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Fast and accurate identification of soybean varieties is important for determining seed quality, protecting the interests of soybean growers and ensuring food safety. A combination of Raman spectroscopy with chemometric methods has been widely applied in the identification of agricultural products such as grains, fruit, edible oils, and honey; however, the identification methods of soybean varieties mainly focuses on infrared spectroscopy and hyperspectral imagery. Therefore, a partial least squares (PLS) identification model was established by Raman spectroscopy combined with characteristic wavenumber extraction method to rapidly identify four high-protein soybean varieties (Heinong 88, Heinong 98, Suinong 71, and Suinong 76) that are extensively planted in Heilongjiang Province, China. Owing to the high-dimensional and high correlation data obtained from Raman spectroscopy, a full-spectrum prediction mode will lead to high complexity and poor stability. Therefore, first, the optimal combinations of spectral subintervals were selected by backward interval PLS (BIPLS) and synergy interval PLS (SIPLS); however, redundant variables still existed in the selected continuous band and strong collinearity was observed between adjacent wavenumbers. Consequently, ElasticNet was used to re-filter the characteristic spectral regions of BIPLS and SIPLS, which effectively reduced the collinearity between the selected wavenumbers. The performance of different algorithms, i.e., full-spectrum and five characteristic wavenumber selection algorithms—BIPLS, SIPLS, ElasticNet, BIPLS-ElasticNet, and SIPLS-ElasticNet —were compared. In the BIPLS-ElasticNet algorithm, 1113 effective wavenumbers were extracted, which accounted for approximately 35% of the total wavenumbers. Moreover, the values of root mean square error, determination coefficient, and identification accuracy of the prediction set were determined to be 0.2298,0.9568 and 100%, respectively. Therefore, the proposed BIPLS-ElasticNet demonstrated the best performance among the PLS models and can be used for the fast and accurate identification of soybean varieties; moreover, it can also provide a reference for the rapid identification of other crop seeds. [ABSTRACT FROM AUTHOR]

Although crop rotations have been widely shown as an effective approach for improving yield or soil quality in the long term, the relationship between crop rotations and quality traits of crop or biochar-based fertilization is still unclear. To address this, we conducted a long-term field experiment in the Heilongjiang province of China to investigate the effects of crop rotation and biochar-based fertilizer application on the crop yield, soil parameters, crop quality, and agronomic traits in 2014–2020. The effects of rotations on crop production and soil properties were evaluated with the average yield variability during the 7 years of this study. Our results showed that the diversified corn and soybean rotations had a significant positive effect on average crop yield compared with their monocultures. The corn yield was enhanced by 0.6 Mg ha−1 (5.4%) in the corn–soybean–corn (CSC) crop sequence compared with monoculture corn. Similarly, soybean yield was enhanced by 0.21 Mg ha−1 (9.7%) in the soybean–corn–corn (SCC) crop sequence compared with monoculture soybean. However, a negative effect of crop rotations was detected on the protein content of soybean compared with the monoculture soybean, while a positive effect was detected on oil content. Additionally, no differences were detected in crop yield between biochar-based fertilization and mineral fertilization treatments, but a significant positive effect of biochar-based fertilization was observed for any crop on both protein and oil content. A significant effect of crop rotation was found on the percentage of total soil N (TN), available soil N (AN), and available soil K (AK) content. The SSS crop sequence treatment illustrated the highest TN values at 0.18%. The CCC crop sequence treatment increased AN and AK content by 9.1% and 7.8%, respectively, compared with SSS (p < 0.05). We conclude that crop rotations increase crop yield and biochar-based fertilizer application, improving crop quality traits in the long term. Thus, the addition of biochar-based fertilizer could efficiently enhance the yield and quality of crop in the rotation cropping system. The findings of this study may provide useful information for designing sustainable cropping systems based on rotations. [ABSTRACT FROM AUTHOR]