RESUMO
Mapping soil properties in sub-watersheds is critical for agricultural productivity, land management, and ecological security. Machine learning has been widely applied to digital soil mapping due to a rapidly increasing number of environmental covariates. However, the inclusion of many environmental covariates in machine learning models leads to the problem of multicollinearity, with poorly understood consequences for prediction performance. Here, we explored the effects of variable selection on the prediction performance of two machine learning models for multiple soil properties in the Haihun River sub-watershed, Jiangxi Province, China. Surface soils (0-20 cm) were collected from a total of 180 sample points in 2022. The optimal covariates were selected from 40 environmental covariates using a recursive feature elimination algorithm. Compared to all-variable models, the random forest (RF) and extreme gradient boosting (XGBoost) models with variable selection improved in prediction accuracy. The R2 values of the RF and XGBoost models increased by 0.34 and 0.47 for the soil organic carbon, by 0.67 and 0.62 for the total phosphorus, and by 0.43 and 0.62 for the available phosphorus, respectively. The models with variable selection presented reduced global uncertainty, and the overall uncertainty of the RF model was lower than that of the XGBoost model. The soil properties showed high spatial heterogeneity based on the models with variable selection. Remote sensing covariates (particularly principal component 2) were the major factors controlling the distribution of the soil organic carbon. Human activity covariates (mainly land use) and organism covariates (mainly potential evapotranspiration) played a predominant role in driving the distribution of the soil total and soil available phosphorus, respectively. This study indicates the importance of variable selection for predicting multiple soil properties and mapping their spatial distribution in sub-watersheds.
RESUMO
OBJECTIVE: To explore the effect of Wenjing Decoction and Tiaobu Chongren acupuncture and moxibustion therapy on serum sex hormones and ovarian function recovery in premature ovarian failure (POF) patients with deficiency-cold syndrome. METHODS: From February 2018 to October 2019, 119 POI patients with deficiency-cold syndrome who met the selection criteria were randomly divided into the control group (n = 59) and the observation group (n = 60). The control group was treated with hormone replacement therapy, and the observation group was treated with Wenjing Decoction and Tiaobu Chongren acupuncture and moxibustion therapy on the basis of the control group. Both groups were treated continuously for 3 months. After treatment, the clinical efficacy of the two groups was compared, the Chinese medicine syndrome score, serum estradiol (E 2), follicle-stimulating hormone (FSH), luteinizing hormone (LH), anti-mullerian hormone (AMH) and bilateral antral follicle count (AFC), mean ovarian volume, and endometrial thickness of the two groups before and after treatment were compared. RESULT: The effective rate of the observation group (93.10%) was higher than that of the control group (77.59%) (P < 0.05). After treatment, the index scores of traditional Chinese medicine syndromes in two groups were lower than before (P < 0.05), and the observation group was lower than the control group (P < 0.05). The serum E 2 and AMH levels in the two groups increased, while FSH and LH levels decreased compared with before treatment, and the observation group improved significantly compared with the control group (P < 0.05). The bilateral AFC, mean ovarian volume, and endometrial thickness of the two groups increased compared with before treatment, and the observation group was higher than the control group (P < 0.05). CONCLUSION: On the basis of hormone replacement therapy, the combination of Wenjing Decoction and Tiaobu Chongren acupuncture and moxibustion therapy is effective in treating POF patients with deficiency-cold syndrome, which can effectively regulate their serum sex hormone levels and promote the recovery of ovarian function.