Improving the accuracy of cotton seedling emergence rate estimation by fusing UAV-based multispectral vegetation indices.

Timely and accurate estimation of cotton seedling emergence rate is of great significance to cotton production. This study explored the feasibility of drone-based remote sensing in monitoring cotton seedling emergence. The visible and multispectral images of cotton seedlings with 2 - 4 leaves in 30 plots were synchronously obtained by drones. The acquired images included cotton seedlings, bare soil, mulching films, and PE drip tapes. After constructing 17 visible VIs and 14 multispectral VIs, three strategies were used to separate cotton seedlings from the images: (1) Otsu's thresholding was performed on each vegetation index (VI); (2) Key VIs were extracted based on results of (1), and the Otsu-intersection method and three machine learning methods were used to classify cotton seedlings, bare soil, mulching films, and PE drip tapes in the images; (3) Machine learning models were constructed using all VIs and validated. Finally, the models constructed based on two modeling strategies [Otsu-intersection (OI) and machine learning (Support Vector Machine (SVM), Random Forest (RF), and K-nearest neighbor (KNN)] showed a higher accuracy. Therefore, these models were selected to estimate cotton seedling emergence rate, and the estimates were compared with the manually measured emergence rate. The results showed that multispectral VIs, especially NDVI, RVI, SAVI, EVI2, OSAVI, and MCARI, had higher crop seedling extraction accuracy than visible VIs. After fusing all VIs or key VIs extracted based on Otsu's thresholding, the binary image purity was greatly improved. Among the fusion methods, the Key VIs-OI and All VIs-KNN methods yielded less noises and small errors, with a RMSE (root mean squared error) as low as 2.69% and a MAE (mean absolute error) as low as 2.15%. Therefore, fusing multiple VIs can increase crop image segmentation accuracy. This study provides a new method for rapidly monitoring crop seedling emergence rate in the field, which is of great significance for the development of modern agriculture.

Improving the estimation accuracy of rapeseed leaf photosynthetic characteristics under salinity stress using continuous wavelet transform and successive projections algorithm.

Soil salinization greatly restricts crop production in arid areas for salinity stress can inhibit crop photosynthesis and growth. Chlorophyll fluorescence and photosynthetic gas exchange (CFPGE) parameters are important indicators of crop photosynthesis and have been widely used to evaluate the impacts of salinity stress on crop photosynthesis and growth. Remote sensing technology can quickly and non-destructively obtain crop information under salinity stress, however, at present, the distribution of spectral features of CFPGE parameters in different regions is still unclear. In this study (2019-2020), under salinity stress conditions, the spectral data of rapeseed leaves were acquired and the CFPGE parameters were simultaneously determined. Then, continuous wavelet transformation (CWT) and standard normal variate (SNV) transformation were utilized to preprocess the raw spectral data. After that, a CFPGE parameter estimation model was constructed by using the partial least squares regression (PLSR) algorithm and the support vector machines (SVM) algorithm based on the spectral features in the red region (600-800 nm) and those in the red, blue-green (350-600 nm), and near-infrared (800-2500 nm) regions. The results showed that the spectral features of CFPGE parameters could be extracted by successive projections algorithm (SPA) based on the CWT preprocessing. The CFPGE parameter estimation model constructed based on the spectral features in the red region (675 nm, 680 nm, 688 nm, 749 nm, and 782 nm) had the highest Fv/Fm estimation accuracy on day 30, with R2c, R2p, and RPD of 0.723, 0.585, and 1.68, respectively. Based on this, the spectral features (578 nm, 976 nm, 1088 nm, 1476 nm, and 2250 nm) in the blue-green and near-infrared regions were added in the variables for modeling, which significantly improved the accuracy and stability of the model, with R2c, R2p, and RPD of 0.886, 0.815, and 2.58, respectively. Therefore, the fusion of the spectral features in the red, blue-green, and near-infrared regions could improve the estimation accuracy of rapeseed leaf CFPGE parameters. This study will provide technical reference for rapid estimation of photosynthetic performance of crops under salinity stress in arid and semi-arid areas.

Improving the ability of straw biochar to remediate Cd contaminated soil: KOH enhanced the modification of K3PO4 and urea on biochar.

In recent years, the improvement of soil cadmium (Cd) contamination remediation effect of biochar by modification has received wide attention. However, the effect of combined modification on biochar performance in soil Cd contamination remediation and the mechanism are still unclear. In this study, cotton straw biochar and maize straw biochar were co-modified by KOH (0, 3, 5 mol L-1), K3PO4, and urea. Then, two modified biochars with high Cd adsorption capacity were selected to test the soil Cd contamination remediation effect through a pot experiment. The results showed that the combined modification by using KOH, K3PO4, and urea significantly increased the specific surface area and nitrogen (N) and phosphorus (P) contents of biochar, providing more adsorption sites for Cd. Among the modified biochar, the cotton straw biochar modified with KOH (3 mol L-1), K3PO4, and urea (m3-CSB) had the highest adsorption capacity (111.25 mg g-1), which was 7.86 times that of cotton straw biochar (CSB). The m3-CSB for adsorption isotherm and kinetics of Cd conformed to the Langmuir model and Pseudo-second-order kinetic equation, respectively. In the pot experiment, under different exogenous Cd levels (0 (Cd0), 4 (Cd4), and 8 (Cd8) mg kg-1), m3-CSB treatment decreased soil available Cd content the most (51.68%-63.4%) compared with other biochar treatments. Besides, m3-CSB treatment significantly promoted the transformation of acid-soluble Cd to reducible, oxidizable, and residual Cd, reducing the bioavailability of Cd. At the Cd4 level, the application of m3-CSB significantly reduced cotton Cd uptake compared to CK, and the maximum reduction of Cd content in cotton fibers was as high as 81.95%. Therefore, cotton straw biochar modified with KOH (3 mol L-1), K3PO4, and urea has great potential in the remediation of soil Cd contamination.

Improving the monitoring of root zone soil salinity under vegetation cover conditions by combining canopy spectral information and crop growth parameters.

Soil salinization is one of the main causes of land degradation in arid and semi-arid areas. Timely and accurate monitoring of soil salinity in different areas is a prerequisite for amelioration. Hyperspectral technology has been widely used in soil salinity monitoring due to its high efficiency and rapidity. However, vegetation cover is an inevitable interference in the direct acquisition of soil spectra during crop growth period, which greatly limits the monitoring of soil salinity by remote sensing. Due to high soil salinity could lead to difficulty in plants' water absorption, and inhibit plant dry matter accumulation, a method for monitoring root zone soil salinity by combining vegetation canopy spectral information and crop aboveground growth parameters was proposed in this study. The canopy spectral information was acquired by a spectroradiometer, and then variable importance in projection (VIP), competitive adaptive reweighted sampling (CARS), and random frog algorithm (RFA) were used to extract the salinity spectral features in cotton canopy spectrum. The extracted features were then used to estimate root zone soil salinity in cotton field by combining with cotton plant height, aboveground biomass, and shoot water content. The results showed that there was a negative correlation between plant height/aboveground biomass/shoot water content and soil salinity in 0-20, 0-40, and 0-60 cm soil layers at different growth stages of cotton. Spectral feature selection by the three methods all improved the prediction accuracy of soil salinity, especially CARS. The prediction accuracy based on the combination of spectral features and cotton growth parameters was significantly higher than that based on only spectral features, with R2 increasing by 10.01%, 18.35%, and 29.90% for the 0-20, 0-40, and 0-60 cm soil layer, respectively. The model constructed based on the first derivative spectral preprocessing, spectral feature selection by CARS, cotton plant height, and shoot water content had the highest accuracy for each soil layer, with R2 of 0.715,0.769, and 0.742 for the 0-20, 0-40, 0-60 cm soil layer, respectively. Therefore, the method by combining cotton canopy hyperspectral data and plant growth parameters could significantly improve the prediction accuracy of root zone soil salinity under vegetation cover conditions. This is of great significance for the amelioration of saline soil in salinized farmlands arid areas.

Cotton straw biochar and compound Bacillus biofertilizer reduce Cd stress on cotton root growth by regulating root exudates and antioxidant enzymes system.

Introduction: Cotton straw biochar (biochar) and compound Bacillus biofertilizer (biofertilizer) have attracted wide attentions in the remediation of heavy metal-contaminated soils in recent years. However, few studies have explored the metabolomics of lateral roots of Cd-stressed cotton to determine the mechanism of biochar and biofertilizer alleviating Cd stress. Methods: In this pot experiment, biochar and biofertilizer were applied to the soils with different Cd contamination levels (1, 2, and 4 mg kg-1). Then, the responses of cotton root morphology, vitality, Cd content, and antioxidant enzyme activities were analyzed, and the mechanism of biochar and biofertilizer alleviating Cd stress was determined by metabolomic analysis. Results: The results showed that exogenous Cd addition decreased the SOD and POD activities in cotton taproot and lateral root. Besides, with the increase of soil Cd content, the maximum Cd content in taproot (0.0250 mg kg-1) and lateral root (0.0288 mg kg-1) increased by 89.11% and 33.95%, respectively compared with those in the control (p< 0.05). After the application of biochar and biofertilizer, the SOD and POD activities in cotton taproot and lateral root increased. The Cd content of cotton taproot in biochar and biofertilizer treatments decreased by 16.36% and 19.73%, respectively, and that of lateral root decreased by 13.99% and 16.68%, respectively. The metabolomic analysis results showed that the application of biochar and biofertilizer could improve the resistance of cotton root to Cd stress through regulating the pathways of ABC transporters and phenylalanine metabolism. Discussion: Therefore, the application of biochar and biofertilizer could improve cotton resistance to Cd stress by increasing antioxidant enzyme activities, regulating root metabolites (phenols and amino acids), and reducing Cd content, thus promoting cotton root growth.

Nitrogen application alleviates salt stress by enhancing osmotic balance, ROS scavenging, and photosynthesis of rapeseed seedlings (Brassica napus).

Nitrogen application could alleviate salt stress on crops, but the specific physiological mechanism is still unclear. Therefore, in this study, a pot experiment was conducted to explore the effects of different application rates of nitrogen (0, 0.15, 0.30, and 0.45 g·kg-1) on the growth parameters, osmotic adjustment, reactive oxygen species scavenging, and photosynthesis of rapeseed seedlings planted in the soils with different concentrations of sodium chloride (1.5, 3.5, 5.5, and 7.5 g·kg-1). The results showed that nitrogen could alleviate the inhibition of salt on rapeseed growth, and improve the antioxidant enzyme activities and the contents of non-enzymatic substances, K+, soluble protein (SP), soluble sugar (SS), and proline. Besides, there was a significant correlation between the indexes of active oxygen scavenging system, osmoregulation system, and photosynthesis. Therefore, applying appropriate amount of nitrogen can promote the growth and development of rapeseed seedlings under salt stress, accelerate the scavenging of reactive oxygen species, maintain osmotic balance, and promote photosynthesis. This study will improve our understanding on the mechanism by which nitrogen application alleviates salt stress to crops.

Application of cotton straw biochar and compound Bacillus biofertilizer decrease the bioavailability of soil cd through impacting soil bacteria.

BACKGROUND: Cd seriously threatens soil environment, remedying Cd in farmland and clearing the response of soil environment to modifiers in Cd-contaminated soils is necessary. In this study, the effects of cotton straw biochar and compound Bacillus biofertilizer used as modifiers on the biochemical properties, enzyme activity, and microbial diversity in Cd-contaminated soils (1, 2, and 4 mg·kg-1) were investigated. RESULTS: The results showed that both cotton straw biochar and compound Bacillus biofertilizer could improve the soil chemical characteristics, including the increase of soil C/N ratio, electrical conductance (EC) and pH, and the most important decrease of soil available Cd content by 60.24% and 74.34%, respectively (P < 0.05). On the other hand, adding cotton straw biochar and compound Bacillus biofertilizer in Cd stressed soil also improved soil biological characteristics. Among them, cotton straw biochar mainly through increasing soil alkaline phosphatase activity and improve bacteria abundance, compound Bacillus biofertilizer by increasing soil invertase, alkaline phosphatase, catalase, and urease activity increased bacterial community diversity. On the whole, the decrease of soil available Cd was mainly caused by the increase of soil pH, C/N, urease and alkaline phosphatase activities, and the relative abundance of Acidobacteria and Proteobacteria. CONCLUSIONS: In summary, the applications of cotton straw biochar and compound Bacillus biofertilizer could decrease soil available Cd concentration, increase soil bacterial community diversity and functions metabolism, and reduce the damage of Cd stress, compared with cotton straw biochar, compound Bacillus biofertilizer was more effective in immobilizing Cd and improving soil environmental quality.