efficiency and high precision. However, there are still major challenges. First, the technology will continue to expand into new application areas in the future, and there will be more technological issues that need to be overcome. It is essential to build large-scale data sets. Second, with the rapid development of agricultural automation, the demand for professionals will continue to grow. Finally, the robust performance of related technologies in various complex environments will also face challenges. Through analysis and discussion, we believe that in the future, computer vision technology will be combined with intelligent technology such as deep learning technology, be applied to every aspect of agricultural production management based on large-scale datasets, be more widely used to solve the current agricultural problems, and better improve the economic, general and robust performance of agricultural automation systems, thus promoting the development of agricultural automation equipment and systems in a more intelligent direction.

Sarah Piehl, Anna Leibner, M. Löder et al.

Microplastic contamination of aquatic ecosystems is a high priority research topic, whereas the issue on terrestrial ecosystems has been widely neglected. At the same time, terrestrial ecosystems under human influence, such as agroecosystems, are likely to be contaminated by plastic debris. However, the extent of this contamination has not been determined at present. Via Fourier transform infrared (FTIR) analysis, we quantified for the first time the macro- and microplastic contamination on an agricultural farmland in southeast Germany. We found 206 macroplastic pieces per hectare and 0.34 ± 0.36 microplastic particles per kilogram dry weight of soil. In general, polyethylene was the most common polymer type, followed by polystyrene and polypropylene. Films and fragments were the dominating categories found for microplastics, whereas predominantly films were found for macroplastics. Since we intentionally chose a study site where microplastic-containing fertilizers and agricultural plastic applications were never used, our findings report on plastic contamination on a site which only receives conventional agricultural treatment. However, the contamination is probably higher in areas where agricultural plastic applications, like greenhouses, mulch, or silage films, or plastic-containing fertilizers (sewage sludge, biowaste composts) are applied. Hence, further research on the extent of this contamination is needed with special regard to different cultivation practices.

Manish Kumar, Xinni Xiong, Mingjing He et al.

Microplastics (MPs) as emerging persistent pollutants have been a growing global concern. Although MPs are extensively studied in aquatic systems, their presence and fate in agricultural systems are not fully understood. In the agricultural soils, major causes of MPs pollution include application of biosolids and compost, wastewater irrigation, mulching film, polymer-based fertilizers and pesticides, and atmospheric deposition. The fate and dispersion of MPs in the soil environment are mainly associated with the soil characteristics, cultivation practices, and diversity of soil biota. Although there is emerging pollution of MPs in the soil environment, no standardized detection and quantification techniques are available. This study comprehensively reviews the sources, fate, and dispersion of MPs in the soil environment, discusses the interactions and effects of MPs on soil biota, and highlights the recent advancements in detection and quantification methods of MPs. The prospects for future research include biomagnification potency, cytotoxic effects on human/animals, nonlinear behavior in the soil environment, standardized analytical methods, best management practices, and global policies in the agricultural industry for the sake of sustainable development.

English Only

D. Cox, K. A. Gomez, A. A. Gómez

L. Breiman, J. Friedman, R. Olshen et al.

T. Benton, J. Vickery, Jeremy D. Wilson

Oded Galor, Ömer Özak

This research explores the origins of observed differences in time preference across countries and regions. Exploiting a natural experiment associated with the expansion of suitable crops for cultivation in the course of the Columbian Exchange, the research establishes that pre-industrial agro-climatic characteristics that were conducive to higher return to agricultural investment, triggered selection, adaptation and learning processes that generated a persistent positive effect on the prevalence of long-term orientation in the contemporary era. Furthermore, the research establishes that these agro-climatic characteristics have had a culturally embodied impact on economic behavior such as technological adoption, education, saving, and smoking.