Straw incorporation is an important measure to improve soil fertility and soil acidification. However, fresh straw that is returned to the field cannot be decomposed in a short time. Accumulation of undecomposed straw in the soil changes humus composition and the C structure. An experiment was designed to evaluate the effects of decomposed straw on soil fertility and microbial communities. Soil samples were collected from a rice-rice-tobacco region in southwestern China (The rice was Hongyou No 7, which was a new variety applied in 2007 by the Honghe State Agricultural Science Institute,Yunnan province, China). (The tobacco was K326. K326 was an excellent variety which Imported from Northup King Seed Company (USA) to China in 1985). The soil was mixed with different kinds of straw and incubated in a greenhouse. The responses of the soil fertility, microbial diversity, and microbial population were analyzed after 0, 16, and 33 d of incubation. Overall, we found that (a) the soil organic matter and the organic C content of each humus component were significantly increased after 33 d of incubation. In addition, the condensation and oxidation degrees of the soil C structure were decreased. (b) Community dynamics changes in the soil were accompanied by changes of incubation times. (c) Decomposed straw incorporation could stimulate potentially beneficial microbial populations. (d) Decomposed straw incorporation with microbial agent application could be the best practice for the application of biofertilizers.
The maturity affects the yield, quality, and economic value of tobacco leaves. Leaf maturity level discrimination is an important step in manual harvesting. However, the maturity judgment of fresh tobacco leaves by grower visual evaluation is subjective, which may lead to quality loss and low prices. Therefore, an objective and reliable discriminant technique for tobacco leaf maturity level based on near-infrared (NIR) spectroscopy combined with a deep learning approach of convolutional neural networks (CNNs) is proposed in this study. To assess the performance of the proposed maturity discriminant model, four conventional multiclass classification approaches—K-nearest neighbor (KNN), backpropagation neural network (BPNN), support vector machine (SVM), and extreme learning machine (ELM)—were employed for a comparative analysis of three categories (upper, middle, and lower position) of tobacco leaves. Experimental results showed that the CNN discriminant models were able to precisely classify the maturity level of tobacco leaves for the above three data sets with accuracies of 96.18%, 95.2%, and 97.31%, respectively. Moreover, the CNN models with strong feature extraction and learning ability were superior to the KNN, BPNN, SVM, and ELM models. Thus, NIR spectroscopy combined with CNN is a promising alternative to overcome the limitations of sensory assessment for tobacco leaf maturity level recognition. The development of a maturity-distinguishing model can provide an accurate, reliable, and scientific auxiliary means for tobacco leaf harvesting.
A Gram-stain-positive, motile, rod-shaped bacterial strain, YN-1 T , was isolated from a rice field in the town of Jietou, Yunnan Province, PR China. Colonies were circular, 1-2 mm in diameter, creamy white, with slightly irregular margins. The isolate grew optimally at 37 C, pH 7.0 and with 1.0 % (w/v) NaCl. On the basis of the results of 16S rRNA gene sequence similarity comparisons, YN-1 T clustered together with other species of the genus Bacillus and showed highest similarities with Bacillus onubensis 0911MAR22V3 T (98.0 %), Bacillus humi LMG22167 T (97.5 %), 'Bacillus timonensis' 10403023 (97.4 %) and 'Bacillus sinesaloumensis' P3516 (97.1 %). However, the DNA-DNA hybridization values between YN-1 T and closely related strains of species of the genus Bacillus were well below 47 %, indicating that they represent different taxa. The average nucleotide identity and the Genome-to-Genome Distance Calculator also revealed low relatedness (below 95 and 70 %, respectively) between YN-1 T and type strains of closely related species of the genus Bacillus. The DNA G+C content of the strain was 40 mol%. The major cellular fatty acids were iso-C 15 : 0 , anteiso-C 15 : 0 , and C 16 : 0. The polar lipids were diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, two unidentified phospholipids, three unidentified aminophospholipids and two other unidentified lipids. Physiological and biochemical test results were also different from those of the most closely related species. On the basis of the phenotypic, genetic and chemotaxonomic data, strain YN-1 T is considered to represent a novel species of the genus Bacillus, for which the name Bacillus aciditolerans sp. nov. is proposed, with strain YN-1 T (=CCTCC AB 2017280 T =JCM 32973 T) as the type strain.
Compound biofertilizers could improve the nutrient condition of the ecosystem and the fertility of agricultural fields. At micro level, the soil microbial communities could be influenced, resulting in taxonomic and functional changes in the soil microbiome. In the present research, compound biofertilizers were applied into tobacco (Nocotiana tabacum L., Family: Solanaceae) field ecosystems of Qianxi, Weining, and Meitan city of China, and the diversity of microbial communities were determined using metagenome technique. The results revealed that nitrogen compounds of each treatment were significantly increased after 30 d. In addition, indigenous microorganisms in fertilizer were developed into the dominant bacteria, and Compound Biofertilizer III has a potential and great effect compared with others. Depending on our findings, the research‐based knowledge obtained between compound biofertilizers, and soil microbiome could provide a clue to the development of environmentally friendly and long‐acting biofertilizer application processes in the agricultural fields.
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