European Journal of Agronomy最新文献_第10页

Digestate in replacement of synthetic fertilisers: A comparative 3–year field study of the crop performance and soil residual nitrates in West-Flanders 沼渣替代合成肥料：对西佛兰德地区作物表现和土壤残留硝酸盐进行为期 3 年的田间比较研究

IF 4.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2024-10-01 DOI: 10.1016/j.eja.2024.127380

Gregory Reuland , Tomas Van de Sande , Harmen Dekker , Ivona Sigurnjak , Erik Meers

Nitrogen (N) is an essential macronutrient for plant growth. As a widespread source of plant-available N, ammonia synthesis via the Haber-Bosch process has proven an extremely valuable commodity in farming systems since the middle of the twentieth century. However, its heavy reliance on ever-shrinking fossil fuel reserves and its sizeable carbon footprint have fostered the exploration of alternative, more sustainable, fertilising prospects. Through the recycling and reuse of nutrient byproducts, biobased fertilisers (BBF) can help reduce the European Union’s dependency on imported synthetic fertilisers. In this study, we examined digestate, the liquid fraction of digestate, pig slurry and pig urine as potential substitutes for synthetic fertilisers. In a full-scale field approach using a different crop each year (maize, spinach, potatoes), the agronomic performance of the treatments (defined as the crop N uptake and the crop yield) and the environmental performance (taken as the residual soil nitrates after harvest) of the BBF treatments were compared with those of a synthetic fertiliser benchmark (calcium ammonium nitrate) at three N regimes. As regards short-term fertilising capability, results showed that yields obtained from BBFs were not statistically different (p > 0.05) than those obtained with synthetic fertilisers. Likewise, for soil residual nitrates (0–90 cm), measured in October–November of each year, no difference (p > 0.05) was detected between the BBFs and the synthetic fertiliser reference treatments. However, the non-superiority test showed that some BBFs tended to perform better in terms of residual nitrates than the synthetic regimes. Generally, results pointed to a fast N release ability of the BBFs, indicated by the presence of nitrates at different soil depths. Hence, as with the mineral fertiliser, BBFs were prone to leaching which calls for adequate N management strategies. The N content of some BBFs were shown to vary over time, hence adequate and timely nutrient characterisations must be carried out prior to field application to ensure a more accurate N accountancy and reduce risks of over-fertilisation (or under-fertilisation).

氮（N）是植物生长必不可少的主要营养元素。自二十世纪中叶以来，通过哈伯-博施工艺合成的氨作为植物可用氮的广泛来源，已被证明是农业系统中极为宝贵的商品。然而，对日益减少的化石燃料储备的严重依赖及其巨大的碳足迹促进了对替代性、更可持续的肥料前景的探索。通过回收和再利用养分副产品，生物基肥料（BBF）有助于减少欧盟对进口合成肥料的依赖。在这项研究中，我们考察了沼渣、沼液、猪浆和猪尿作为合成肥料潜在替代品的情况。在每年使用一种不同作物（玉米、菠菜、马铃薯）的大规模田间试验中，我们比较了 BBF 处理与合成肥料基准（硝酸铵钙）在三种氮肥制度下的农艺表现（作物氮吸收量和作物产量）和环境表现（收获后土壤硝酸盐残留量）。在短期施肥能力方面，结果显示 BBF 的产量与使用合成肥料的产量相比没有统计学差异（p > 0.05）。同样，在每年 10 月至 11 月测量的土壤残留硝酸盐（0-90 厘米）方面，BBF 和合成肥料参考处理之间也未发现差异（p > 0.05）。不过，非优劣检验表明，某些 BBF 在残留硝酸盐方面的表现往往优于合成肥料。一般来说，结果表明 BBFs 具有快速释放氮的能力，这一点从不同土壤深度的硝酸盐存在情况可以看出。因此，与矿物肥料一样，BBFs 也很容易被沥滤，这就需要采取适当的氮管理策略。一些 BBFs 的氮含量随时间而变化，因此在田间施肥前必须进行充分、及时的养分鉴定，以确保更准确的氮核算，降低过度施肥（或施肥不足）的风险。

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引用次数: 0

Capsular attention Conv-LSTM network (CACN): A deep learning structure for crop yield estimation based on multispectral imagery 囊状注意力 Conv-LSTM 网络 (CACN)：基于多光谱图像的作物产量估算深度学习结构

IF 4.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2024-09-28 DOI: 10.1016/j.eja.2024.127369

Seyed Mahdi Mirhoseini Nejad , Dariush Abbasi-Moghadam , Alireza Sharifi , Aqil Tariq

Precise prediction of agricultural production output is crucial for farmers, policymakers, and the Farming-related industry. This article introduces a novel methodology to crop yield forecasting using a capsular neural network equipped with Conv-LSTM and attention mechanism. Our model combines the strengths of 3DCNN, and Conv-LSTM, which can capture the temporal dependencies and 3D features of crop yield data, and attention mechanism, which Can prioritize the most significant characteristics for making predictions. We evaluated CACN on a sizable collection of data of soybean crop yield in the United States from 2003 to 2019 and evaluated against various cutting-edge deep learning models. The outcomes indicate that our suggested approach surpasses other models in performance in terms of RMSE, correlation coefficient, and prediction error map. Specifically, our model achieved approximately 14 % improvement in terms of RMSE, compared to the state-of-the-art model Deep-Yield. Our model also demonstrated the ability to extract more meaningful features and capture the complex relationships between crop yield data and meteorological variables. Overall, our proposed method shows great potential for accurate and efficient crop yield forecasting and can be applied to other crops and regions.

农业产量的精确预测对于农民、政策制定者和农业相关产业来说至关重要。本文介绍了一种利用配备 Conv-LSTM 和注意力机制的囊状神经网络进行作物产量预测的新方法。我们的模型结合了 3DCNN 和 Conv-LSTM 的优势，前者可以捕捉作物产量数据的时间依赖性和三维特征，后者可以优先考虑最重要的特征进行预测。我们对 2003 年至 2019 年美国大豆作物产量的大量数据收集进行了 CACN 评估，并与各种前沿深度学习模型进行了对比。结果表明，我们建议的方法在均方根误差、相关系数和预测误差图方面的性能都超过了其他模型。具体来说，与最先进的 Deep-Yield 模型相比，我们的模型在均方根误差方面提高了约 14%。我们的模型还展示了提取更有意义的特征和捕捉作物产量数据与气象变量之间复杂关系的能力。总之，我们提出的方法在准确、高效的作物产量预测方面显示出巨大潜力，并可应用于其他作物和地区。

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引用次数: 0

Atmospheric CO2 fertilization effect on cereal yields in Morocco using the CARAIB dynamic vegetation model. 利用 CARAIB 动态植被模型分析大气二氧化碳施肥对摩洛哥谷物产量的影响。

IF 4.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2024-09-27 DOI: 10.1016/j.eja.2024.127374

Iliass Loudiyi , Ingrid Jacquemin , Mouanis Lahlou , Riad Balaghi , Bernard Tychon , Louis François

Climate change and rising atmospheric CO₂ levels are critical factors influencing agricultural productivity, particularly in Morocco, where cereal crops are essential for food security. The primary objective of this study is to evaluate the combined effects of atmospheric CO₂ variations and climatic changes on cereal yields up to 2099 using the CARAIB dynamic vegetation model. This evaluation is driven by four future scenarios based on the Euro-CORDEX initiative's regional climate models under the Representative Concentration Pathway 8.5. As part of this evaluation, the study also validates the CARAIB model for Morocco’s major cereal crops: soft wheat, durum wheat, and barley, in order to ensure the model's accuracy in simulating crop responses under projected environmental conditions. The CARAIB model effectively simulated historical cereal yield trajectories across major farming regions in Morocco from 2000 to 2016, demonstrating its robust predictive capability. Our future projections suggest that elevated CO₂ levels might initially sustain cereal yields at approximately 90 % of current levels until 2050. This trend indicates that the increase in atmospheric CO₂ may exert a moderating influence on the negative impacts of other environmental stressors on crop yields. However, despite this initial buffering effect, the overall yield trend from the present until 2099 indicates a decrease for most combinations of crop, zone, and climate model, even with the CO₂ fertilization effect, except in some cases, the model exhibits slight increases or stabilization in yields. Additionally, the CARAIB model predicts potential yield shocks of 10–35 % below current levels from the 2080 s onwards, primarily due to periodic droughts. This variation underscores the complexity of the interplay between CO₂ fertilization and climatic changes, emphasizing the urgent need for Morocco to develop adaptive agricultural strategies for long-term sustainability in the face of climatic challenges.

气候变化和大气中二氧化碳含量的上升是影响农业生产力的关键因素，特别是在摩洛哥，谷类作物对粮食安全至关重要。本研究的主要目的是利用 CARAIB 动态植被模型，评估大气二氧化碳变化和气候变化对 2099 年前谷物产量的综合影响。该评估由欧洲-CORDEX 计划的区域气候模型在代表性浓度途径 8.5 下的四种未来情景驱动。作为评估的一部分，该研究还验证了摩洛哥主要谷物作物：软质小麦、硬质小麦和大麦的 CARAIB 模型，以确保该模型在预测环境条件下模拟作物反应的准确性。CARAIB 模型有效模拟了 2000 年至 2016 年摩洛哥主要农业地区谷物的历史产量轨迹，证明了其强大的预测能力。我们对未来的预测表明，二氧化碳水平的升高最初可能会使谷物产量维持在目前水平的约 90%，直到 2050 年。这一趋势表明，大气中二氧化碳的增加可能会缓和其他环境压力因素对作物产量的负面影响。然而，尽管有这种初始缓冲作用，但从现在到 2099 年的总体产量趋势表明，即使有二氧化碳施肥效应，大多数作物、区域和气候模型组合的产量也会下降，只有在某些情况下，模型显示产量略有增加或趋于稳定。此外，CARAIB 模型预测，从 2080 年代起，主要由于周期性干旱，产量可能会比当前水平低 10-35%。这种变化凸显了二氧化碳施肥与气候变化之间相互作用的复杂性，强调摩洛哥迫切需要制定适应性农业战略，以应对气候挑战，实现长期可持续性。

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引用次数: 0

Grazing and precipitation addition interactions alleviate dominant species overgrowth and promote community productivity and biodiversity in a typical steppe 放牧和降水的相互作用缓解了典型草原上优势物种的过度生长，提高了群落生产力和生物多样性

IF 4.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2024-09-25 DOI: 10.1016/j.eja.2024.127370

Xiaojuan Huang , Meiyue He , Lan Li , Zhaoxia Guo , Fujiang Hou

Grazing and precipitation are pivotal factors influencing the productivity and biodiversity of grassland ecosystems, largely through their effects on the growth and reproduction of dominant species. Approximately 50 % of terrestrial ecosystems are concurrently affected by grazing and precipitation addition (PA), yet the interactive effects of these factors remain underexplored. To elucidate the combined impacts of grazing and PA on the growth of dominant species and their influence on community structure and function, we initiated a four-year combined grazing and PA experiment based on a long term of grazing experiment in a typical steppe. The synergistic interaction between PA and grazing enhanced canopy diameter (CD), tiller density (TD), and seedling density (SD) in dominant species, while decreasing reproductive branch density (RB). Conversely, an antagonistic interaction increased plant height (PH) and TD but reduced SD. These responses suggest that dominant species adapt to combined grazing and PA pressures by shifting growth strategies towards lateral growth and asexual reproduction. The growth characteristics of dominant species exhibited four response patterns to grazing and PA interactions: full saturation, sufficient saturation, equal saturation, and deficit saturation, each with three corresponding thresholds: adaptation, optimum, and saturation points. Grazing decreased the precipitation response thresholds for PH, CD, RB, and population density, while increasing the optimal points for TD and SD. These changes in the growth of the dominant species resulted in a 33 % reduction in the aboveground biomass (AGB) of the community and triggered a 18 % increase in the coupling index between AGB and species richness within the community. Our findings highlight the role of dominant species in facilitating community adaptation to increased precipitation and rotational grazing, offering critical insights for developing sustainable grazing strategies under climate change.

放牧和降水是影响草原生态系统生产力和生物多样性的关键因素，这主要是通过它们对优势物种的生长和繁殖的影响来实现的。约有 50% 的陆地生态系统同时受到放牧和降水增加（PA）的影响，但这些因素的交互作用仍未得到充分探索。为了阐明放牧和 PA 对优势物种生长的综合影响及其对群落结构和功能的影响，我们在典型草原长期放牧实验的基础上，启动了一项为期四年的放牧和 PA 综合实验。PA和放牧之间的协同作用增强了优势物种的冠层直径（CD）、分蘖密度（TD）和幼苗密度（SD），同时降低了生殖枝密度（RB）。相反，拮抗作用增加了植株高度（PH）和分蘖密度（TD），但降低了分蘖密度（SD）。这些反应表明，优势物种通过将生长策略转向侧向生长和无性繁殖来适应放牧和PA的双重压力。优势物种的生长特征表现出四种对放牧和PA相互作用的响应模式：完全饱和、充分饱和、同等饱和和不足饱和，每种模式都有三个相应的阈值：适应点、最佳点和饱和点。放牧降低了 PH、CD、RB 和种群密度的降水响应阈值，同时提高了 TD 和 SD 的最佳点。优势物种生长的这些变化导致群落的地上生物量（AGB）减少了33%，并使群落内AGB与物种丰富度之间的耦合指数增加了18%。我们的研究结果突显了优势物种在促进群落适应降水增加和轮牧方面的作用，为在气候变化下制定可持续的放牧策略提供了重要的启示。

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引用次数: 0

Efficient crop segmentation net and novel weed detection method 高效作物分割网和新型杂草检测方法

IF 4.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2024-09-24 DOI: 10.1016/j.eja.2024.127367

Xiaotong Kong , Teng Liu , Xin Chen , Xiaojun Jin , Aimin Li , Jialin Yu

Computer vision-based precision weed control offers a promising avenue for reducing herbicide input and the associated costs of weed management. However, the substantial investments in time and labor required for the collection and annotation of weed image data pose challenges to develop effective deep learning models. The limitation also stems from the challenges in achieving accurate and reliable detection of weeds across varying growth stages, densities, and ecotypes in field scenarios. To address these issues, this research investigated a novel methodology employing a segmentation algorithm to accurately mark the contour information of crops in the image and detect weeds through image processing technology. Furthermore, a novel segmentation network was developed based on the YOLO architecture to address the substantial computing resource demands associated with segmentation algorithms. This was achieved through the design of a new backbone, incorporation of an attention mechanism, and modification of the feature fusion technique. The novel network achieved higher segmentation accuracy with less computational demands. The effectiveness of three different attention modules on segmentation tasks was additionally investigated. Experimental results showed that the insertion of Criss-cross Attention significantly improved the model's performance and was subsequently incorporated into our enhanced methodology. The enhanced model achieved a Mean Intersection over Union (mIoU50) of 90.9 %, with precision increasing by 5.9 % and Giga FLoating-point Operations Per Second (GFLOPs) reduced by 15.56 %, demonstrating enhanced suitability for deployment in resource-constrained computing environments. The findings presented in this study hold substantial theoretical and practical implications for precise weed management.

基于计算机视觉的精准杂草控制为减少除草剂投入和杂草管理的相关成本提供了一条前景广阔的途径。然而，收集和标注杂草图像数据需要投入大量的时间和人力，这给开发有效的深度学习模型带来了挑战。此外，在田间不同生长阶段、不同密度和不同生态类型的杂草中实现准确可靠的检测也是一大挑战。为解决这些问题，本研究调查了一种新型方法，该方法采用分割算法准确标记图像中作物的轮廓信息，并通过图像处理技术检测杂草。此外，还开发了基于 YOLO 架构的新型分割网络，以解决与分割算法相关的大量计算资源需求。这是通过设计新的骨干网、加入关注机制和修改特征融合技术来实现的。新型网络以更低的计算需求实现了更高的分割精度。此外，还研究了三种不同注意力模块在分割任务中的有效性。实验结果表明，"十字交叉注意力 "的加入显著提高了模型的性能，并随后被纳入我们的增强型方法中。增强型模型的平均联合交叉率（mIoU50）达到了 90.9%，精确度提高了 5.9%，每秒千亿 FLoating-point 运算次数（GFLOPs）减少了 15.56%，表明该模型更适合部署在资源有限的计算环境中。本研究的发现对精确杂草管理具有重要的理论和实践意义。

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引用次数: 0

Enhancing soil moisture estimation in alfalfa root-zone using UAV-based multimodal remote sensing and deep learning 利用无人机多模态遥感和深度学习加强苜蓿根区土壤水分估算

IF 4.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2024-09-23 DOI: 10.1016/j.eja.2024.127366

Liubing Yin, Shicheng Yan, Meng Li, Weizhe Liu, Shu Zhang, Xinyu Xie, Xiaoxue Wang, Wenting Wang, Shenghua Chang, Fujiang Hou

Accurate estimation of soil moisture content (SMC) is essential for optimizing irrigation schedules and identifying drought-tolerant varieties. The integration of unmanned aerial vehicles (UAVs) with advanced sensors provides a novel method for monitoring SMC with high flexibility, resolution, and performance. This study utilized UAVs to capture RGB, multispectral, and thermal imagery of alfalfa (Medicago sativa L.) at the Linze Grassland Agricultural Experiment Station, Lanzhou University, and to evaluate the potential of fusing multimodal UAV data for SMC estimation in the root zone of densely and uniformly distributed leafy plants, using alfalfa as a case study, within a deep learning framework. Results showed that combining multimodal data—encompassing canopy spectral, structural, thermal, and textural information—significantly improved SMC estimation accuracy. Among the four regression models evaluated—partial least squares (PLSR), support vector machine (SVM), random forest (RF), and deep neural network (DNN)—the DNN model achieved the highest accuracy in overall multimodal data fusion, with a coefficient of determination (R²) of 0.72 and a root mean square error (RMSE) of 4.98%. It demonstrated good predictive performance for both full and deficit irrigation scenarios, with R² values of 0.74 and 0.75, respectively. The DNN model also provided reliable SMC estimates across the three alfalfa canopy types, with R² values of 0.72, 0.74, and 0.58, respectively. Moreover, it exhibited superior accuracy under both irrigation regimes and demonstrated strong spatial adaptability, characterized by low spatial dependence and autocorrelation. In conclusion, the DNN model based on UAV-derived multimodal data fusion offers a reliable and robust approach for SMC estimation, providing valuable insights for irrigation management at farmland-scale.

准确估算土壤含水量（SMC）对于优化灌溉计划和确定耐旱品种至关重要。无人飞行器（UAV）与先进传感器的集成为监测 SMC 提供了一种具有高灵活性、高分辨率和高性能的新方法。本研究利用无人机在兰州大学临泽草原农业试验站捕捉紫花苜蓿（Medicago sativa L.）的 RGB、多光谱和热图像，并以紫花苜蓿为例，在深度学习框架内评估融合多模态无人机数据用于密集和均匀分布的多叶植物根区 SMC 估计的潜力。结果表明，结合多模态数据--包括冠层光谱、结构、热和纹理信息--显著提高了SMC估计的准确性。在所评估的四种回归模型（部分最小二乘法（PLSR）、支持向量机（SVM）、随机森林（RF）和深度神经网络（DNN））中，DNN 模型在整体多模态数据融合中取得了最高的准确度，其决定系数（R2）为 0.72，均方根误差（RMSE）为 4.98%。该模型在全面灌溉和缺水灌溉情况下均表现出良好的预测性能，R2 值分别为 0.74 和 0.75。DNN 模型还为三种苜蓿冠层类型提供了可靠的 SMC 估计值，R2 值分别为 0.72、0.74 和 0.58。此外，该模型在两种灌溉制度下都表现出较高的准确性，并表现出较强的空间适应性，其特点是空间依赖性和自相关性较低。总之，基于无人机多模态数据融合的 DNN 模型为 SMC 估算提供了一种可靠、稳健的方法，为农田灌溉管理提供了有价值的见解。

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引用次数: 0

Optimal magnesium management for better seed yield and quality of rapeseed based on native soil magnesium supply 基于原生土壤镁供应量，优化镁管理，提高油菜籽产量和质量

IF 4.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2024-09-20 DOI: 10.1016/j.eja.2024.127364

Guotao Geng , Xiaolei Ye , Tao Ren , Yangyang Zhang , Xiaokun Li , Rihuan Cong , Ismail Cakmak , Zhifeng Lu , Jianwei Lu

Soil magnesium (Mg) deficiency is a common problem in many crop plants including rapeseed (Brassica napus L.), resulting in significant impairments in seed yield and quality. However, precise application approaches and technologies used for Mg fertilization are still not well established for rapeseed plants grown under field conditions. A better understanding and characterization of the relationship between soil Mg supply and yield response of plants is of great importance for appropriate Mg fertilization management. This study used large-scale experiments to (i) establish a criterion for soil extractable Mg (ex-Mg) in rapeseed-cultivated soils, (ii) evaluate the role of Mg in improving rapeseed yield and quality under contrasting soil ex-Mg status and (iii) optimize Mg fertilization programs based on native soil Mg supply. A large-scale field study program comprising of 56 rapeseed field trials, each with five Mg application levels (0, 9, 18, 27, 36 kg Mg ha⁻¹), was conducted in 13 provinces of China to investigate the effects of soil Mg status on rapeseed yield and quality. A soil ex-Mg criteria system was established to optimize Mg fertilization of rapeseed plants based on yield responses and soil ex-Mg levels. The critical soil ex-Mg for rapeseed was found to be 200 mg kg⁻¹, and seed yield was increased by more than 5 % after adding Mg fertilizers in over 85 % of the experimental trials. In case of severe Mg deficiency (ex-Mg < 70 mg kg⁻¹), Mg fertilization improved seed yield by about 40 % and this increase was closely related to the number of pods per plant and seeds per pod. When soil ex-Mg concentration was above 70 mg kg⁻¹, the increments of seed yield by Mg fertilization were diminished. Magnesium fertilization also improved seed oil and oleic acid concentrations of plants grown on severe Mg-depleted soils. The average recommended Mg rate was 23.2 kg Mg ha⁻¹ under severe soil Mg deficiency conditions, which then showed decreases as the soil ex-Mg increases. Besides soil ex-Mg, soil pH, the soil Ca²⁺ and K⁺ concentrations as well as the yield capacity of plants were further factors affecting the agronomic effectiveness of Mg fertilization on crop yield and Mg application rates. For example, seed yield significantly increased in response to Mg fertilization under high soil K/Mg (>2) and Ca/Mg (>20) ratios. The results collected from 56 field experiments indicate that soil ex-Mg level is a critical factor in determining Mg application rates in rapeseed-cultivated soils, and represents an important factor involved in varied response of rapeseed plants in respect to seed yield and quality. The study highlights the significance of soil ex-Mg levels and optimization of Mg recommendations in achieving improvements in seed yield and quality of rapeseed plants grown under diverse native ex-Mg levels.

土壤镁（Mg）缺乏是包括油菜籽（Brassica napus L.）在内的许多作物植物的常见问题，会严重影响种子的产量和质量。然而，对于在田间条件下生长的油菜植物来说，镁肥的精确施用方法和技术还没有得到很好的确立。更好地理解和描述土壤镁供应与植物产量反应之间的关系，对适当的镁肥管理具有重要意义。本研究通过大规模试验：（i）确定油菜种植土壤中可提取镁（ex-Mg）的标准；（ii）评估在不同土壤ex-Mg状态下，镁在提高油菜产量和质量方面的作用；（iii）根据原生土壤镁供应量优化镁施肥方案。为了研究土壤镁含量对油菜籽产量和品质的影响，研究人员在中国 13 个省开展了大规模的田间试验，包括 56 个油菜籽田间试验，每个试验有五个镁施用水平（0、9、18、27、36 千克镁公顷-1）。根据产量反应和土壤镁含量，建立了土壤镁含量标准体系，以优化油菜的镁施肥。结果发现，油菜籽的临界土壤外镁含量为 200 毫克/千克，85% 以上的试验中，施用镁肥后籽粒产量提高了 5%以上。在严重缺镁的情况下（土壤中的镁含量为 70 毫克/千克），施用镁肥可使种子产量提高约 40%，而这一增产幅度与每株植物的荚果数和每个荚果的种子数密切相关。当土壤中的前镁浓度超过 70 毫克/千克时，镁肥对种子产量的提高作用就会减弱。镁肥还能提高严重缺镁土壤上生长的植物的籽油和油酸浓度。在土壤严重缺镁的条件下，平均推荐镁用量为 23.2 千克镁/公顷，随着土壤外镁的增加，推荐镁用量随之减少。除了土壤外镁，土壤 pH 值、土壤 Ca2+ 和 K+ 浓度以及植物的产量能力也是影响镁肥对作物产量和镁施用量的农艺效果的因素。例如，在土壤钾/镁（&t;2）和钙/镁（&t;20）比值较高的条件下，施用镁肥的种子产量会明显增加。56 项田间试验的结果表明，土壤中的外镁水平是决定油菜种植土壤中镁施用量的关键因素，也是影响油菜籽产量和质量的重要因素。这项研究强调了土壤镁含量和优化镁建议对提高不同土壤镁含量下油菜籽产量和质量的重要性。

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引用次数: 0

Effect of climate, crop, and management on soil phosphatase activity in croplands: A global investigation and relationships with crop yield 气候、作物和管理对农田土壤磷酸酶活性的影响：全球调查及与作物产量的关系

IF 4.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2024-09-20 DOI: 10.1016/j.eja.2024.127358

Patrícia Campdelacreu Rocabruna , Xavier Domene , Catherine Preece , Marcos Fernández-Martínez , Joan Maspons , Josep Peñuelas

Agricultural and livestock production cover more than a third of the Earth's land surface and are crucial to food supply. Soil extracellular enzymes play an important role in the transformation of elements and compounds in soil, particularly acid (ACP) and alkaline (ALP) phosphatases (both, APases). These enzymes have a vital role in releasing phosphorus (P) from organic matter. However, the effect of climate variables and agro-ecosystem management on APase activity in croplands remains unclear, as does its eventual relationship with agricultural productivity. Therefore, we compiled a global database of APase activity in croplands (between 1977 and 2022) and we analysed 5876 observations across 474 papers to study climate variables, crop family, and management effects on ACP and ALP activity, and their relationship with yield. ACP activity is reduced by higher temperatures (p<0.001) and lower rainfall (p=0.002). There was an interaction effect of temperature and precipitation on ALP activity (p=0.046), with the negative effect of temperature being stronger with high precipitation, and low precipitation showing low ALP activity levels at any temperature. The crop family greatly influenced APase activity (p<0.001). Management practices affected ACP and ALP activity differently; ACP activity was positively influenced by organic fertilization combined with, crop rotation or irrigation by an average of 15.6 % and 30.7 %, respectively. ALP activity was mainly positively influenced by the interaction of two different factors: organic or inorganic-organic fertilization and reduced or zero tillage. Further understanding of soil enzyme mechanisms would aid global food security and yield. As ACP activity doubles from 100.0 to 200.0 mg pNP kg⁻¹h⁻¹, the crop yield increases by more than two-fold, an outcome not demonstrated in croplands until now. These results could enhance yield potential through the promotion of APase activity, and the consideration of climate variables and agro-ecosystem management, which could ultimately improve cost-benefit ratios for sustainable crop growth.

农业和畜牧业生产占地球陆地面积的三分之一以上，对粮食供应至关重要。土壤细胞外酶在土壤中元素和化合物的转化过程中发挥着重要作用，特别是酸性（ACP）和碱性（ALP）磷酸酶（均为 APases）。这些酶在从有机物中释放磷（P）方面发挥着重要作用。然而，气候变量和农业生态系统管理对耕地中磷酸酶活性的影响及其与农业生产力的最终关系仍不清楚。因此，我们建立了一个全球耕地AP酶活性数据库（1977年至2022年），并分析了474篇论文中的5876个观测数据，以研究气候变量、作物种类和管理对ACP和ALP活性的影响，以及它们与产量的关系。气温升高（p<0.001）和降雨量减少（p=0.002）会降低 ACP 活性。温度和降水量对 ALP 活性有交互作用（p=0.046），温度的负作用在降水量大时更强，降水量小则在任何温度下都表现出低 ALP 活性水平。作物种类对 APase 活性有很大影响（p<0.001）。管理措施对 ACP 和 ALP 活性的影响各不相同；有机施肥、轮作或灌溉对 ACP 活性有积极影响，平均影响程度分别为 15.6% 和 30.7%。ALP 活性主要受到两个不同因素的交互影响：有机或无机-有机施肥以及减少耕作或零耕作。进一步了解土壤酶机制将有助于全球粮食安全和产量。当 ACP 活性从 100.0 mg pNP kg-1h-1 提高到 200.0 mg pNP kg-1h-1 时，作物产量增加了两倍多，这是迄今为止在农田中尚未证实的结果。这些结果可以通过促进蛋白水解酶活性、考虑气候变量和农业生态系统管理来提高产量潜力，最终提高可持续作物生长的成本效益比。

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引用次数: 0

Potential use of phosphorus saturation degree as combined indicator for crop yield and leaching risks at regional scale 将磷饱和度作为区域范围内作物产量和沥滤风险综合指标的潜力

IF 4.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2024-09-19 DOI: 10.1016/j.eja.2024.127347

Yu Gu , Gerard H. Ros , Qichao Zhu , Maarten van Doorn , Jianbo Shen , Zejiang Cai , Minggang Xu , Wim de Vries

To ensure the sustainable use of phosphorus (P) fertilizers it is necessary to develop P management strategies that maximize crop yield while minimizing P leaching. Current P management practices, based on single agronomic soil P tests such as Olsen P (P_OLSEN), do not consider the P sorption capacity allowing one to predict soil P dynamics in response to long-term P inputs and related impacts on crop yield, P uptake and P loss. The oxalate extraction method, measuring contents of P, aluminium (Al) and iron (Fe), has been identified as a high-potential agri-environmental P test as it measures the reversibly sorbed P pool. This test gives insights in the plant-available P pool, the P sorption capacity and the degree of P Saturation (PSD). In this study, we evaluated the performance of P_OLSEN and PSD in explaining crop yield and P leaching risks, using long-term field experiments from China (n = 1) and Europe (n = 11), and we applied these insights to an inventory dataset (grid-sampling based) of Qiyang county in China. The variations in crop yield and P leaching risk were better explained by PSD (R²=0.5–0.95 for crop yield and 0.84–0.95 for P leaching risk) than by P_OLSEN (R²=0.68–0.93 for crop yield and < 0.73 for P leaching risk). The PSD target level to achieve 90 % of the potential yield was higher than the critical level to avoid enhanced P leaching for the Chinese but not for the European experiments. When applied on regional scale, we showed that the use of P_OLSEN might underestimate P demand for crop production and overestimate the potential leaching risk. Considering the theoretical advantages of PSD as a combined agri-environmental soil P test, we discussed the implications of its use for regional P management and showed that the α value, which is used to estimate PSD from oxalate extractable Al and Fe, needs to be adjusted for regional pedogenic and related climate factors.

为确保磷（P）肥料的可持续使用，有必要制定磷管理策略，在最大限度地提高作物产量的同时，最大限度地减少磷沥滤。目前的磷管理方法以单一的农艺土壤磷测试（如奥尔森磷测试（POLSEN））为基础，没有考虑磷的吸附能力，因此无法预测长期磷投入对土壤磷的动态影响，以及对作物产量、磷吸收和磷流失的相关影响。草酸盐萃取法测量钾、铝（Al）和铁（Fe）的含量，被认为是一种极具潜力的农业环境钾测试方法，因为它测量的是可逆吸附的钾库。该测试可深入了解植物可利用的磷库、磷吸附能力和磷饱和度（PSD）。在本研究中，我们利用中国（n = 1）和欧洲（n = 11）的长期田间试验，评估了 POLSEN 和 PSD 在解释作物产量和钾浸出风险方面的性能，并将这些见解应用于中国祁阳县的库存数据集（基于网格采样）。与 POLSEN（R2=0.68-0.93（作物产量）和 0.73（P 浸出风险））相比，PSD（R2=0.5-0.95（作物产量）和 0.84-0.95（P 浸出风险））能更好地解释作物产量和 P 浸出风险的变化。在中国的实验中，实现 90% 潜在产量的 PSD 目标水平高于避免增加 P 浸出的临界水平，而在欧洲的实验中则不然。在区域范围内应用时，我们发现使用 POLSEN 可能会低估作物生产对磷的需求，并高估潜在的沥滤风险。考虑到 PSD 作为农业-环境土壤钾综合测试的理论优势，我们讨论了使用 PSD 进行区域钾管理的意义，并表明需要根据区域成土因素和相关气候因素对用于估算 PSD 的草酸盐可提取铝和铁的α 值进行调整。

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引用次数: 0

Scientometric analysis of cover crop management: Trends, networks, and future directions 覆盖作物管理的科学计量分析：趋势、网络和未来方向

IF 4.5 1区农林科学 Q1 AGRONOMY

European Journal of Agronomy

Pub Date : 2024-09-19 DOI: 10.1016/j.eja.2024.127355

Raúl San-Juan-Heras , José L. Gabriel , María M. Delgado , Sergio Alvarez , Sara Martinez

This research paper presents a comprehensive scientometric analysis of English articles from the Scopus database regarding the topic of cover crop management from 1956 to March 2024. Through the analysis of the annual production trend, total production, a co-occurrence network of keywords, co-authorship networks, and co-citation networks, the data was mapped and visualized using VOSviewer and Bibliometrix software. There was an exponential increase in publications from 1991 onwards. The predominant subject was Agricultural and Biological Sciences and the most relevant journals, authors, and documents were related to this topic. Additionally, the most productive country was the United States, but in terms of article production per surface area, other countries, such as Switzerland and The Netherlands, evidence the great weight of cover crop management in these countries. The identified research topics were related to the application of different crops as cover crops and the effects on different cultivars, also soil quality improvement, and fertilization and nutrient efficiency. An emerging research topic was found to be the usefulness of cover crops as effective tools for climate change adaptation and mitigation strategies in agriculture. Future research in the field of cover crop management could be directed towards climate-adaptive cover crop species and varieties, the use of technological innovations for cover crop monitoring, and management and analysis of the economic and social impacts of cover crop adoption.

本研究论文对 Scopus 数据库中 1956 年至 2024 年 3 月有关覆盖作物管理主题的英文文章进行了全面的科学计量分析。通过对年产量趋势、总产量、关键词共现网络、共同作者网络和共同引用网络的分析，使用 VOSviewer 和 Bibliometrix 软件对数据进行了映射和可视化。从 1991 年起，出版物呈指数增长。最主要的主题是农业和生物科学，最相关的期刊、作者和文献都与该主题有关。此外，产量最高的国家是美国，但从单位面积的文章产量来看，瑞士和荷兰等其他国家的覆盖作物管理占有很大比重。已确定的研究课题涉及不同作物作为覆盖作物的应用及其对不同栽培品种的影响，以及土壤质量的改善、施肥和养分效率。一个新出现的研究课题是覆盖作物作为农业适应和减缓气候变化战略的有效工具的实用性。今后在覆盖作物管理领域的研究方向可以是适应气候的覆盖作物物种和品种、利用技术创新进行覆盖作物监测，以及管理和分析采用覆盖作物的经济和社会影响。

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引用次数: 0