由核盘菌(Sclerotinia sclerotiorum)引起的菌核病是一种毁灭性的土传大豆病害，会造成巨大的产量损失。我们以前报道过变栖克雷伯氏菌FH-1可以降解莠去津除草剂，并且可以增加莠去津敏感作物(如大豆)的营养生长。我们发现FH-1可以促进大豆生长并诱导对菌核病菌的抗性，为了证明FH-1对大豆菌核病菌的生防机制并评价其生防能力，我们在体外培养基试验中证明菌株FH-1可以固定培养基中的氮，溶解无机磷和钾，并产生吲哚乙酸和铁载体，具有促进植物生长的潜力。盆栽试验结果表明，变栖克雷伯氏菌FH-1能促进大豆植株发育，显著提高株高、鲜重和根长，并诱导大豆叶片对菌核病的抗性。用菌株FH-1治疗的疾病进展曲线下面积(AUDPC)显著低于对照，并且在48小时内减少了高达42.2%。(P < 0.001)。此外，紫外分光光度计法测量结果表明菌株FH-1可以增强参与大豆植物防御的过氧化氢酶、超氧化物歧化酶、过氧化物酶、苯丙氨酸解氨酶和多酚氧化酶的酶活性，并减少了叶片中丙二醛的积累。定量实时PCR检测了可能参与大豆抵抗核盘菌胁迫的相关基因的转录水平，结果表明诱导抗性的机制似乎主要是由于变栖克雷伯氏菌FH-1诱导PR10、PR12、AOS、CHS和PDF1.2基因转录水平的提高。利用结晶紫染色法测定了菌株FH-1具有生物膜形成能力，用共聚焦荧光显微镜和扫描电镜观测菌株FH-1在大豆根上的定殖情况，菌株FH-1可以定殖在大豆根表面、根毛和外皮层上形成生物膜。综上所述，变栖克雷伯氏菌FH-1在大豆根部的定殖有助于诱导参与植物保护的防御酶和相关防御基因的表达，诱导大豆对菌核病菌的抗性表现出生物防治潜力。这对大豆的种植和生长具有重要意义。此外，本研究有助于理解变种芽胞杆菌FH-1、大豆植株和核盘菌之间相互作用的有价值的第一步，这为绿色防控提供了新的思路。

Maize (Zea mays L.), also known as corn, is the third most cultivated crop in the world.  Northern corn leaf blight (NCLB) is a globally devastating maize foliar disease caused by Setosphaeria turcica (Luttrell) Leonard and Suggs.  Early intelligent diagnosis and warning is an effective and economical strategy to control this disease.  Today, deep learning is beginning to play an essential role in agriculture.  Notably, deep convolutional neural networks (DCNN) are amongst the most successful machine learning techniques in plant disease detection and diagnosis.  Our study aims to identify NCLB in the maize-producing area in Jilin Province based on several DCNN models.  We established a database of 985 leaf images of healthy and infected maize and applied data augmentation techniques including image segmentation, image resizing, image cropping, and image transformation, to expand to 30 655 images.  Several proven convolutional neural networks, such as AlexNet, GoogleNet, VGG16, and VGG19, were then used to identify diseases.  Based on the best performance of the DCNN pre-trained model GoogleNet, some of the recent loss functions developed for deep facial recognition tasks such as ArcFace, CosFace, and A-Softmax were applied to detect NCLB.  We found that a pre-trained GoogleNet architecture with the Softmax loss function can achieve an excellent accuracy of 99.94% on NCLB diagnosis.  The analysis was implemented in Python with two deep learning frameworks, Pytorch and Keras.  The techniques, training, validation, and test results are presented in this paper.  Overall, our study explores intelligent identification technology for NCLB and effectively diagnoses NCLB from images of maize.

The genus Adelphocoris (Hemiptera: Miridae) is a group of key insect pests in cotton fields in China that includes three dominant species: A. suturalis (Jakovlev), A. lineolatus (Goeze) and A. fasciaticollis (Reuter). Previous field surveys have found that adults of these Adelphocoris species usually move onto specific host plants when the plants enter the flowering stage. To determine the potential trade-offs for this host-plant preference behavior, the performance of these three Adelphocoris spp. on flowering and non-flowering cotton and alfalfa were compared in the laboratory. The results showed that Adelphocoris spp. had significantly higher nymphal developmental and survival rates, along with increased adult longevity and fecundity on flowering cotton and alfalfa than on non-flowering plants of either species. In addition, compared with cotton plants, alfalfa generally promoted better performance of these three Adelphocoris species, especially for A. lineolatus. Simple correlation analysis indicated that female adult longevity was positively correlated to male adult longevity and female fecundity, and female fecundity was positively correlated to nymphal development and survival rates. This study demonstrated a positive correlation between adult preference and offspring/adult performance for all three Adelphocoris species, with no evidence of any trade-offs for this preference for flowering host plants. These findings support the hypothesis that hemimetabolous insects such as mirid bugs have positive adult preference-adult/nymphal performance relationships, which is likely due to the similar feeding habits and nutritional requirements of adults and nymphs.

Porcine skeletal muscle genes play a major role in determining muscle growth and meat quality. Construction of a full-length cDNA library is an effective way to understand the expression of functional genes in muscle tissues. In addition, novel genes for further research could be identified in the library. In this study, we constructed a full-length cDNA library from porcine muscle tissue. The estimated average size of the cDNA inserts was 1 076 bp, and the cDNA fullness ratio was 86.2%. A total of 1 058 unique sequences with 342 contigs (32.3%) and 716 singleton (67.7%) expressed sequence tags (EST) were obtained by clustering and assembling. Meanwhile, 826 (78.1%) ESTs were categorized as known genes, and 232 (21.9%) ESTs were categorized as unknown genes. 65 novel porcine genes that exhibit no identity in the TIGR gene index of Sus scrofa and 124 full-length sequences with unknown functions were deposited in the dbEST division of GenBank (accession numbers: EU650784-EU650788, GE843306, GH228978-GH229100). The abundantly expressed genes in porcine muscle tissue were related to muscle fiber development, energy metabolism and protein synthesis. Gene ontology analysis showed that sequences expressed in porcine muscle tissue contained a high percentage of binding activity, catalytic activity, structural molecule activity and motor activity, which involved mainly in metabolic, cellular and developmental process, distributed mainly in intracellular region. The sequence data generated in this study would provide valuable information for identifying porcine genes expressed in muscle tissue and help to advance the study on the structure and function of genes in pigs.

Maize (Zea mays L.) is one of the world’s major food crops, and often suffers from tremendous yield loss caused by abiotic stresses. The MADS-box genes are known to play versatile roles in plants, controlling plant responses to multiple abiotic stresses. However, understanding of regulation of their expressions by the conventional loss-of-function approach is very difficult. So far, regulation of MADS-box gene expression is little known. The best approach to retrieve expression regulation of this category of genes is to characterize expression of their promoters. In this study, the promoter of a homolog (GenBank accession no. EC864166) of maize MADS-box gene m18 was cloned by way of genome-walking PCR, named Pro66. Predicative analysis indicated that Pro66 contains more than one TATA box and multiple cis-acting environmental conditions-responsive elements (ECREs). Pro66 could drive expression of the β-glucuronidase (GUS)-encoding gene in maize, and heterologous expression of GUS in red pepper stressed by water deficit, salt, copper, iron deficiency, heat, cold, and grown under short and long photoperiods, echoing predicative ECREs. Conclusively, maize MADS-box gene m18 likely plays versatile functions in maize response to multiple abiotic stresses due to the promoter with multiple cis-acting elements. The complex arrangement of multiple cis-acting elements in the promoter features meticulously regulated expression of m18. The results give informative clues for heterologous utilisation of the promoters in monocot and dicot species. The copy of the ECREs and heterologous expression of the promoter in dicot species are also discussed.