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学者姓名：温志强
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Abstract ：
Grifola frondosa is a valuable medicinal and edible mushroom whose industrial cultivation and developmental mechanisms remain poorly understood. In this study, we systematically investigated the optimal cultivation parameters and molecular basis of fruiting body development using the white strain Gr0001+3 through integrated physiological and transcriptomic approaches. The results showed that the optimal liquid medium composition was glucose (28.5 g/L), yeast extract (11.5 g/L), and MgSO4 (2 g/L), with a C/N ratio of 10:1. This composition achieved a mycelial biomass of 2.333 g/L via an orthogonal design. Ideal culture conditions were 100 mL/250 mL liquid volume, 10% inoculum size, and pH 4.0 in single-factor experiments. The fruiting body developmental transcriptomes were analyzed in four stages: early primordia (EP), middle primordia (MP), late primordia (LP), and mature fruiting body (FB). Principal component analysis revealed distinct transcriptional profiles, with greater similarities among later developmental stages. Differential gene expression peaked during the LP vs. FB transition. Functional enrichment (GO/KEGG) showed conserved biological processes in the MP-LP-FB transitions. Heat shock proteins (hsp_78/hsp_82) and the cAMP signaling pathway component (PKAC) were involved in fruiting body development, based on RT-qPCR. This work establishes practical cultivation parameters and offers fundamental insights into the molecular regulation of G. frondosa development, providing a comprehensive foundation for advancing the industrial production of this mushroom.
Keyword ：
cAMP signaling pathway cAMP signaling pathway fruiting body development fruiting body development Grifola frondosa Grifola frondosa heat shock proteins heat shock proteins liquid culture optimization liquid culture optimization mycelial biomass mycelial biomass transcriptome analysis transcriptome analysis
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| GB/T 7714 | Ren, Hui-Hui , Zhang, Jia-Ye , Wang, Jia-Yuan et al. Advancing Industrial Production of White Grifola frondosa: Liquid Inoculum Culture Parameter Optimization and Molecular Insights into Fruiting Body Development [J]. | HORTICULTURAE , 2025 , 11 (10) . |
| MLA | Ren, Hui-Hui et al. "Advancing Industrial Production of White Grifola frondosa: Liquid Inoculum Culture Parameter Optimization and Molecular Insights into Fruiting Body Development" . | HORTICULTURAE 11 . 10 (2025) . |
| APA | Ren, Hui-Hui , Zhang, Jia-Ye , Wang, Jia-Yuan , Xiao, Shang-Shang , Liu, Su-Ya , Sun, Bao-Yue et al. Advancing Industrial Production of White Grifola frondosa: Liquid Inoculum Culture Parameter Optimization and Molecular Insights into Fruiting Body Development . | HORTICULTURAE , 2025 , 11 (10) . |
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Wet bubble disease (WBD) in Agaricus bisporus caused by Mycogone species imposes a substantial economic loss to mushroom production in China. Currently, fungicide application is the main method to control WBD. However, excessive use of fungicides is challenged by the appearance of resistance and food safety. Therefore, it is necessary to explore safe and efficient strategies to control WBD. Strain 9-13, isolated from the rhizosphere soil of Taxus chinensis, showed strong inhibitory activity against three Mycogone species. According to morphological and biochemical characteristics and multilocus phylogenetic analysis, the strain was identified as Streptomyces nojiriensis. In addition, strain 9-13 extracts significantly inhibited mycelial growth and spore germination of M. perniciosa, M. rosea, and M. xinjiangensis in vitro. Strain 9-13 and its extracts also exhibited broad-spectrum antifungal activities against 12 selected plant pathogenic fungi. Scanning electron microscopic observations showed that the extracts destroyed mycelial structure, inducing mycelia to twist and shrink. Moreover, transmission electron microscopy revealed that the extracts resulted in severe plasmolysis, rupture of the cell membrane, and a decrease in cell inclusions, and the cell wall had a rough and uneven surface. Notably, the extracts obviously reduced disease severity and incidence of WBD by from 83.85 to 87.32% in fruiting bodies and 77.36% in mushroom beds and maintained fruiting time and color on harvested mushrooms. Collectively, these results clearly indicate that S. nojiriensis 9-13 is a promising biocontrol agent to control WBD on A. bisporus.
Keyword ：
antifungal mechanism antifungal mechanism biocontrol biocontrol broad-spectrum activities broad-spectrum activities Mycogone sp. Mycogone sp. Streptomyces nojiriensis Streptomyces nojiriensis wet bubble disease wet bubble disease
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| GB/T 7714 | Shi, Niuniu , Chen, Furu , Wen, Zhiqiang et al. Antifungal Activity and Possible Mechanism of Streptomyces nojiriensis 9-13 Against Mycogone sp., Causing Wet Bubble Disease on Agaricus bisporus [J]. | PLANT DISEASE , 2024 , 108 (10) : 3097-3107 . |
| MLA | Shi, Niuniu et al. "Antifungal Activity and Possible Mechanism of Streptomyces nojiriensis 9-13 Against Mycogone sp., Causing Wet Bubble Disease on Agaricus bisporus" . | PLANT DISEASE 108 . 10 (2024) : 3097-3107 . |
| APA | Shi, Niuniu , Chen, Furu , Wen, Zhiqiang , Yang, Jun , Zhang, Nan , Yin, Yue et al. Antifungal Activity and Possible Mechanism of Streptomyces nojiriensis 9-13 Against Mycogone sp., Causing Wet Bubble Disease on Agaricus bisporus . | PLANT DISEASE , 2024 , 108 (10) , 3097-3107 . |
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The Mycogone perniciosa disease of Agaricus bisporus is highly contagious, with insignificant early symptoms and a long infestation period. Currently, there is a lack of a convenient and rapid means to detect the disease for early control. By using the transmission route of the disease, this paper focuses on M. perniciosa chlamydospore detection in contaminated soil. Microscopic hyperspectral images of M. perniciosa chlamydospore in contaminated soil were obtained to establish a detection model. Given a small target and a complex background, we proposed an improved spore detection model based on a faster regional convolutional neural network (Faster RCNN). Furthermore, we combined the residual network Resnet50 and feature pyramid network (FPN) to extract thick spore target features at multiple scales. Meanwhile, we optimized the region proposal network (RPN) region proposal generation by adding two small scales to improve the performance of the detection model. The first three principal components (with 95% or more information) and RGB images were selected as model inputs, respectively, and the final average precision (AP) was 94.68% and 92.35%, respectively. This PC-based model also was compared to the VGG16 and Resnet50-based feature extraction networks of Faster R-CNN and Darknet53-based feature extraction network of the YOLOv3 model, and the AP was found to improve by 5.41%, 4.78%, and 6.34%, respectively. The results showed that micro-hyperspectral imaging combined with deep learning methods could accurately detect the chlamydospore in the soil, providing new methods and ideas for the early prevention and detection of M. perniciosa disease of A. bisporus.
Keyword ：
Agaricus bisporus Agaricus bisporus Deep learning Deep learning Faster R-CNN Faster R-CNN Microscopic hyperspectral imaging Microscopic hyperspectral imaging Small target detection Small target detection
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| GB/T 7714 | Wei, Xuan , Liu, Yongjie , Song, Qiming et al. Microscopic hyperspectral imaging and an improved detection model based detection of Mycogone perniciosa chlamydospore in soil [J]. | EUROPEAN JOURNAL OF AGRONOMY , 2023 , 152 . |
| MLA | Wei, Xuan et al. "Microscopic hyperspectral imaging and an improved detection model based detection of Mycogone perniciosa chlamydospore in soil" . | EUROPEAN JOURNAL OF AGRONOMY 152 (2023) . |
| APA | Wei, Xuan , Liu, Yongjie , Song, Qiming , Zou, Jinping , Wen, Zhiqiang , Li, Jiayu et al. Microscopic hyperspectral imaging and an improved detection model based detection of Mycogone perniciosa chlamydospore in soil . | EUROPEAN JOURNAL OF AGRONOMY , 2023 , 152 . |
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In the production of edible fungi, the use of degraded strains in cultivation incurs significant economic losses. Based on micro-hyperspectral imaging and machine learning, this study proposes an early, nondestructive method for detecting different degradation degrees of Pleurotus geesteranus strains. In this study, an undegraded strain and three different degradation-level strains were used. During the mycelium growth, 600 micro-hyperspectral images were obtained. Based on the average transmittance spectra of the region of interest (ROI) in the range of 400-1000 nm and images at feature bands, feature spectra and images were extracted using the successive projections algorithm (SPA) and the deep residual network (ResNet50), respectively. Different feature input combinations were utilized to establish support vector machine (SVM) classification models. Based on the results, the spectra-input-based model performed better than the image-input-based model, and feature extraction improved the classification results for both models. The feature-fusion-based SPA+ResNet50-SVM model was the best; the accuracy rate of the test set was up to 90.8%, which was better than the accuracy rates of SPA-SVM (83.3%) and ResNet50-SVM (80.8%). This study proposes a nondestructive method to detect the degradation of Pleurotus geesteranus strains, which could further inspire new methods for the phenotypic identification of edible fungi.
Keyword ：
classification classification edible fungi edible fungi micro-hyperspectral imaging micro-hyperspectral imaging phenotype phenotype strain degradation strain degradation
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| GB/T 7714 | Wei, Xuan , Liu, Shiyang , Xie, Chuangyuan et al. Nondestructive detection of Pleurotus geesteranus strain degradation based on micro-hyperspectral imaging and machine learning [J]. | FRONTIERS IN PLANT SCIENCE , 2023 , 14 . |
| MLA | Wei, Xuan et al. "Nondestructive detection of Pleurotus geesteranus strain degradation based on micro-hyperspectral imaging and machine learning" . | FRONTIERS IN PLANT SCIENCE 14 (2023) . |
| APA | Wei, Xuan , Liu, Shiyang , Xie, Chuangyuan , Fang, Wei , Deng, Chanjuan , Wen, Zhiqiang et al. Nondestructive detection of Pleurotus geesteranus strain degradation based on micro-hyperspectral imaging and machine learning . | FRONTIERS IN PLANT SCIENCE , 2023 , 14 . |
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The Mycogone perniciosa disease of Agaricus bisporus is highly contagious, with insignificant early symptoms and a long infestation period. Currently, there is a lack of a convenient and rapid means to detect the disease for early control. By using the transmission route of the disease, this paper focuses on M. perniciosachlamydospore detection in contaminated soil. Microscopic hyperspectral images of M. perniciosachlamydospore in contaminated soil were obtained to establish a detection model. Given a small target and a complex background, we proposed an improved spore detection model based on a faster regional convolutional neural network (Faster RCNN). Furthermore, we combined the residual network Resnet50 and feature pyramid network (FPN) to extract thick spore target features at multiple scales. Meanwhile, we optimized the region suggestion network (RPN) suggestion box generation by adding two small sizes to improve the performance of the detection model. The first three principal components (with 95% or more information) and RGB images were selected as model inputs, respectively, and the final average precision(AP) was 94.68% and 92.35%, respectively. This PC-based model also was compared to the VGG16 and Resnet50-based feature extraction networks of Faster RCNN and Darknet53-based feature extraction network of the YOLOv3 model, and the AP was found to improve by 5.41%, 4.78%, and 6.34%, respectively. The results showed that micro-hyperspectral imaging combined with deep learning methods could accurately detect the chlamydospore in the soil, providing new methods and ideas for the early prevention and detection of M. perniciosa disease of A. bisporus. © 2023, The Authors. All rights reserved.
Keyword ：
Convolutional neural networks Convolutional neural networks Deep learning Deep learning Disease control Disease control Extraction Extraction Feature extraction Feature extraction Fungi Fungi Hyperspectral imaging Hyperspectral imaging Learning systems Learning systems Soil pollution Soil pollution Soils Soils
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| GB/T 7714 | Wei, Xuan , Liu, Yongjie , Song, Qiming et al. Microscopic Hyperspectral Imaging and Deep Learning Based Detection of Mycogone Perniciosa Chlamydospore in Soil [J]. | SSRN , 2023 . |
| MLA | Wei, Xuan et al. "Microscopic Hyperspectral Imaging and Deep Learning Based Detection of Mycogone Perniciosa Chlamydospore in Soil" . | SSRN (2023) . |
| APA | Wei, Xuan , Liu, Yongjie , Song, Qiming , Zou, Jinping , Wen, Zhiqiang , Li, Jiayu et al. Microscopic Hyperspectral Imaging and Deep Learning Based Detection of Mycogone Perniciosa Chlamydospore in Soil . | SSRN , 2023 . |
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Auricularia heimuer Auricularia heimuer cobweb disease cobweb disease Hypomyces mycophilus Hypomyces mycophilus
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| GB/T 7714 | Zhang, Jiaye , Wen, Die , Zhu, Yifan et al. First Report of Cobweb Disease of Auricularia heimuer Caused by Hypomyces mycophilus in Fujian Province, China [J]. | PLANT DISEASE , 2023 , 107 (8) . |
| MLA | Zhang, Jiaye et al. "First Report of Cobweb Disease of Auricularia heimuer Caused by Hypomyces mycophilus in Fujian Province, China" . | PLANT DISEASE 107 . 8 (2023) . |
| APA | Zhang, Jiaye , Wen, Die , Zhu, Yifan , Wen, Zhiqiang . First Report of Cobweb Disease of Auricularia heimuer Caused by Hypomyces mycophilus in Fujian Province, China . | PLANT DISEASE , 2023 , 107 (8) . |
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利用反向传播(back propagation, BP)神经网络及支持向量机(support vector machine, SVM)优化模型等算法实现了双孢蘑菇多酚氧化酶(polyphenol oxidase, PPO)的检测与双孢蘑菇的病害判别.首先各采集200个健康、染病双孢蘑菇在全波段(450～1 000 nm)上的高光谱数据及其PPO值.采用竞争自适应加权算法(competitive adaptive reweighted sampling, CARS)和连续投影算法(successive projections algorithm, SPA)提取对PPO值敏感的特征波段，并建立偏最小二乘回归(partial least squares regression, PLSR)预测模型.结果表明SPA-PLSR模型(R_P=0.917)的预测精度最高.其次采用逐步回归法对SPA提取的特征波长逐步引入与疣孢霉病相关的特征信息，再利用相关性分析探究所引入的特征信息与染病情况的相关性，最终优选出12个特征波长.对比了极限学习机(extreme learning machine, ELM)、SVM、粒子群优化后的支持向量机(particle swarm optimization-SVM,PSO-SVM)和BP神经网络4种模型对双孢蘑菇染病判别的结果，其中隐含层神经元节点数为14的BP神经网络模型建模效果最好，预测集总体判别率为94.737%.本研究建立的判别模型能够有效判别双孢蘑菇早期疣孢霉病.
Keyword ：
BP神经网络 BP神经网络 PSO算法 PSO算法 双孢蘑菇 双孢蘑菇 逐步回归 逐步回归 高光谱成像技术 高光谱成像技术
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| GB/T 7714 | 黄亮 , 魏萱 , 陈子涵 et al. 基于优化SVM和BP神经网络检测双孢蘑菇早期病害 [J]. | 福建农林大学学报(自然科学版) , 2022 , 51 (06) : 857-864 . |
| MLA | 黄亮 et al. "基于优化SVM和BP神经网络检测双孢蘑菇早期病害" . | 福建农林大学学报(自然科学版) 51 . 06 (2022) : 857-864 . |
| APA | 黄亮 , 魏萱 , 陈子涵 , 温志强 . 基于优化SVM和BP神经网络检测双孢蘑菇早期病害 . | 福建农林大学学报(自然科学版) , 2022 , 51 (06) , 857-864 . |
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Mycogone perniciosa is the main causative agent of wet bubble disease, which causes severe damage to the production of the cultivated mushroom Agaricus bisporus around the world. Whole-genome sequencing of 12 isolates of M. perniciosa was performed using the Illumina sequencing platform, and the obtained paired-end reads were used to assemble complete mitochondrial genomes. Intraspecific comparisons of conserved protein-coding genes, transfer RNA (tRNA) and ribosomal RNA (rRNA) genes, introns, and intergenic regions were conducted. Five different mitochondrial DNA (mtDNA) haplotypes were detected among the tested isolates, ranging from 89,080 to 93,199 bp in length. All of the mtDNAs contained the same set of 14 protein-coding genes and 2 rRNA and 27 tRNA genes, which shared high sequence similarity. In contrast, the number, insertion sites, and sequences of introns varied greatly among the mtDNAs. Eighteen of 43 intergenic regions differed among the isolates, reflecting 65 single nucleotide polymorphisms, 76 indels, and the gain/loss of nine long fragments. Intraspecific comparison revealed that two introns were located within tRNA genes, which is the first detailed description of mitochondrial tRNA introns. Intronic sequence comparison within the same insertion sites revealed the formation process of two introns, which also illustrated a fast evolutionary rate of introns among M. perniciosa isolates. Based on the intron distribution pattern, a pair of universal primers and four pairs of isolate-specific primers were designed and were used to identify the five mtDNA types. In summary, the rapid gain or loss of mitochondrial introns could be an ideal marker for population genetics analysis.
Keyword ：
fungal pathogens fungal pathogens genomics genomics intraspecific comparison intraspecific comparison mtDNA mtDNA tRNA intron tRNA intron twintron twintron
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| GB/T 7714 | Deng, Youjin , Wu, Xin , Wen, Die et al. Intraspecific Mitochondrial DNA Comparison of Mycopathogen Mycogone perniciosa Provides Insight Into Mitochondrial Transfer RNA Introns [J]. | PHYTOPATHOLOGY , 2021 , 111 (4) : 639-648 . |
| MLA | Deng, Youjin et al. "Intraspecific Mitochondrial DNA Comparison of Mycopathogen Mycogone perniciosa Provides Insight Into Mitochondrial Transfer RNA Introns" . | PHYTOPATHOLOGY 111 . 4 (2021) : 639-648 . |
| APA | Deng, Youjin , Wu, Xin , Wen, Die , Huang, Haichen , Chen, Yilei , Mukhtar, Irum et al. Intraspecific Mitochondrial DNA Comparison of Mycopathogen Mycogone perniciosa Provides Insight Into Mitochondrial Transfer RNA Introns . | PHYTOPATHOLOGY , 2021 , 111 (4) , 639-648 . |
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【目的】有害疣孢霉菌(Mycogone perniciosa)引起的双孢蘑菇疣孢霉病,是破坏性极强的真菌类病害,本研究拟基于高光谱成像技术,建立双孢蘑菇疣孢霉病早期快速检测方法。【方法】对200个健康双孢蘑菇样本与200个染病双孢蘑菇样本采集全波段(401～1046 nm)可见/近红外高光谱图像信息,利用Savitzky-Golay卷积一阶求导、Savitzky-Golay卷积平滑(SG平滑)、多元散射校正(MSC)分别对360个波段(全波段)的高光谱图像信息进行预处理后,对比随机森林(Random forest, RF)、支持向量机(Support vector machine, SVM)和极限学习机(Extreme learning machine,ELM)3种模型对健康和染病双孢蘑菇鉴别准确度进行分析。【结果】3种鉴别模型的结果接近,其中,MSC-SVM模型检测效果最优,将原始测试集和预测集总体样本鉴别准确度分别由85.02%和87.38%提升至92.21%和91.04%。【结论】本研究建立的MSC-SVM模型可以有效提高基于全波段的双孢蘑菇疣孢霉病早期的鉴别准确度,同时,为进一步开发双孢蘑菇病害早期的快速无损鉴别设备提供了理论依据和方法。
Keyword ：
双孢蘑菇 双孢蘑菇 病害早期检测 病害早期检测 高光谱成像技术 高光谱成像技术
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| GB/T 7714 | 陈子涵 , 黄亮 , 温志强 et al. 基于高光谱成像技术的双孢蘑菇病害早期诊断 [J]. | 福建农业学报 , 2021 , 36 (11) : 1365-1372 . |
| MLA | 陈子涵 et al. "基于高光谱成像技术的双孢蘑菇病害早期诊断" . | 福建农业学报 36 . 11 (2021) : 1365-1372 . |
| APA | 陈子涵 , 黄亮 , 温志强 , 温蝶 , 王胜楠 , 廖小玲 et al. 基于高光谱成像技术的双孢蘑菇病害早期诊断 . | 福建农业学报 , 2021 , 36 (11) , 1365-1372 . |
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选用白色耐高温灰树花(Grifola frondosa) Gr0001+3与性状优良的5个栽培菌株进行配对,得到13株杂交子作为试验菌株,研究温度和pH对不同杂交子生长的影响,并对杂交子进行分子鉴定。试验筛选出5株生长较快的杂交子,杂交子的菌丝最适生长温度为25℃,最适生长pH为5。共发现6种可以用于杂交子鉴定的RAPD和ISSR引物,并成功鉴定了其中7个杂交子菌株。为灰树花工厂化栽培专用菌株的生长条件控制、杂交子鉴定提供理论依据和实用方法。
Keyword ：
分子鉴定 分子鉴定 杂交子 杂交子 灰树花 灰树花
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| GB/T 7714 | 权新华 , 武鑫 , 温蝶 et al. 灰树花杂交子的特性与分子鉴定 [J]. | 中国食用菌 , 2020 , 39 (10) : 42-45 . |
| MLA | 权新华 et al. "灰树花杂交子的特性与分子鉴定" . | 中国食用菌 39 . 10 (2020) : 42-45 . |
| APA | 权新华 , 武鑫 , 温蝶 , 温志强 . 灰树花杂交子的特性与分子鉴定 . | 中国食用菌 , 2020 , 39 (10) , 42-45 . |
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