European Journal of Agronomy最新文献

{"title":"Enhancement of soil humic acid hydrophobicity by 5 consecutive years of full-amount straw shallow-mixed field return","authors":"","doi":"10.1016/j.eja.2024.127378","DOIUrl":"10.1016/j.eja.2024.127378","url":null,"abstract":"<div><div>Crop yield is directly influenced by the storage and stabilisation of soil organic carbon (SOC), which is determined by the hydrophobicity of soil humic acid (HA). Changes in soil HA hydrophobicity, humic substances, SOC and crop yield were compared after the application of different amounts of straw returns in the field, and the contribution of straw application in enhancing HA hydrophobicity was examined. The treatments included no straw application and soil stirring, no straw application with soil stirring, application of half-amount straw shallow-mixed field return, application of full-amount straw shallow-mixed field return and application of double-amount straw shallow-mixed field return. Using elemental analysis, infrared spectroscopy and fluorescence spectroscopy, the structural hydrophobicity of soil HA was exhaustively characterised. The results showed that the hydrogen to carbon ratio of HA increased by 11.46 %, the ratio of hydrophobic to hydrophilic intensity increased by 21.02 %, and the ratio of peak B to peak A fluorescence intensity decreased by 32.21 % after 5 years of full amount straw shallow-mixing field return compared to no straw application and soil stirring. The observed results indicate that the augmentation in hydrophobicity stimulates the formation of HA, enhances soil humification, elevates SOC content by 9.78 % and potentially contributes to the ultimate crop yield increase by 22.98 %. Compared with stirring the soil, the contribution rate of applying full amount of straw to increase HA hydrophobicity was 49.57–62.05 %, and the contribution rate to increase SOC and yield were 54.59 % and 76.37 %, respectively. While stirring the soil contributed to increasing hydrophobicity, straw application persisted as the primary factor in enhancing hydrophobicity. The findings of this study have significant implications for understanding the mechanism by which straw improves HA hydrophobicity, thereby facilitating carbon sequestration and increasing crop yield.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Arbuscular mycorrhizal fungus activates wheat physiology for higher reproductive allocation under drought stress in primitive and modern wheat","authors":"","doi":"10.1016/j.eja.2024.127376","DOIUrl":"10.1016/j.eja.2024.127376","url":null,"abstract":"<div><div>Arbuscular mycorrhizal fungus (AMF) can mediate physiological adaptation of higher plants to drought stress, including wheat. Yet, it is unclear how AMF affects reproductive output via mediating crop physiological vitality at the evolutionary scale. To clarify this issue, a growth environment-controlled experiment was conducted using four primitive wheat genotypes and four modern ones with or without AMF (<em>Funneliformis mosseae</em>) inoculation. Two water regimes (80 % and 40 % field water capacity, FWC80 (well-watered) and FWC40 (drought stress)) were included. The data indicated that AMF inoculation significantly improved leaf area, photosynthetic rate, stomatal conductance and water use efficiency under drought stress, compared to the non-AMF group (CK). Regardless of soil moisture, the relationship between reproductive biomass vs. vegetative biomass (R-V), and between leaf biomass vs. shoot biomass, all fell into a typical allometric pattern (α&gt;1, <em>P</em>&lt;0.001) in primitive wheat. In contrast, in modern wheat, the R-V relationship tended to an isometric pattern (α≈1, <em>P</em>&lt;0.001), showing lower α values in all treatments relative to primitive ones. Furthermore, AMF inoculation significantly promoted the maintenance rate of yield and biomass under drought stress, suggesting greater drought tolerance as induced by AMF in modern wheat compared to primitive ones. These findings illuminated a key evolutionary strategy to enhance reproductive allocation via activating physiological activities under drought stress from primitive to modern wheat.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Greenhouse gas emissions and mitigation potential of crop production in Northeast China","authors":"","doi":"10.1016/j.eja.2024.127371","DOIUrl":"10.1016/j.eja.2024.127371","url":null,"abstract":"<div><div>Agricultural management practices that reduce greenhouse gas (GHG) emissions have been identified as effective mitigation strategies. However, research on carbon emissions from major crops in Northeast China focuses on national and provincial data, overlooking city-scale variability and uncertainties, which prevents fine-scale assessment of crop emissions reduction potential. To address this, a life cycle assessment (LCA) combined with the Monte Carlo method was conducted to estimate the carbon footprint of rice, maize, and soybean production for different cities in Northeast China from 1991 to 2020. The results showed that the top one-third of cities with the highest total carbon emissions (TCE) account for approximately 40 % of the region's TCE. Nitrogen losses and production processes related to nitrogen fertilizer application were identified as the primary contributors to TCE from crop production, accounting for 29.6–62.5 % of the total, with a relative importance of 58.5–78.2 %. Scenario analysis indicated that optimizing nitrogen fertilizer management and reducing active nitrogen losses are the most effective strategies for reducing TCE from major crop production, offering a reduction potential of 34.5–60.6 %. Recommended strategies include phased application of nitrogen fertilizer, the addition of nitrification inhibitors, or using slow-release nitrogen fertilizers, combined with appropriate increases in crop planting density, straw return decomposition technologies and water-saving irrigation methods to reduce GHG emissions. These strategies aim to achieve low-carbon sustainable grain production and provide a foundation for exploring the emissions reduction potential of agricultural inputs and optimizing regional crop layouts, offering new insights for developing more effective GHG reduction strategies.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced seed yield of full-season soybean when rotated with cereals and cover crops as compared to monoculture in a long-term experiment","authors":"","doi":"10.1016/j.eja.2024.127382","DOIUrl":"10.1016/j.eja.2024.127382","url":null,"abstract":"<div><div>Soybeans are of great importance to the global economy, but the cultivation as monoculture has shown several negative environmental implications in the long-term. Long-term studies demonstrate the cumulative effects of rotations on soil variables, but few studies have considered changes during consecutive years in a time series of soybean as a monoculture. The inclusion of cereals and cover crops in rotation with soybean increases the intensification sequence index (ISI, time with crops actively growing during the year) and increases in soybean yield are expected. In line with this, some studies suggest that only including a winter cover crop will increase ISI and raise production. However, these comparisons have not been made in the long term. The objectives of this work were to: i) compare the evolution of full-season soybean yield and production when sowed as monoculture and in cropping sequences that include cereal crops and cover crops, and ii) quantify a yield gap in full-season soybean due to monoculture by evaluating the long-term residual effect of crop sequences with different land occupation. Soybean yield time series in a 14-years period in rotation or as monoculture were studied in a long-term field experiment under no-tillage established in 2006 in the Northern Pampas region of Argentina. Rotations consisted in sequences that included soybean (S), maize (M) and wheat (W), and also incorporated wheat as a winter cover crop (CC): S-S, CC/S-CC/S, S-W/S-M, CC/S-W/S-M, M-W/S, and CC/M-W/S, with ISI values of 0.39, 0.69, 0.55, 0.64, 0.65 and 0.80, respectively. In 2021/22 season, full-season soybean was planted in all plots as a \"test\" crop, to evaluate the long-term residual effect of sequences with different intensification indexes. Seed yield averaged 3249 kg ha⁻¹ among years. During the 14 years under study, seed yield in S-W/S-M surpassed S-S by 28 % in 6 out of 14 years. The differences between S-S with respect to this sequence were observed consistently from the ninth crop season (i.e. since 2017/18). The inclusion of a cover crop within a soybean monoculture (i.e. CC/S-CC/S) showed similar seed yields as in S-S in 11 out of 14 years. The analysis of the test crop showed yield-gaps when soybeans were grown as monoculture (seed yield in rotations minus seed yield in S-S) of 9, 20, 27, 21 and 31 % for CC/S-CC/S, S-W/S-M, CC/S-W/S-M, M-W/S and CC/M-W/S, respectively. In summary, soybean in rotation with cereals showed an average increase of ca. 346 kg ha⁻¹ and including a cover crop within a soybean monoculture did not increase seed yield at the levels observed when rotated with cereals. Finally, when estimating seed yield-gaps in soybean, it is important to set in which rotation soybean is placed, since a higher maximum yield is expected to happen when soybean follows a more intensified rotation.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Achieving wheat seedling freezing injury assessment during the seedling stage using Unmanned Ground Vehicle (UGV) and hyperspectral imaging technology","authors":"","doi":"10.1016/j.eja.2024.127375","DOIUrl":"10.1016/j.eja.2024.127375","url":null,"abstract":"<div><div>Freezing injury may cause irreversible damage to wheat (<em><strong>Triticum aestivum L</strong></em>) tissues and can significantly reduce yield and quality. Therefore, quick and non-destructively estimating the degree of frost damage for formulating anti-freezing protection strategies and preventing frost damage is very crucial. In this study, we obtained hyperspectral images of wheat leaves for accurate identification of frost damage. A remote-controlled Unmanned Ground Vehicle (UGV) equipped with an imaging spectral camera was used to capture the hyperspectral images of frost-damaged wheat leaves. We compared the efficiency of two methods (the one without removal of weeds, and the other is to remove the corresponding area of weeds from the hyperspectral image by Deeplab V3+) for estimation of wheat freezing damage degree by using four different algorithms; Support Vector Machine Classification (SVM), Mahalanobis Distance Classification (MaD), Minimum Distance Classification (MiD), and Maximum Likelihood Classification (ML). We found that, Deeplab V3+ can efficiently identify the weeds from hyperspectral images, as the overall accuracy (OA) values of different algorithms were high in images with weeds removal as compared to the values in weeds containing images. Further, applying ML model after weeds removal have high OA (93.26 %) as compared to the other models. Thus, using Deeplab V3+ and ML can be a potential approach to identify the freezing injury in wheat for sustainable agricultural productivity.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging machine learning to discriminate wheat scab infection levels through hyperspectral reflectance and feature selection methods","authors":"","doi":"10.1016/j.eja.2024.127372","DOIUrl":"10.1016/j.eja.2024.127372","url":null,"abstract":"<div><div>Real-time or pre-symptomatic wheat scab (WS) detection is inevitable for precision agriculture to secure yield and quality at the critical grain formation stage. For this, feature selection (FS) techniques and machine learning (ML) have demonstrated their capabilities. However, for the same type and size of dataset, all FS and ML techniques behave differently due to their diverse primary constituents. This study attempts to leverage ML for WS classification and prediction employing different FS techniques on hyperspectral data of wheat spikes. The spectral features were selected and assessed to regress and classify disease occurrence. Relief-F-neural net (NN) manifested the best results with classification accuracy (CA) of 67 % and 89 % at the pre-symptomatic scale and 3 days after inoculation (DAI), respectively. Followed by continuous wavelet transform (CWT)-NN with 63 % CA at the pre-symptomatic scale and CWT-Xgboost with 89 % CA at 3DAI. For prediction, random forest regression revealed best accuracy of R² = 0.94 and RMSE = 7.70, followed by partial least squares regression with R² = 0.90 and RMSE = 10.37. The results offer a precise quantitative benchmark for future investigations into the capacity of hyperspectral data and FS for the real-time quantification of plant diseases.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digestate in replacement of synthetic fertilisers: A comparative 3–year field study of the crop performance and soil residual nitrates in West-Flanders","authors":"","doi":"10.1016/j.eja.2024.127380","DOIUrl":"10.1016/j.eja.2024.127380","url":null,"abstract":"<div><div>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 &gt; 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 &gt; 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).</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Capsular attention Conv-LSTM network (CACN): A deep learning structure for crop yield estimation based on multispectral imagery","authors":"","doi":"10.1016/j.eja.2024.127369","DOIUrl":"10.1016/j.eja.2024.127369","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142359002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Atmospheric CO2 fertilization effect on cereal yields in Morocco using the CARAIB dynamic vegetation model.","authors":"","doi":"10.1016/j.eja.2024.127374","DOIUrl":"10.1016/j.eja.2024.127374","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142326871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Grazing and precipitation addition interactions alleviate dominant species overgrowth and promote community productivity and biodiversity in a typical steppe","authors":"","doi":"10.1016/j.eja.2024.127370","DOIUrl":"10.1016/j.eja.2024.127370","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":51045,"journal":{"name":"European Journal of Agronomy","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}