Inversion of soil carbon, nitrogen, and phosphorus in the Yellow River Wetland of Shaanxi Province using field in situ hyperspectroscopy

Soil nitrogen and phosphorus are directly related to soil quality and vegetation growth and are, therefore, a common research topic in studies on global climate change, material cycling, and information exchange in terrestrial ecosystems. However, collecting soil hyperspectral data under in situ conditions and predicting soil properties, which can effectively save time, manpower, material resources, and financial costs, have been generally undervalued. Recent optimization techniques have, however, addressed several of the limitations previously restricting this technique. In this study, hyperspectral data were taken from surface soils under different vegetation types in the wetlands of the Shaanxi Yellow River Wetland Provincial Nature Reserve. Through in situ original and first-order differential transformation spectral data, three prediction models for soil carbon, nitrogen, and phosphorus contents were established: partial least squares (PLSR), random forest (RF), and Gaussian process regression (GPR). The R2 and RMSR of the constructed models were then compared to select the optimal model for evaluating soil content. The soil organic carbon, total nitrogen, and total phosphorus content models established based on the first-order differential had a higher accuracy when modeling and during model validation than those of other models. Moreover, the PLSR model based on the original spectrum and the Gaussian process regression model had a superior inversion performance. These results provide solid theoretical and technical support for developing the optimal model for the quantitative inversion of wetland surface soil carbon, nitrogen, and phosphorus based on in situ hyperspectral technology

Cigarette Flavouring Regulation by Using Aroma-producing Microorganism Isolated from Maotai Daqu

The selected Moutai aromatic microorganisms and their metabolites were applied into the fermentation of tobacco leaves in order to improve the tobacco quality. The results showed that a variety of aromatic substances in Moutai, as well as the typical flavor substances commonly used in cigarettes, were detected in the fermented tobacco leaf extract. In view of the GC-MS results as well as the sensory smoking evaluation of tobacco leaf extracts under designed experimental conditions, the optimal parameters of stable single-strain fermentation process was at 40 ℃ for 10-15 days. The results of specific effects of different fermentation conditions on the content of aroma substances in different parts of tobacco leaves after fermentation, as well as the subsequent sensory evaluation, provided basic data for the improvement of tobacco fermentation and aroma flavoring technology, which was conducive to the development of new cigarettes

Cigarette Flavouring Regulation by Using Aroma-producing Microorganism Isolated from Maotai Daqu

The selected Moutai aromatic microorganisms and their metabolites were applied into the fermentation of tobacco leaves in order to improve the tobacco quality. The results showed that a variety of aromatic substances in Moutai, as well as the typical flavor substances commonly used in cigarettes, were detected in the fermented tobacco leaf extract. In view of the GC-MS results as well as the sensory smoking evaluation of tobacco leaf extracts under designed experimental conditions, the optimal parameters of stable single-strain fermentation process was at 40 ℃ for 10-15 days. The results of specific effects of different fermentation conditions on the content of aroma substances in different parts of tobacco leaves after fermentation, as well as the subsequent sensory evaluation, provided basic data for the improvement of tobacco fermentation and aroma flavoring technology, which was conducive to the development of new cigarettes