Climate Smart Agriculture最新文献

Trends in the research on soil nitrogen leaching from farmland: A bibliometric analysis (2014–2023) 农田土壤氮沥滤研究趋势：文献计量分析（2014-2023 年）

Climate Smart Agriculture

Pub Date : 2024-11-01 DOI: 10.1016/j.csag.2024.100026

Caixia Hu, Xinrui Wang, Jie Li, Lan Luo, Fang Liu, Wenhao Wu, Yan Xu, Houyu Li, Bingcang Tan, Guilong Zhang

This study aims to explore the current progress, hotspots, and future directions in the research on nitrogen (N) leaching from farmlands. We analyzed 793 publications on N leaching published from 2014 to 2023, which were collected from the Web of Science Core Collection database, using bibliometric tools such as CiteSpace and VOSviewer to visualize research networks and the thematic evolution of the field. The results revealed that China and the USA were the leading contributors to this field, which was driven by environmental policies and agricultural challenges in these countries. The Chinese Academy of Sciences, in cooperation with other institutions, produced the highest number of publications, reflecting a significant impact. High-frequency keywords, including “nitrate leaching,” “nitrogen management,” “cropping system,” and “yield,” indicated that the primary research themes were related to optimizing N fertilizer use efficiency while minimizing environmental impacts. Furthermore, emerging terms such as “organic nitrogen,” “controlled release urea,” and “microbial biomass” provided new insights into evolving research directions, emphasizing the crucial role of integrating sustainable nutrient management strategies to address groundwater quality and environmental sustainability goals. Despite these advances, a gap remains in understanding the link between microbial community dynamics, particularly in terms of functional microbes involved in the N cycle, and N leaching. In future studies, researchers should prioritize investigations of the role of microbiomes in N loss from farmlands by employing advanced modeling approaches and utilizing stable isotope tracing techniques to advance the field. These findings provide valuable guidance for future research directions and policy-making efforts to enhance agricultural sustainability and environmental protection.

本研究旨在探讨农田氮（N）淋溶研究的当前进展、热点和未来方向。我们利用 CiteSpace 和 VOSviewer 等文献计量工具，分析了从 Web of Science Core Collection 数据库中收集的 2014 年至 2023 年发表的 793 篇有关氮沥滤的论文，以可视化研究网络和该领域的主题演变。研究结果表明，中国和美国是该领域的主要贡献者，这主要是受这两个国家的环境政策和农业挑战的推动。中国科学院与其他机构合作发表的论文数量最多，反映出其影响力巨大。高频关键词包括 "硝酸盐沥滤"、"氮肥管理"、"种植系统 "和 "产量"，表明主要研究主题与优化氮肥使用效率、同时最大限度地减少对环境的影响有关。此外，"有机氮"、"控释尿素 "和 "微生物生物量 "等新兴术语为研究方向的演变提供了新的视角，强调了整合可持续养分管理策略对于实现地下水质量和环境可持续性目标的关键作用。尽管取得了这些进展，但在了解微生物群落动态（尤其是参与氮循环的功能微生物）与氮沥滤之间的联系方面仍存在差距。在未来的研究中，研究人员应优先调查微生物群落在农田氮流失中的作用，采用先进的建模方法，并利用稳定同位素追踪技术来推动这一领域的研究。这些发现为未来的研究方向和政策制定工作提供了宝贵的指导，以提高农业的可持续性和环境保护。

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引用次数: 0

The potential to reduce runoff generation through improving cropping and tillage practices in a sub-humid continental climate 在亚湿润大陆性气候条件下通过改进种植和耕作方法减少径流产生的潜力

Climate Smart Agriculture

Pub Date : 2024-11-01 DOI: 10.1016/j.csag.2024.100021

Jian Liu , David A. Lobb , Jane A. Elliott , Merrin L. Macrae , Helen M. Baulch , Diogo Costa

Agricultural sustainability is threatened by both water deficit and water excess, especially at the presence of extreme meteorological events resulting from climate change. However, there has been lack of demonstrations on management options with long-term values for agricultural adaptation to runoff. Using 20 years of monitoring data (1993–2012) for two experimental fields in the Canadian Prairies as a case study, we quantified the effects of rainfall characteristics, crop type and biomass, and tillage on growing-season runoff generation using regression analyses and thereafter scenario comparisons. With growing-season gross rainfall ranging between 183 and 456 mm, runoff responses varied between 0 and 59 mm. Over the 20-year study period, 70%–74 % of the growing-season runoff was generated by rainfall events >100 mm. Compared to high-intensity tillage, long-term conservation tillage reduced both overall runoff and runoff in large events likely by improving water infiltration. Under both tillage methods, growing-season runoff significantly increased with increasing rainfall but decreased with increasing biomass (R² range: 0.40–0.58; p range: 0.0007–0.02). At the event level, the rainfall-runoff relationship followed a piecewise regression model (C_d = 0.82; p < 0.0001; “breakpoint” rainfall event = 105 mm), in which runoff increased slowly before reaching the “breakpoint” but rose sharply afterwards. Due to a greater biomass, canola resulted in less runoff than wheat. Scenario analyses showed that increasing crop biomass by 50 % under the current average rainfall conditions could reduce runoff by 81–86 % in wheat and 100 % in canola. The reduction may be attributed to the combined effects of crop on interception, evapotranspiration, and infiltration. In conclusion, although in a sub-humid continental climate like the Canadian Prairies there are generally low amounts of rainfall runoff, this study demonstrates significant runoff in some years, especially following large rainfall events. Runoff generation can be significantly reduced through improving cropping and tillage practices, and such effects on regional water retention should be further assessed by considering the past and future changes in climate and management.

农业的可持续发展受到水资源短缺和过剩的威胁，尤其是在气候变化导致极端气象事件的情况下。然而，在农业适应径流方面，一直缺乏具有长期价值的管理方案示范。以加拿大草原两块试验田 20 年（1993-2012 年）的监测数据为例，我们通过回归分析和此后的情景比较，量化了降雨特征、作物类型和生物量以及耕作对生长季径流产生的影响。生长季总降雨量介于 183 毫米和 456 毫米之间，径流响应介于 0 毫米和 59 毫米之间。在 20 年的研究期间，70%-74% 的生长季径流是由 100 毫米的降雨量产生的。与高强度耕作相比，长期保护性耕作减少了总体径流和大降雨量时的径流，这可能是通过提高水的渗透率实现的。在两种耕作方法下，生长季径流随着降雨量的增加而显著增加，但随着生物量的增加而减少（R2范围：0.40-0.58；P范围：0.0007-0.02）。在事件水平上，降雨与径流的关系遵循片断回归模型（Cd = 0.82；p < 0.0001；"断点 "降雨事件 = 105 毫米），其中径流在达到 "断点 "之前缓慢增加，但在达到 "断点 "之后急剧增加。由于生物量较大，油菜籽的径流量比小麦少。情景分析表明，在当前平均降雨量条件下，作物生物量增加 50%，可使小麦径流量减少 81-86%，油菜籽径流量减少 100%。径流减少的原因可能是作物对截流、蒸散和渗透的综合影响。总之，尽管在加拿大大草原这样的亚湿润大陆性气候中，降雨径流量通常较低，但这项研究表明，在某些年份，尤其是在降雨量较大的年份，径流量很大。通过改进种植和耕作方法，可大大减少径流的产生，而且应考虑到气候和管理方面过去和未来的变化，进一步评估这种情况对区域水源涵养的影响。

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引用次数: 0

Leveraging crop yield forecasts using satellite information for early warning in Senegal 利用卫星信息对塞内加尔作物产量预测进行预警

Climate Smart Agriculture

Pub Date : 2024-11-01 DOI: 10.1016/j.csag.2024.100024

Shweta Panjwani , Mahesh Jampani , Mame H.A. Sambou , Giriraj Amarnath

Agricultural losses driven by climate variability and anthropogenic pressures have severely impacted food security in Senegal. There is a crucial need to generate early warning signals for the upcoming season to enhance food security in response to the sudden climate shocks like drought. In this study, we investigated the spatial distribution of maize and groundnut using factor analysis with a principal component approach. We aimed to identify suitable predictors of crop yields for the development of a seasonal yield prediction model. Subsequently, multi-regression analysis was performed to predict crop yield based on various combinations of satellite-derived vegetation and climate (rainfall) datasets as well as agronomic data from Senegal's 40 districts between 2010 and 2021. Studies revealed a strong correlation between seasonal rainfall (May to September) and crop yield: a 10–20 % decline in rainfall can lead to crop losses. The accuracy of the yield prediction model, built on the best performing scenarios for each district based on monsoon onset, duration, and planting time, exceeded 0.5 (R-squared) for all districts when combining rainfall and normalized difference vegetation index (NDVI) data. The model prediction accuracy varied between 0.6 and 0.8 for major crop growing areas. The study emphasizes that refining the yield prediction model using machine learning techniques can improve its accuracy and enable its implementation in early warning systems. This enhanced capability could bolster Senegal's resilience to climate change by aiding decision-makers and planners in developing more effective strategies to ensure food security.

气候多变性和人为压力造成的农业损失严重影响了塞内加尔的粮食安全。因此，亟需为即将到来的季节发出预警信号，以加强粮食安全，应对干旱等突发性气候冲击。在这项研究中，我们采用主成分方法进行因子分析，调查了玉米和落花生的空间分布。我们的目的是找出合适的作物产量预测因子，以开发季节性产量预测模型。随后，根据卫星植被和气候（降雨量）数据集的不同组合，以及 2010 年至 2021 年期间塞内加尔 40 个地区的农艺数据，对作物产量进行了多元回归分析预测。研究显示，季节性降雨量（5 月至 9 月）与作物产量之间存在密切联系：降雨量减少 10-20% 会导致作物减产。产量预测模型是根据季风开始时间、持续时间和播种时间为每个地区制定的最佳方案建立的，在结合降雨量和归一化差异植被指数（NDVI）数据时，所有地区的预测精度都超过了 0.5（R 平方）。主要作物种植区的模型预测精度介于 0.6 和 0.8 之间。研究强调，利用机器学习技术完善产量预测模型可以提高其准确性，并使其能够应用于预警系统。这种能力的提高可以帮助决策者和规划者制定更有效的战略，确保粮食安全，从而增强塞内加尔应对气候变化的能力。

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引用次数: 0

Assessing spatiotemporal variations of soil organic carbon and its vulnerability to climate change: A bottom-up machine learning approach 评估土壤有机碳的时空变化及其对气候变化的脆弱性：自下而上的机器学习方法

Climate Smart Agriculture

Pub Date : 2024-11-01 DOI: 10.1016/j.csag.2024.100025

Qichen Wang , Yinuo Shan , Wenbo Shi , Fubo Zhao , Qiang Li , Pengcheng Sun , Yiping Wu

Soil organic carbon (SOC) is a crucial component of the terrestrial carbon cycle and essential for agricultural productivity. Quantifying its sensitivity to future climate change is vital for sustaining agricultural practices and mitigating greenhouse gas emissions. However, this remains a challenge as long-term SOC data are scarce and substantial uncertainties regarding future climate scenarios. This study presents a bottom-up machine learning framework to assess the spatiotemporal variations of SOC and its vulnerability to climate change in the Jinghe River Basin, a typical loess hilly and gully watershed. Firstly, the long-term (2000–2023) dynamics of SOC was estimated by integrating in-situ measurements with machine learning techniques. Results show that the high SOC values are primarily distributed in the farmland of the mountain-loess transition zone, while the low-value areas are mainly found in the loess region. During the study period, the SOC content exhibited a slight increasing trend with a rate of 0.02 g kg⁻¹ yr⁻¹ (p = 0.449). The vulnerability of farmland surface SOC to future climate change was then evaluated by combining a robust machine learning model with the bottom-up framework. To this end, the study explored a wide range of possible future climates to identify critical climate thresholds and their spatial variation across the basin’s farmlands. Based on this analysis, this research found that the farmland in the northern basin is generally more susceptible to changing climate with even marginal rises in temperature could lead to severe loss in SOC. These results highlight the need for proactive climate adaptation strategies to safeguard SOC in vulnerable agricultural landscapes, ensuring soil health and resilience in the face of climate change.

土壤有机碳（SOC）是陆地碳循环的重要组成部分，对农业生产力至关重要。量化土壤有机碳对未来气候变化的敏感性对于维持农业生产和减少温室气体排放至关重要。然而，由于长期 SOC 数据稀缺，且未来气候情景存在很大的不确定性，这仍然是一项挑战。本研究提出了一个自下而上的机器学习框架，以评估泾河流域（典型的黄土丘陵沟壑流域）SOC 的时空变化及其对气候变化的脆弱性。首先，利用机器学习技术整合原位测量数据，估算了 SOC 的长期（2000-2023 年）动态变化。结果表明，SOC 高值区主要分布在山地-黄土过渡带的农田中，而低值区主要分布在黄土地区。在研究期间，SOC 含量呈轻微增长趋势，增长率为 0.02 g kg-1 yr-1（p = 0.449）。随后，通过将稳健的机器学习模型与自下而上的框架相结合，评估了农田地表 SOC 对未来气候变化的脆弱性。为此，研究探索了多种可能的未来气候，以确定临界气候阈值及其在盆地农田中的空间变化。基于这一分析，本研究发现，盆地北部的农田一般更容易受到气候变化的影响，即使气温略有上升，也会导致 SOC 的严重损失。这些结果突出表明，有必要采取积极的气候适应战略，以保护脆弱农业景观中的 SOC，确保土壤健康和面对气候变化时的恢复能力。

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引用次数: 0

Maize–peanut intercropping and N fertilization changed the potential nitrification rate by regulating the ratio of AOB to AOA in soils 玉米-花生间作和氮肥通过调节土壤中 AOB 与 AOA 的比例改变潜在硝化率

Climate Smart Agriculture

Pub Date : 2024-11-01 DOI: 10.1016/j.csag.2024.100023

Yongyong Zhang , Fengyan Zhao , Zhanxiang Sun , Wei Bai , Chen Feng , Anita C. Risch , Liangshan Feng , Beat Frey

Maize–peanut intercropping could potentially mitigate nitrogen (N) loss from the soil, a process primarily governed by the net nitrification rate. However, the impact of maize–peanut intercropping on the potential nitrification rate (PNR) and its relationships with key players, such as ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB), are not well understood. Herein, we conducted a field experiment involving two management systems and two crops, namely, maize (MP_m) and peanut (MP_p) intercropping, maize monoculture (MM), and peanut monoculture (PM), under three N fertilization rates (no N fertilization, 150 kg N ha⁻¹, and 300 kg N ha⁻¹). Under intercropping (MP_m and MP_p), the abundance of AOA amoA gene increased by 64.8 % and 60.3 % and the abundance of AOB amoA gene increased by 63.2 % and 68.2 % compared to the MM and PM monoculture systems, respectively. Furthermore, the abundances of AOA and AOB decreased in MP_p and MM, while AOB increased in MP_m and PM across the N fertilization gradient. The PNR increased corresponding to the N fertilization rates, with intercropping enhancing the PNR in peanut-planted soil but reducing the PNR in maize-planted soil compared to monocropping. Notably, no significant positive relationship between the abundances of AOA or AOB and the PNR. Random forest analysis indicated that the AOB/AOA ratio was an important predictor of the PNR. N fertilization and intercropping regulated the AOB/AOA ratio mainly through controlling the ammonia content and the soil C/N, respectively. These findings highlight the substantial impacts of N fertilization and intercropping on PNR, with the AOB/AOA ratio emerging as a valuable predictive indicator for the PNR.

玉米-花生间作有可能减轻土壤中氮（N）的流失，这一过程主要受净硝化率的制约。然而，玉米-花生间作对潜在硝化率（PNR）的影响及其与氨氧化古细菌（AOA）和氨氧化细菌（AOB）等关键角色的关系尚不十分清楚。在此，我们进行了一项田间试验，涉及两种管理制度和两种作物，即玉米（MPm）和花生（MPp）间作、玉米单作（MM）和花生单作（PM），并采用三种氮肥施用率（不施用氮肥、每公顷施用 150 千克氮肥和每公顷施用 300 千克氮肥）。与 MM 和 PM 单作相比，在间作（MPm 和 MPp）条件下，AOA amoA 基因的丰度分别增加了 64.8% 和 60.3%，AOB amoA 基因的丰度分别增加了 63.2% 和 68.2%。此外，在整个氮肥梯度中，MPp 和 MM 的 AOA 和 AOB 丰度下降，而 MPm 和 PM 的 AOB 丰度上升。PNR随氮肥施用量的增加而增加，与单作相比，间作提高了花生种植土壤的PNR，但降低了玉米种植土壤的PNR。值得注意的是，AOA 或 AOB 的丰度与 PNR 之间没有明显的正相关关系。随机森林分析表明，AOB/AOA 比率是预测 PNR 的重要指标。氮肥和间作主要分别通过控制氨含量和土壤碳/氮来调节 AOB/AOA 比率。这些发现凸显了氮肥和间作对PNR的重大影响，而AOB/AOA比值则成为预测PNR的重要指标。

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引用次数: 0

Unveiling the top-down control of soil viruses over microbial communities and soil organic carbon cycling: A review 揭示土壤病毒自上而下对微生物群落和土壤有机碳循环的控制：综述

Climate Smart Agriculture

Pub Date : 2024-10-17 DOI: 10.1016/j.csag.2024.100022

Shuo Wang , Dong Zhu , Tida Ge , Yongfeng Wang , Ying Zhang , Chao Liang , Hanpeng Liao , Xiaolong Liang

Soil viruses play a pivotal yet underexplored role in microbial community succession and soil organic matter (SOM) turnover. This review synthesizes current knowledge on the mechanisms by which soil viruses influence SOM dynamics. It highlights how viral lysis accelerates microbial turnover and restructures microbial communities and how these processes rewire nutrient cycling and substantially fuel microbial metabolism. Furthermore, we also discussed the critical roles of virus-carried auxiliary metabolic genes (AMGs) in microbial processes, the degradation of complex organic materials and nutrient cycling. In together, this review emphasizes the significance of virus-microbe interactions in regulating SOM formation, transformation, and stabilization, and underscores the need and urgency for further research to achieve a comprehensive understanding of how soil viruses contribute to carbon cycling and ecosystem sustainability. Understanding virus-microbe-environment interactions is crucial for developing strategies to enhance soil carbon storage, mitigate climate change, and promote sustainable soil management practices.

土壤病毒在微生物群落演替和土壤有机质（SOM）周转中发挥着举足轻重的作用，但这方面的研究还不够深入。本综述综合了目前关于土壤病毒影响 SOM 动态机制的知识。它重点介绍了病毒裂解如何加速微生物更替和重组微生物群落，以及这些过程如何重新连接养分循环和大大促进微生物新陈代谢。此外，我们还讨论了病毒携带的辅助代谢基因（AMGs）在微生物过程、复杂有机物降解和养分循环中的关键作用。综上所述，本综述强调了病毒-微生物相互作用在调节 SOM 的形成、转化和稳定方面的重要意义，并强调了进一步研究的必要性和紧迫性，以便全面了解土壤病毒如何促进碳循环和生态系统的可持续性。了解病毒-微生物-环境之间的相互作用对于制定提高土壤碳储存、减缓气候变化和促进可持续土壤管理实践的战略至关重要。

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引用次数: 0

An exploration of the latest developments, obstacles, and potential future pathways for climate-smart agriculture 探索气候智能型农业的最新发展、障碍和未来可能的发展道路

Climate Smart Agriculture

Pub Date : 2024-09-24 DOI: 10.1016/j.csag.2024.100020

Asif Raihan , Mohammad Ridwan , Md Shoaibur Rahman

Global climate change presents major challenges to agricultural production, the most significant this century being mitigating greenhouse gas (GHG) emissions and achieving food security. Climate-smart agriculture (CSA) is a conceptual framework that offers potential solutions to these multifaceted problems. Sustainable agriculture can be achieved by implementing strategies aimed at enhancing adaptation, reducing GHG emissions, and safeguarding national food security. However, there has been limited critical examination of the advances made in CSA within emerging and developed nations. This study provides a timely, informative, and comprehensive review of the academic literature, collating recent advances, challenges, and potential future directions of CSA. It identifies and analyzes a range of pertinent issues and obstacles, and offers policy recommendations to foster cooperation and drive forward the objectives of CSA. Future development of CSA is expected to focus on leveraging advanced internet technologies to enhance agricultural data security, optimize cropping patterns, and improve management techniques. This will encompass the integration of precision farming and genetic enhancement technologies to boost crop yields in the face of changing climatic conditions.

全球气候变化给农业生产带来了重大挑战，本世纪最重要的挑战是减少温室气体排放和实现粮食安全。气候智能型农业（CSA）是一个概念框架，为这些多方面的问题提供了潜在的解决方案。可持续农业可以通过实施旨在加强适应性、减少温室气体排放和保障国家粮食安全的战略来实现。然而，对于新兴国家和发达国家在 CSA 方面取得的进展，批判性的研究还很有限。本研究对学术文献进行了及时、翔实和全面的回顾，整理了 CSA 的最新进展、挑战和潜在的未来方向。它指出并分析了一系列相关问题和障碍，并提出了促进合作和推动 CSA 目标的政策建议。CSA 的未来发展预计将侧重于利用先进的互联网技术加强农业数据安全、优化种植模式和改进管理技术。这将包括整合精准农业和基因强化技术，以在不断变化的气候条件下提高作物产量。

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引用次数: 0

Site-based climate-smart tree species selection for forestation under climate change 为气候变化下的植树造林选择基于地点的气候智能树种

Climate Smart Agriculture

Pub Date : 2024-09-12 DOI: 10.1016/j.csag.2024.100019

Wenhuan Xu , Anil Shrestha , Guangyu Wang , Tongli Wang

Global climate change threatens ecosystem functions and resilience, prompting large-scale planting initiatives to mitigate its impacts. To ensure new plantations are adaptive to future climates, it is crucial to consider climate mismatches resulting from climate change when selecting tree species. However, current research is all species-based, which is not effective for species selection across species at specific plantation sites. Our research developed a novel site-based approach that can identify optimal tree species for specific planting sites under projected future climates. We evaluated the feasibility and effectiveness of this method across 10 representative sites in diverse climatic zones in China based on climate niche projections for 100 key tree species. Our findings demonstrated the necessity and effectiveness of this approach, which can select a suit of suitable tree species tailored for any potential planting site across China under different climate change scenarios. For instance, at Tibet Dongjiu Forest farm, Aibes densa and Quercus pannosa currently showed high suitability scores above 0.8 (on a scale of 0–1). However, by the 2080s, Aibes densa's suitability was projected to drop to 0.25, while Quercus pannosa was expected to maintain its suitability. Conversely, Quercus aquifolioides currently had a low suitability of 0.08, but it was projected to increase to 0.74 by the 2080s. These findings demonstrate the importance of using this approach to avoid selecting the wrong species or overlooking potentially suitable species. In addition, our simulation analysis suggests that a dataset of 40–50 species is necessary to ensure that most planting sites can identify 2–3 suitable species. This advancement significantly enhances the precision and effectiveness of tree species selection strategies for local practitioners, offering vital insights for forestry, conservation, and ecological restoration projects. These results highlight the tremendous potential and practical applicability of our site-based approach in enhancing forestry adaptation and ecological functions in response to global climate change.

全球气候变化威胁着生态系统的功能和恢复能力，促使人们采取大规模植树造林措施来减轻气候变化的影响。为确保新种植园能够适应未来气候，在选择树种时必须考虑气候变化造成的气候错配。然而，目前的研究都是以树种为基础的，这对于在特定种植地点跨树种选择树种并不有效。我们的研究开发了一种新颖的基于地点的方法，可在预测的未来气候条件下确定特定种植地点的最佳树种。我们根据对 100 种主要树种的气候生态位预测，在中国不同气候带的 10 个代表性地点评估了这种方法的可行性和有效性。我们的研究结果证明了这种方法的必要性和有效性，它可以在不同的气候变化情景下，为中国任何潜在的种植地点选择适合的树种。例如，在西藏东久林场，艾比斯丹萨（Aibes densa）和枹罕（Quercus pannosa）目前的适宜性得分高于 0.8（0-1 分）。然而，到 20 世纪 80 年代，Aibes densa 的适宜性预计将下降到 0.25，而柞树的适宜性预计将保持不变。相反，Quercus aquifolioides 目前的适宜度较低，仅为 0.08，但预计到 2080 年代将增至 0.74。这些发现表明，使用这种方法可以避免选择错误的物种或忽略潜在的适宜物种。此外，我们的模拟分析表明，有必要建立一个包含 40-50 个物种的数据集，以确保大多数种植地点都能确定 2-3 个合适的物种。这一进步大大提高了当地从业人员选择树种策略的精确性和有效性，为林业、自然保护和生态恢复项目提供了重要启示。这些结果凸显了我们基于地点的方法在提高林业适应性和生态功能以应对全球气候变化方面的巨大潜力和实际应用性。

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引用次数: 0

Sugar competition is important for sheath blight resistance in rice towards climate adaptation 糖竞争对水稻抗鞘枯病以适应气候非常重要

Climate Smart Agriculture

Pub Date : 2024-08-28 DOI: 10.1016/j.csag.2024.100018

Shuo Yang , Chunyan Huang , Dandan Li , Naoki Yamamoto , Xiaofeng Zhu , Yuanhu Xuan

Sheath blight (ShB) caused by Rhizoctonia solani Kühn is one of the most serious diseases in rice and is highly susceptible to climate and environmental influences, high humidity climate conditions combined with higher temperatures often lead to more severe occurrences of ShB. The heterotrophic R. solani and rice might compete for sugar at the border of interaction; however, the underlying mechanism remains unclear. In this study, we demonstrated that the expression level of Sugar will eventually be exported transporters (SWEETs) induction was higher in ShB susceptible varieties than in ShB resistant varieties by R. solani inoculation. Inoculation of R. solani revealed that most sweet mutants were less susceptible to ShB than the wild-type. Also, sugar transporters (STPs) gene expression was sensitive to R. solani infection. STPs were localized at the plasma membrane and transported hexose in yeast. Knockdown of STP4 increased the susceptibility of rice to ShB. Interestingly, sequence analysis identified two monosaccharide transporter genes (hereafter named RsMST). RsMSTs transported 2-deoxyglucose, a toxic glucose analog in yeast, suggesting their role as glucose transporter. Spray-induced gene silencing of RsMST1 or RsMST2 dramatically suppressed their expression level and reduced virulence of R. solani. These data suggested that R. solani might induce SWEETs to efflux sugar from the cytosol to apoplast, and STP and RsMSTs compete for sugar at the apoplast for host defense and pathogen virulence. This study provided important insights for ShB-resistant breeding in rice.

由根瘤菌（Rhizoctonia solani Kühn）引起的鞘枯病（ShB）是水稻最严重的病害之一，极易受到气候和环境的影响，高湿度气候条件加上较高的温度往往会导致鞘枯病更加严重。异养菌 R. solani 和水稻可能会在相互作用的边界上争夺糖分，但其潜在机制仍不清楚。在本研究中，我们证明了接种 R. solani 后，Sugar will eventually be exported transporters（SWEETs）诱导表达水平在 ShB 易感品种中高于 ShB 抗性品种。接种 R. solani 后发现，大多数甜突变体对 ShB 的敏感性低于野生型。此外，糖转运体（STPs）基因的表达对 R. solani 感染也很敏感。STPs定位于质膜，在酵母中转运己糖。敲除 STP4 会增加水稻对 ShB 的敏感性。有趣的是，序列分析发现了两个单糖转运体基因（以下称为 RsMST）。RsMSTs 在酵母中转运一种有毒的葡萄糖类似物--2-脱氧葡萄糖，这表明它们具有葡萄糖转运体的作用。喷雾诱导的 RsMST1 或 RsMST2 基因沉默能显著抑制它们的表达水平，并降低 R. solani 的毒力。这些数据表明，R. solani 可能诱导 SWEETs 从细胞质向细胞凋亡体外排糖，而 STP 和 RsMSTs 则在细胞凋亡体竞争糖分，以达到防御宿主和提高病原体毒力的目的。这项研究为水稻抗 ShB 育种提供了重要启示。

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引用次数: 0

The impacts of film mulching and ridging on N2O emissions, relevant functional genes, and microbial communities in rain-fed potato fields 覆膜和打埂对雨水灌溉马铃薯田中一氧化二氮排放、相关功能基因和微生物群落的影响

Climate Smart Agriculture

Pub Date : 2024-07-11 DOI: 10.1016/j.csag.2024.100010

Liwei Wang , Jingjie Miao , Yubo Meng , Naijia Wang , Kai Zhang , Kangjun Guo , Yue Zhang , Jun Zhang , Chen Feng , Rajesh Kumar Soothar , Jiaxin Zhang , Xining Gao , Cheng Wang

Rain-fed potato (Solanum tuberosum) fields in drylands significantly contribute to nitrous oxide (N₂O) emissions, making them an important focus of agricultural greenhouse gas research. Film mulching and ridging are key agricultural methods in potato cultivation. Investigating the impact of these methods on N₂O emissions, nitrifying/denitrifying functional genes, and microbial communities can provide a theoretical basis for soil emission reduction and more sustainable dryland agriculture. We examine the effects of flat tillage with mulching, ridge tillage with mulching, flat tillage without mulching, and ridge tillage without mulching, on potato fields under natural rainfall conditions in Wuchuan County, China. N₂O emission fluxes were monitored using a static (dark) chamber and gas chromatography. Real-time quantitative PCR (q-PCR) was used to quantify abundances of nitrifying and denitrifying bacteria related to N₂O emissions at various potato-growth stages. Illumina high-throughput sequencing was used to investigate microbial community structure by targeting 16S rRNA genes; related soil elements (soil temperatures and moisture) are analyzed. Mulching and ridging indirectly influence N₂O emissions, nitrifying/denitrifying functional gene copy numbers, and microbial community structure by altering soil temperature and moisture. Cumulative N₂O emissions and emission intensity were both consistently higher in ridge tillage with mulching during the potato-growing period. Ammonia-oxidizing archaea are the main microorganisms that control N₂O emissions, with nitrification-coupled denitrification also being an important mechanism contributing to high N₂O emissions during soil dry–wet cycles. Increased soil temperature and moisture elevated N₂O emissions and functional gene copy numbers. The combination of mulching and ridging effectively uses the characteristics of both practices, making Nitrospira the dominant genus, and significantly increases N₂O emissions.

旱地的雨水灌溉马铃薯（Solanum tuberosum）田极大地增加了一氧化二氮（N2O）的排放量，使其成为农业温室气体研究的一个重要焦点。覆膜和打埂是马铃薯种植的主要农业方法。研究这些方法对一氧化二氮排放、硝化/反硝化功能基因和微生物群落的影响，可为土壤减排和更可持续的旱地农业提供理论依据。我们研究了在中国武川县自然降雨条件下，平耕加地膜覆盖、脊耕加地膜覆盖、平耕不加地膜覆盖和脊耕不加地膜覆盖对马铃薯田的影响。采用静态（暗）室和气相色谱仪监测 N2O 排放通量。实时定量 PCR（q-PCR）用于定量分析马铃薯不同生长阶段与 N2O 排放相关的硝化细菌和反硝化细菌的丰度。利用 Illumina 高通量测序技术，以 16S rRNA 基因为目标研究微生物群落结构；分析相关土壤元素（土壤温度和湿度）。地膜覆盖和田埂通过改变土壤温度和湿度间接影响了 N2O 排放、硝化/反硝化功能基因拷贝数和微生物群落结构。在马铃薯生长期间，覆土耕作和起垄耕作的累积 N2O 排放量和排放强度都持续较高。氨氧化古细菌是控制 N2O 排放的主要微生物，硝化耦合反硝化也是导致土壤干湿循环期间 N2O 高排放的重要机制。土壤温度和湿度的增加提高了 N2O 排放量和功能基因拷贝数。地膜覆盖与田埂覆盖相结合，有效利用了这两种方法的特点，使硝化细菌成为优势菌属，并显著增加了 N2O 排放量。

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引用次数: 0