Recent advance in the valorization of soy-based by-products: Extraction, modification, interaction and applications in the food industry

Huang, Lihua; Cai, Yongjian; Fang, Fang; Huang, Tongwen; Zhao, Mouming; Zhao, Qiangzhong; Van der Meeren, Paul

doi:10.1016/j.foodhyd.2024.110407

Cited by 3 publications

References 104 publications

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The characterization of size-controlled nanocrystalline cellulose from soy hulls with ultrasonic assisted extraction

Yu,

Yang,

Zhang

et al. 2024

Preprint

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Soybean is a crop of important economic significance and soy hull is the residual by-product of soybean processing industry. In this study, cellulose nanocrystals were extracted from soy hull using a combined acid hydrolysis-ultrasonic treatment process, and its structure, properties, and antimicrobial activity were investigated. Fourier-transform infrared spectroscopy revealed the presence of hydrogen and ester bonds in the soy hull nanocrystalline cellulose (SHNC), whereas scanning electron microscopy showed that the SHNC was globular or short-rod shaped with diameters in the range of 20–50 nm. The molecular weight of SHNC was 213,935 Da and the extraction yield was 11.42%. Meanwhile, SHNC also had high crystallinity (55.59%), thermal stability, transparency (80%), and UV resistance. Notably, SHNC exhibited an excellent bacteriostatic effect against Escherichia coli and Staphylococcus aureus, whose bacteriostatic percentage reached 69.33%. Meanwhile, this study provided a new idea for the high value utilization of waste soy hull.

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The characterization of size-controlled nanocrystalline cellulose from soy hulls with ultrasonic assisted extraction

Yu,

Yang,

Zhang

et al. 2024

Preprint

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Planting Density and Sowing Date Strongly Influence Canopy Characteristics and Seed Yield of Soybean in Southern Xinjiang

Xu,

Mao,

Zhang

et al. 2024

Agriculture

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Southern Xinjiang is an important soybean production region in China. However, the short growing season and the cultivation of winter crops (such as wheat) in the region limit the expansion of soybean planting areas. An increased planting density can compensate for the loss in yield due to delayed sowing. To identify the quantitative relationship between increased density and delayed days, a two-year field experiment was conducted at the Tarim University Agronomy Experiment Station. Two sowing dates (April 7 (S1) and May 7 (S2)) and three planting densities of 206,800 plants·ha−1 (D1), 308,600 plants·ha−1 (D2), and 510,200 plants·ha−1 (D3) were used to compare various plant growth parameters and canopy characteristics. Late sowing and a high planting density significantly increased the plant height (S2 was 37.3% higher than S1, and D3 was 17.6% and 8.8% higher than D1 and D2), main stem internode, petiole length, and the mean tilt angle of the leaves (S2 was 22.5% higher than S1, and D3 was 11.7% higher than D2) but reduced the stem diameter (D3 was 28.6% and 12.5% lower than D1 and D2), branch number (S2 was 26.7% lower than S1, and D2 was 75% lower than D1), canopy light transmittance (S2 was 49.2% lower than S1, and D3 was 36.7% and 20.8% lower than D1 and D2), photosynthetic rate, and dry matter. The highest yield was achieved at S1D1, but the lowest yield was found for S2D1. Overall, the results suggest that earlier sowing and a lower planting density contribute to achieving an optimum canopy structure and higher yield. Our conclusions provide a reference for soybean production in southern Xinjiang.

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Monitoring Soybean Soil Moisture Content Based on UAV Multispectral and Thermal-Infrared Remote-Sensing Information Fusion

Shi,

Liu,

et al. 2024

Plants

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By integrating the thermal characteristics from thermal-infrared remote sensing with the physiological and structural information of vegetation revealed by multispectral remote sensing, a more comprehensive assessment of the crop soil-moisture-status response can be achieved. In this study, multispectral and thermal-infrared remote-sensing data, along with soil-moisture-content (SMC) samples (0~20 cm, 20~40 cm, and 40~60 cm soil layers), were collected during the flowering stage of soybean. Data sources included vegetation indices, texture features, texture indices, and thermal-infrared vegetation indices. Spectral parameters with a significant correlation level (p < 0.01) were selected and input into the model as single- and fuse-input variables. Three machine learning methods, eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Genetic Algorithm-optimized Backpropagation Neural Network (GA-BP), were utilized to construct prediction models for soybean SMC based on the fusion of UAV multispectral and thermal-infrared remote-sensing information. The results indicated that among the single-input variables, the vegetation indices (VIs) derived from multispectral sensors had the optimal accuracy for monitoring SMC in different soil layers under soybean cultivation. The prediction accuracy was the lowest when using single-texture information, while the combination of texture feature values into new texture indices significantly improved the performance of estimating SMC. The fusion of vegetation indices (VIs), texture indices (TIs), and thermal-infrared vegetation indices (TVIs) provided a better prediction of soybean SMC. The optimal prediction model for SMC in different soil layers under soybean cultivation was constructed based on the input combination of VIs + TIs + TVIs, and XGBoost was identified as the preferred method for soybean SMC monitoring and modeling, with its R2 = 0.780, RMSE = 0.437%, and MRE = 1.667% in predicting 0~20 cm SMC. In summary, the fusion of UAV multispectral and thermal-infrared remote-sensing information has good application value in predicting SMC in different soil layers under soybean cultivation. This study can provide technical support for precise management of soybean soil moisture status using the UAV platform.

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Recent advance in the valorization of soy-based by-products: Extraction, modification, interaction and applications in the food industry

Cited by 3 publications

References 104 publications

The characterization of size-controlled nanocrystalline cellulose from soy hulls with ultrasonic assisted extraction

The characterization of size-controlled nanocrystalline cellulose from soy hulls with ultrasonic assisted extraction

Planting Density and Sowing Date Strongly Influence Canopy Characteristics and Seed Yield of Soybean in Southern Xinjiang

Monitoring Soybean Soil Moisture Content Based on UAV Multispectral and Thermal-Infrared Remote-Sensing Information Fusion

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