Fresh Meat Classification Using Laser-Induced Breakdown Spectroscopy Assisted by LightGBM and Optuna.

To enhance the accuracy of identifying fresh meat varieties using laser-induced breakdown spectroscopy (LIBS), we utilized the LightGBM model in combination with the Optuna algorithm. The procedure involved flattening fresh meat slices with glass slides and collecting spectral data of the plasma from the surfaces of the fresh meat tissues (pork, beef, and chicken) using LIBS technology. A total of 900 spectra were collected. Initially, we established LightGBM and SVM (support vector machine) models for the collected spectra. Subsequently, we applied information gain and peak extraction algorithms to select the features for each model. We then employed Optuna to optimize the hyperparameters of the LightGBM model, while a 10-fold cross-validation was conducted to determine the optimal parameters for SVM. Ultimately, the LightGBM model achieved higher accuracy, macro-F1, and Cohen's kappa coefficient (kappa coefficient) values of 0.9370, 0.9364, and 0.9244, respectively, compared to the SVM model's values of 0.8888, 0.8881, and 0.8666. This study provides a novel method for the rapid classification of fresh meat varieties using LIBS.

FPGA-based CCD signal acquisition and transmission system design.

In order to facilitate the analysis and processing of optical signals, an FPGA-based CCD signal acquisition and data transmission system is designed in this work. The system uses an FPGA as the main control device, the TCD1304DG/AP chip as the optical signal detector, and the CYUSB3KIT-003 development board product by Cypress for data transmission. Verilog and Python languages are employed for modular design and on-board verification. Through the coordination of each module, the system successfully achieves CCD signal data acquisition and transmission.

Community structure, distribution pattern, and influencing factors of soil Archaea in the construction area of a large-scale photovoltaic power station / Estructura de la comunidad, patrón de distribución y factores influyentes del suelo Archaea en el área de construcción de una central fotovoltaica a gran escala

The photovoltaic power station in Qinghai has been built for 8 years; however, its impact on the regional soil ecological environment has not been studied in depth. To reveal the structure and distribution pattern of archaeal communities in desert soil under the influence of a large photovoltaic power station, a comparative study was carried out between the soil affected by photovoltaic panels and the bare land samples outside the photovoltaic station in Gonghe, Qinghai Province. The abundance, community structure, diversity, and distribution characteristics of archaea were analyzed by quantitative PCR and Illumina-MiSeq high-throughput sequencing, and the main environmental factors affecting the variation in soil archaeal community were identified by RDA. The contribution rate of environmental factors and human factors to microbial community diversity was quantitatively evaluated by VPA. The results showed that there was no significant difference in soil nutrients and other physicochemical factors between the photovoltaic power station and bare land. Thaumarchaeota was the dominant archaeal phylum in the area, accounting for more than 99% of archaeal phylum, while at the level of genus, Nitrososphaera was the dominant archaeal genera. There was no significant difference in archaeal community structure between and under different types of PV panels. The analysis has shown that the construction of a photovoltaic station has little effect on the community structure of soil archaea in a desert area, and it was speculated that the selection of niche played a leading role in the distribution pattern of soil archaeal community. This study provides the basis for a scientific understanding of the characteristics and distribution patterns of soil archaeal communities affected by the construction of a photovoltaic power station.(AU)

Community structure, distribution pattern, and influencing factors of soil Archaea in the construction area of a large-scale photovoltaic power station.

The photovoltaic power station in Qinghai has been built for 8 years; however, its impact on the regional soil ecological environment has not been studied in depth. To reveal the structure and distribution pattern of archaeal communities in desert soil under the influence of a large photovoltaic power station, a comparative study was carried out between the soil affected by photovoltaic panels and the bare land samples outside the photovoltaic station in Gonghe, Qinghai Province. The abundance, community structure, diversity, and distribution characteristics of archaea were analyzed by quantitative PCR and Illumina-MiSeq high-throughput sequencing, and the main environmental factors affecting the variation in soil archaeal community were identified by RDA. The contribution rate of environmental factors and human factors to microbial community diversity was quantitatively evaluated by VPA. The results showed that there was no significant difference in soil nutrients and other physicochemical factors between the photovoltaic power station and bare land. Thaumarchaeota was the dominant archaeal phylum in the area, accounting for more than 99% of archaeal phylum, while at the level of genus, Nitrososphaera was the dominant archaeal genera. There was no significant difference in archaeal community structure between and under different types of PV panels. The analysis has shown that the construction of a photovoltaic station has little effect on the community structure of soil archaea in a desert area, and it was speculated that the selection of niche played a leading role in the distribution pattern of soil archaeal community. This study provides the basis for a scientific understanding of the characteristics and distribution patterns of soil archaeal communities affected by the construction of a photovoltaic power station.

Effects of photovoltaic panels on soil temperature and moisture in desert areas.

Photovoltaic power generation is an important clean energy alternative to fossil fuels. To reduce CO2 emissions, the Chinese government has ordered the construction of a large number of photovoltaic (PV) panels to generate power in the past two decades; many are located in desert areas because of the sufficient light conditions. Large-scale PV construction in desert areas can alter the local microclimate and soil conditions, thereby affecting the growth of vegetation. However, few studies have focused on the effects of PV panels on the environment of desert areas. In this study, we investigated the effects of PV panels on soil moisture and temperature via a whole-year field experiment at a PV power plant in a desert area in western China. The in situ soil moisture and temperature at a depth of 0-0.4 m were measured under three types of PV shading conditions: shaded by fixed-tilt (FIX) PV panels, shaded by oblique single-axis (OSA) PV panels, and no shading. The results showed that the soil temperature and moisture at sites under PV shading were significantly affected compared with those at sites without shading. PV panels increased the average soil temperature during winter but decreased it during the other three seasons. Moreover, the warming effect of FIX PV panels on the soil is more apparent than that of OSA PV panels. PV panels have positive effects on soil moisture. Compared with that at the sites without shaded areas, the average soil moisture under the FIX PV panels and under the OSA PV panels increased by 14.7% and by 11.1%, respectively. These data provide support for future studies on vegetation restoration around PV power plants in desert areas.