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学者姓名：侯毛毛
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为揭示不同暗管间距与生物有机肥施用下盐碱地N
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| GB/T 7714 | 章二子 , 陈竞楠 , 黄艳 et al. 不同暗管间距与生物有机肥施用对盐碱地N [J]. | 节水灌溉 , 2025 , 7 (02) : 15-20,27 . |
| MLA | 章二子 et al. "不同暗管间距与生物有机肥施用对盐碱地N" . | 节水灌溉 7 . 02 (2025) : 15-20,27 . |
| APA | 章二子 , 陈竞楠 , 黄艳 , 田颖 , 金秋 , 侯毛毛 . 不同暗管间距与生物有机肥施用对盐碱地N . | 节水灌溉 , 2025 , 7 (02) , 15-20,27 . |
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为揭示不同暗管间距与生物有机肥施用下盐碱地N
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N N
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| GB/T 7714 | 章二子 , 陈竞楠 , 黄艳 et al. 不同暗管间距与生物有机肥施用对盐碱地N 2 O排放的影响研究 [J]. | 节水灌溉 , 2025 , PageCount-页数: 7 (02) : 15-20,27 . |
| MLA | 章二子 et al. "不同暗管间距与生物有机肥施用对盐碱地N 2 O排放的影响研究" . | 节水灌溉 PageCount-页数: 7 . 02 (2025) : 15-20,27 . |
| APA | 章二子 , 陈竞楠 , 黄艳 , 田颖 , 金秋 , 侯毛毛 . 不同暗管间距与生物有机肥施用对盐碱地N 2 O排放的影响研究 . | 节水灌溉 , 2025 , PageCount-页数: 7 (02) , 15-20,27 . |
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Gray mold is one of the major diseases affecting tomato production. Its early symptoms are often inconspicuous, yet the disease spreads rapidly, leading to severe economic losses. Therefore, the development of efficient and non-destructive early detection technologies is of critical importance. At present, multispectral imaging-based detection methods are constrained by two major bottlenecks: limited sample size and single modality, which hinder precise recognition at the early stage of infection. To address these challenges, this study explores a detection approach integrating multispectral fluorescence and reflectance imaging, combined with machine learning algorithms, to enhance early recognition of tomato gray mold. Particular emphasis is placed on evaluating the effectiveness of multimodal information fusion in extracting early disease features, and on elucidating the quantitative relationships between disease progression and key physiological indicators such as chlorophyll content, water content, malondialdehyde levels, and antioxidant enzyme activities. Furthermore, an improved WGAN-GP (Wasserstein Generative Adversarial Network with Gradient Penalty) is employed to alleviate data scarcity under small-sample conditions. The results demonstrate that multimodal data fusion significantly improves model sensitivity to early-stage disease detection, while WGAN-GP-based data augmentation effectively enhances learning performance with limited samples. The Random Forest model achieved an early recognition precision of 97.21% on augmented datasets, and transfer learning models attained an overall precision of 97.56% in classifying different disease stages. This study provides an effective approach for the early prediction of tomato gray mold, with potential application value in optimizing disease management strategies and reducing environmental impact.
Keyword ：
disease detection disease detection gray mold gray mold machine learning machine learning multispectral fluorescence-reflectance technology multispectral fluorescence-reflectance technology tomato tomato
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| GB/T 7714 | Zhong, Xiaohao , Li, Huicheng , Cai, Yixin et al. Early Detection of Tomato Gray Mold Based on Multispectral Imaging and Machine Learning [J]. | HORTICULTURAE , 2025 , 11 (9) . |
| MLA | Zhong, Xiaohao et al. "Early Detection of Tomato Gray Mold Based on Multispectral Imaging and Machine Learning" . | HORTICULTURAE 11 . 9 (2025) . |
| APA | Zhong, Xiaohao , Li, Huicheng , Cai, Yixin , Deng, Ying , Xu, Haobin , Tian, Jun et al. Early Detection of Tomato Gray Mold Based on Multispectral Imaging and Machine Learning . | HORTICULTURAE , 2025 , 11 (9) . |
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Lettuce is a water-sensitive stem-used plant, and its rapid growth process causes significant disturbances to the soil. Few studies have focused on the gaseous carbon emissions from lettuce fields under different irrigation methods. Therefore, this study investigated the effect of different drip-irrigation lower limits and methods (drip and furrow irrigation) on greenhouse gas (CO2, CH4) emissions from lettuce fields. Thus, drip irrigation (DI) was implemented using three different lower limits of irrigation corresponding to 75%, 65%, and 55% of the field capacity, and named DR1, DR2, and DR3, respectively. Furrow irrigation (FI) was used as a control treatment. The CO2 and CH4 emission fluxes, soil temperature, and soil enzyme activities were detected. The results showed that the cumulative CO2 emission was highest under DR3 and relatively lower under DR1. For the FI treatment, the cumulative CO2 emission (382.7 g C m-2) was higher than that under DR1 but 20.2% lower than that under DR2. The cumulative CH4 emissions under FI (0.012 g C m-2) were the greatest in the whole lettuce growth period, while DR2 and DR3 treatments emitted lower amounts of CH4. The irrigation method considerably enhanced the activity of urease and catalase, meanwhile promoting CO2 emission. The low irrigation amount each time combined with high irrigation frequency reduced soil CO2 emission while increasing CH4 emission. From the perspective of the total reduction of gaseous carbon, DR1 is the optimal drip irrigation method among all the irrigation lower limits and methods.
Keyword ：
emission reduction emission reduction emissions emissions greenhouse gases greenhouse gases irrigation strategies irrigation strategies water-saving irrigation water-saving irrigation
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| GB/T 7714 | Wang, Jinwei , Hamoud, Yousef Alhaj , Zhu, Qinyuan et al. Soil Gaseous Carbon Emissions from Lettuce Fields as Influenced by Different Irrigation Lower Limits and Methods [J]. | AGRONOMY-BASEL , 2024 , 14 (3) . |
| MLA | Wang, Jinwei et al. "Soil Gaseous Carbon Emissions from Lettuce Fields as Influenced by Different Irrigation Lower Limits and Methods" . | AGRONOMY-BASEL 14 . 3 (2024) . |
| APA | Wang, Jinwei , Hamoud, Yousef Alhaj , Zhu, Qinyuan , Shaghaleh, Hiba , Chen, Jingnan , Zhong, Fenglin et al. Soil Gaseous Carbon Emissions from Lettuce Fields as Influenced by Different Irrigation Lower Limits and Methods . | AGRONOMY-BASEL , 2024 , 14 (3) . |
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Nonheading Chinese cabbage is an important leafy vegetable, and quantitative identification and automated analysis of nonheading Chinese cabbage leaves are crucial for cultivating new varieties with higher quality, yield, and resistance. Traditional leaf phenotypic analysis relies mainly on phenotypic observation and the practical experience of breeders, leading to issues such as time consumption, labor intensity, and low precision, which result in low breeding efficiency. Considering these issues, a method for the extraction and analysis of phenotypes of nonheading Chinese cabbage leaves is proposed, targeting four qualitative traits and ten quantitative traits from 1500 samples, by integrating deep learning and OpenCV image processing technology. First, a leaf classification model is trained using YOLOv8 to infer the qualitative traits of the leaves, followed by the extraction and calculation of the quantitative traits of the leaves using OpenCV image processing technology. The results indicate that the model achieved an average accuracy of 95.25%, an average precision of 96.09%, an average recall rate of 96.31%, and an average F1 score of 0.9620 for the four qualitative traits. From the ten quantitative traits, the OpenCV-calculated values for the whole leaf length, leaf width, and total leaf area were compared with manually measured values, showing RMSEs of 0.19 cm, 0.1762 cm, and 0.2161 cm2, respectively. Bland-Altman analysis indicated that the error values were all within the 95% confidence intervals, and the average detection time per image was 269 ms. This method achieved good results in the extraction of phenotypic traits from nonheading Chinese cabbage leaves, significantly reducing the personpower and time costs associated with genetic resource analysis. This approach provides a new technique for the analysis of nonheading Chinese cabbage genetic resources that is high-throughput, precise, and automated.
Keyword ：
deep learning deep learning leaf phenotype leaf phenotype nonheading Chinese cabbage nonheading Chinese cabbage OpenCV OpenCV
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| GB/T 7714 | Xu, Haobin , Fu, Linxiao , Li, Jinnian et al. A Method for Analyzing the Phenotypes of Nonheading Chinese Cabbage Leaves Based on Deep Learning and OpenCV Phenotype Extraction [J]. | AGRONOMY-BASEL , 2024 , 14 (4) . |
| MLA | Xu, Haobin et al. "A Method for Analyzing the Phenotypes of Nonheading Chinese Cabbage Leaves Based on Deep Learning and OpenCV Phenotype Extraction" . | AGRONOMY-BASEL 14 . 4 (2024) . |
| APA | Xu, Haobin , Fu, Linxiao , Li, Jinnian , Lin, Xiaoyu , Chen, Lingxiao , Zhong, Fenglin et al. A Method for Analyzing the Phenotypes of Nonheading Chinese Cabbage Leaves Based on Deep Learning and OpenCV Phenotype Extraction . | AGRONOMY-BASEL , 2024 , 14 (4) . |
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When optimizing irrigation methods, much consideration is given to crop growth indicators while less attention has been paid to soil's gaseous carbon (C) and nitrogen (N) emission indicators. Therefore, adopting an irrigation practice that can reduce emissions while maintaining crop yield and quality is of great interest. Thus, open-field experiments were conducted from September 2020 to January 2022 using a single-factor randomized block design with three replications. The lettuce plants ("Feiqiao Lettuce No.1") were grown using four different irrigation methods established by setting the lower limit of drip irrigation to 75%, 65%, and 55% of soil water content at field capacity corresponding to DR1, DR2, and DR3, respectively. Furrow irrigation (FI) was used as a control. Crop growth indicators and soil gas emissions were observed. Results showed that the mean lettuce yield under DR1 (64,500 kg/ha) was the highest, and it was lower under DR3 and FI. The lettuces under DR3 showed greater concentrations of crude fiber, vitamin C, and soluble sugar, and a greater nitrate concentration. Compared with FI, the DR treatments were more conducive to improving the comprehensive quality of lettuce, including the measured appearance and nutritional quality. Among all the irrigation methods, FI had the maximum cracking rate of lettuce, reaching 25.3%, 24.6%, and 22.7%, respectively, for the three continuous seasons. The stem cracking rates under DR2 were the lowest-only 10.1%, 14.4%, and 8.2%, respectively, which were decreased to nearly half compared with FI. The entropy model detected that the weight coefficient evaluation value of DR2 was the greatest, reaching 0.93, indicating that the DR2 method has the optimal benefits under comprehensive consideration of water saving, yield increase, quality improvement, and emission reduction.
Keyword ：
drip irrigation drip irrigation emission reduction emission reduction entropy weight coefficient entropy weight coefficient lettuce lettuce
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| GB/T 7714 | Hou, Maomao , Zhang, Houdong , Shaghaleh, Hiba et al. Optimization of a Lower Irrigation Limit for Lettuce Based on Comprehensive Evaluation: A Field Experiment [J]. | PLANTS-BASEL , 2024 , 13 (6) . |
| MLA | Hou, Maomao et al. "Optimization of a Lower Irrigation Limit for Lettuce Based on Comprehensive Evaluation: A Field Experiment" . | PLANTS-BASEL 13 . 6 (2024) . |
| APA | Hou, Maomao , Zhang, Houdong , Shaghaleh, Hiba , Chen, Jingnan , Zhong, Fenglin , Hamoud, Yousef Alhaj et al. Optimization of a Lower Irrigation Limit for Lettuce Based on Comprehensive Evaluation: A Field Experiment . | PLANTS-BASEL , 2024 , 13 (6) . |
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Cytokinins (CKs) are among the hormones that regulate plants' growth and development, and the CKX and IPT genes, which are CK degradation and biosynthesis genes, respectively, play important roles in fine-tuning plants' cytokinin levels. However, the current research on the function of IPT and CKX in cucumber's growth, development, and response to abiotic stress is not specific enough, and their regulatory mechanisms are still unclear. In this study, we focused on the IPT and CKX genes in cucumber, analyzed the physiological and biochemical properties of their encoded proteins, and explored their expression patterns in different tissue parts and under low light, salt stress, and drought stress. Eight CsCKX and eight CsIPT genes were identified from the cucumber genome. We constructed a phylogenetic tree from the amino acid sequences and performed prediction analyses of the cis-acting elements of the CsCKX and CsIPT promoters to determine whether CsCKXs and CsIPTs are responsive to light, abiotic stress, and different hormones. We also performed expression analysis of these genes in different tissues, and we found that CsCKXs and CsIPTs were highly expressed in roots and male flowers. Thus, they are involved in the whole growth and development process of the plant. This paper provides a reference for further research on the biological functions of CsIPT and CsCKX in regulating the growth and development of cucumber and its response to abiotic stress.
Keyword ：
abiotic stress response abiotic stress response CsCKXs CsCKXs CsIPTs CsIPTs cucumber cucumber growth and development growth and development
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| GB/T 7714 | Xu, Yang , Ran, Shengxiang , Li, Shuhao et al. Genome-Wide Identification and Abiotic Stress Expression Analysis of CKX and IPT Family Genes in Cucumber (Cucumis sativus L.) [J]. | PLANTS-BASEL , 2024 , 13 (3) . |
| MLA | Xu, Yang et al. "Genome-Wide Identification and Abiotic Stress Expression Analysis of CKX and IPT Family Genes in Cucumber (Cucumis sativus L.)" . | PLANTS-BASEL 13 . 3 (2024) . |
| APA | Xu, Yang , Ran, Shengxiang , Li, Shuhao , Lu, Junyang , Huang, Weiqun , Zheng, Jingyuan et al. Genome-Wide Identification and Abiotic Stress Expression Analysis of CKX and IPT Family Genes in Cucumber (Cucumis sativus L.) . | PLANTS-BASEL , 2024 , 13 (3) . |
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我国是人均水资源匮乏的国家，节水灌溉对于绿色农业和经济社会的可持续发展具有重要现实意义。本文围绕节水灌溉对块根作物产量与品质、农田土壤微生物的影响，阐述当前研究进展，并提出亟待解决的关键问题，以期为块根作物增产提质和水资源高效利用提供理论依据。
Keyword ：
产量 产量 品质 品质 土壤微生物 土壤微生物 块根作物 块根作物 节水灌溉 节水灌溉
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| GB/T 7714 | 黄艳 , 金秋 , 陈竞楠 et al. 节水灌溉对块根作物和土壤微生物影响的研究进展 [J]. | 中国资源综合利用 , 2024 , 42 (04) : 115-119 . |
| MLA | 黄艳 et al. "节水灌溉对块根作物和土壤微生物影响的研究进展" . | 中国资源综合利用 42 . 04 (2024) : 115-119 . |
| APA | 黄艳 , 金秋 , 陈竞楠 , 肖颖 , 佘翔宇 , 侯毛毛 . 节水灌溉对块根作物和土壤微生物影响的研究进展 . | 中国资源综合利用 , 2024 , 42 (04) , 115-119 . |
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1-deoxy-D-xylulose-5-phosphate synthase (DXS) is a rate-limiting enzyme in terpene synthesis that can affect the accumulation of secondary metabolites in plants. In this study, three DXS gene family members were identified in the tomato genome-wide database. Using bioinformatics methods, we analyzed the gene structure, evolutionary affinities, and cis-acting elements of the SlDXS gene family members. Promoters of SlDXS genes contain plant hormone-responsive elements such as the CGTCA-motif, TGACG-motif, ABRE, TCA-element, TGA-element, ERE, CAT-box, and AACA-motif, which suggested that the SlDXS gene family may play an important role in hormone response. The RT-qPCR analysis showed that the tomato DXS2 gene was able to respond upon exposure to methyl jasmonate (MeJA). The construction of a virus-induced gene silencing (VIGS) vector for the SlDXS gene showed that the SlDXS2 gene was also able to respond to MeJA in silenced plants, but the induction level was lower relative to that of wild-type plants. The SlDXS1 gene is associated with the synthesis of photosynthetic pigments. This study provides a reference for the further elucidation of the DXS gene's biological function in the terpenoid synthesis pathway in tomatoes.
Keyword ：
DXS DXS expression analysis expression analysis gene silencing gene silencing tomato tomato
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| GB/T 7714 | Ge, Haicui , Lu, Junyang , Han, Mingxuan et al. Identification and Functional Analysis of 1-Deoxy-D-xylulose-5-phosphate Synthase Gene in Tomatoes (Solanum lycopersicum) [J]. | HORTICULTURAE , 2024 , 10 (3) . |
| MLA | Ge, Haicui et al. "Identification and Functional Analysis of 1-Deoxy-D-xylulose-5-phosphate Synthase Gene in Tomatoes (Solanum lycopersicum)" . | HORTICULTURAE 10 . 3 (2024) . |
| APA | Ge, Haicui , Lu, Junyang , Han, Mingxuan , Lu, Linye , Tian, Jun , Zheng, Hongzhe et al. Identification and Functional Analysis of 1-Deoxy-D-xylulose-5-phosphate Synthase Gene in Tomatoes (Solanum lycopersicum) . | HORTICULTURAE , 2024 , 10 (3) . |
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随着智慧时代的到来，云计算、大数据技术为园林植物生长信息的分析和利用提供了新方法，为园林植物种植和管理提供了强大助力。水肥管理是园林植物种植过程中的关键环节，如何利用前沿技术提升园林植物水肥资源效率，是园林产业升级面临的现实问题之一。首先分析智慧时代的技术特征，其次分析园林植物种类和水肥需求特性，最后根据传统园林植物水肥利用效率提升模式存在的不足，提出水肥利用效率的提升路径，以期为先进技术更好地赋能园林植物水肥管理提供参考。
Keyword ：
利用效率 利用效率 园林植物 园林植物 智慧技术 智慧技术 智能装备 智能装备 水肥资源 水肥资源
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| GB/T 7714 | 林毅雁 , 黄艳 , 黄彦晶 et al. 智慧时代园林植物水肥资源利用效率的提升路径研究 [J]. | 中国资源综合利用 , 2024 , 42 (10) : 88-92 . |
| MLA | 林毅雁 et al. "智慧时代园林植物水肥资源利用效率的提升路径研究" . | 中国资源综合利用 42 . 10 (2024) : 88-92 . |
| APA | 林毅雁 , 黄艳 , 黄彦晶 , 黄从正 , 张后东 , 刘馨悦 et al. 智慧时代园林植物水肥资源利用效率的提升路径研究 . | 中国资源综合利用 , 2024 , 42 (10) , 88-92 . |
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