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Xiao M, Wang T, Tang C, He M, Li Y, Li X. Effects of Drying Methods on Morphological Characteristics, Metabolite Content, and Antioxidant Capacity of Cordyceps sinensis. Foods 2024; 13:1639. [PMID: 38890867 PMCID: PMC11171906 DOI: 10.3390/foods13111639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 05/15/2024] [Accepted: 05/18/2024] [Indexed: 06/20/2024] Open
Abstract
Cordyceps sinensis is a rare and endangered medicinal herb in China and a typical medicinal and food plant. Most of the research related to Cordyceps sinensis focuses on its pharmacological effects, artificial cultivation and clinical applications. However, there are few comprehensive evaluations on the quality of Cordyceps sinensis under different drying methods. In this study, the effects of vacuum freeze-drying (DG), oven-drying (HG) and air-drying (YG) on the morphological characteristics, microstructure, antioxidant activity and metabolites of Cordyceps sinensis were investigated using wild Cordyceps sinensis as the research object. The results showed that in their appearance and morphology, the YG- and HG-method Cordyceps sinensis samples were darker in color and wilted, while the DG- method Cordyceps sinensis samples were golden yellow in color and had better fullness. In terms of microstructure, the stomata of the YG and HG method Cordyceps sinensis samples were relatively small and irregularly shaped, whereas those of the DG method Cordyceps sinensis samples were larger and neat. In terms of antioxidant capacity, the HG-method samples were the lowest, followed by the YG group, and the DG group had the highest total antioxidant capacity. A correlation analysis revealed a significant relationship between antioxidant capacity and lipids, lipid molecules, nucleosides, nucleotides, and analogs. A metabolomics analysis identified 1937 metabolites from 18 superclasses, with lipids, lipid-like molecules, organic acids and derivatives, organoheterocyclic compounds, and organic oxygen compounds being the predominant metabolites in Cordyceps sinensis. Differentially accumulated metabolites (DAMs) in DG samples showed higher levels of lipids and lipid molecules, organic oxygen compounds, organic acids and derivatives, and organoheterocyclic compounds compared to the other drying methods, suggesting DG as the optimal preservation method for Cordyceps sinensis. These findings offer insights for selecting appropriate drying methods and maintaining the post-drying quality of Cordyceps sinensis.
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Affiliation(s)
| | | | | | | | - Yuling Li
- State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China; (M.X.); (T.W.); (C.T.); (M.H.); (X.L.)
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Yang T, Zheng X, Xiao H, Shan C, Zhang J. Moisture content online detection system based on multi-sensor fusion and convolutional neural network. FRONTIERS IN PLANT SCIENCE 2024; 15:1289783. [PMID: 38501134 PMCID: PMC10944943 DOI: 10.3389/fpls.2024.1289783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 02/15/2024] [Indexed: 03/20/2024]
Abstract
To monitor the moisture content of agricultural products in the drying process in real time, this study applied a model combining multi-sensor fusion and convolutional neural network (CNN) to moisture content online detection. This study built a multi-sensor data acquisition platform and established a CNN prediction model with the raw monitoring data of load sensor, air velocity sensor, temperature sensor, and the tray position as input and the weight of the material as output. The model's predictive performance was compared with that of the linear partial least squares regression (PLSR) and nonlinear support vector machine (SVM) models. A moisture content online detection system was established based on this model. Results of the model performance comparison showed that the CNN prediction model had the optimal prediction effect, with the determination coefficient (R2) and root mean square error (RMSE) of 0.9989 and 6.9, respectively, which were significantly better than those of the other two models. Results of validation experiments showed that the detection system met the requirements of moisture content online detection in the drying process of agricultural products. The R2 and RMSE were 0.9901 and 1.47, respectively, indicating the good performance of the model combining multi-sensor fusion and CNN in moisture content online detection for agricultural products in the drying process. The moisture content online detection system established in this study is of great significance for researching new drying processes and realizing the intelligent development of drying equipment. It also provides a reference for online detection of other indexes in the drying process of agricultural products.
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Affiliation(s)
- Taoqing Yang
- College of Mechanical and Electrical Engineering, Shihezi University, Shihezi, China
- Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi, China
- Key Laboratory of Modern Agricultural Machinery Corps, Shihezi, China
| | - Xia Zheng
- College of Mechanical and Electrical Engineering, Shihezi University, Shihezi, China
- Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi, China
- Key Laboratory of Modern Agricultural Machinery Corps, Shihezi, China
| | - Hongwei Xiao
- College of Engineering, China Agricultural University, Beijing, China
| | - Chunhui Shan
- College of Food, Shihezi University, Shihezi, China
| | - Jikai Zhang
- College of Mechanical and Electrical Engineering, Shihezi University, Shihezi, China
- Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi, China
- Key Laboratory of Modern Agricultural Machinery Corps, Shihezi, China
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Zhang J, Zheng X, Xiao H, Shan C, Li Y, Yang T. Quality and Process Optimization of Infrared Combined Hot Air Drying of Yam Slices Based on BP Neural Network and Gray Wolf Algorithm. Foods 2024; 13:434. [PMID: 38338569 PMCID: PMC10855503 DOI: 10.3390/foods13030434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 01/09/2024] [Accepted: 01/18/2024] [Indexed: 02/12/2024] Open
Abstract
In this paper, the effects on drying time (Y1), the color difference (Y2), unit energy consumption (Y3), polysaccharide content (Y4), rehydration ratio (Y5), and allantoin content (Y6) of yam slices were investigated under different drying temperatures (50-70 °C), slice thicknesses (2-10 mm), and radiation distances (80-160 mm). The optimal drying conditions were determined by applying the BP neural network wolf algorithm (GWO) model based on response surface methodology (RMS). All the above indices were significantly affected by drying conditions (p < 0.05). The drying rate and effective water diffusion coefficient of yam slices accelerated with increasing temperature and decreasing slice thickness and radiation distance. The selection of lower temperature and slice thickness helped reduce the energy consumption and color difference. The polysaccharide content increased and then decreased with drying temperature, slice thickness, and radiation distance, and it was highest at 60 °C, 6 mm, and 120 mm. At 60 °C, lower slice thickness and radiation distance favored the retention of allantoin content. Under the given constraints (minimization of drying time, unit energy consumption, color difference, and maximization of rehydration ratio, polysaccharide content, and allantoin content), BP-GWO was found to have higher coefficients of determination (R2 = 0.9919 to 0.9983) and lower RMSEs (reduced by 61.34% to 80.03%) than RMS. Multi-objective optimization of BP-GWO was carried out to obtain the optimal drying conditions, as follows: temperature 63.57 °C, slice thickness 4.27 mm, radiation distance 91.39 mm, corresponding to the optimal indices, as follows: Y1 = 133.71 min, Y2 = 7.26, Y3 = 8.54 kJ·h·kg-1, Y4 = 20.73 mg/g, Y5 = 2.84 kg/kg, and Y6 = 3.69 μg/g. In the experimental verification of the prediction results, the relative error between the actual and predicted values was less than 5%, proving the model's reliability for other materials in the drying technology process research to provide a reference.
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Affiliation(s)
- Jikai Zhang
- College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China; (J.Z.); (Y.L.); (T.Y.)
- Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China
- Key Laboratory of Modern Agricultural Machinery Corps, Shihezi 832003, China
| | - Xia Zheng
- College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China; (J.Z.); (Y.L.); (T.Y.)
- Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China
- Key Laboratory of Modern Agricultural Machinery Corps, Shihezi 832003, China
| | - Hongwei Xiao
- College of Engineering, China Agricultural University, Beijing 100080, China;
| | - Chunhui Shan
- College of Food, Shihezi University, Shihezi 832003, China;
| | - Yican Li
- College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China; (J.Z.); (Y.L.); (T.Y.)
- Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China
- Key Laboratory of Modern Agricultural Machinery Corps, Shihezi 832003, China
| | - Taoqing Yang
- College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China; (J.Z.); (Y.L.); (T.Y.)
- Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China
- Key Laboratory of Modern Agricultural Machinery Corps, Shihezi 832003, China
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Zhang J, Zheng X, Xiao H, Li Y, Yang T. Effect of Combined Infrared Hot Air Drying on Yam Slices: Drying Kinetics, Energy Consumption, Microstructure, and Nutrient Composition. Foods 2023; 12:3048. [PMID: 37628048 PMCID: PMC10453475 DOI: 10.3390/foods12163048] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/31/2023] [Accepted: 08/10/2023] [Indexed: 08/27/2023] Open
Abstract
Using hot air drying (HAD) and combined infrared hot air drying (IR-HAD) test devices, the drying kinetics, unit energy consumption, color difference values, rehydration rate, microstructure, and changes in polysaccharide and allantoin contents of yam slices were examined at various temperatures (50 °C, 55 °C, 60 °C, 65 °C, and 70 °C). The findings demonstrated that each of the aforementioned parameters was significantly impacted by the drying temperature. IR-HAD dries quicker and takes less time to dry than HAD. The Deff of IR-HAD is higher than that of HAD at the same temperature and increases with the increase in temperature. The activation energy required for IR-HAD (26.35 kJ/mol) is lower than that required for HAD (32.53 kJ/mol). HAD uses more energy per unit than IR-HAD by a factor of greater than 1.3. Yam slices treated with IR-HAD had higher microscopic porosity, better rehydration, lower color difference values, and higher polysaccharide and allantoin levels than HAD-treated yam slices. The IR-HAD at 60 °C had the greatest comprehensive rating after a thorough analysis of the dried yam slices using the coefficient of variation method. Three statistical indicators were used to evaluate six thin-layer drying models, and the Weibull model was most applicable to describe the variation of drying characteristics of yam slices.
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Affiliation(s)
- Jikai Zhang
- College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China; (J.Z.); (Y.L.); (T.Y.)
- Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China
- Key Laboratory of Modern Agricultural Machinery Corps, Shihezi 832003, China
| | - Xia Zheng
- College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China; (J.Z.); (Y.L.); (T.Y.)
- Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China
- Key Laboratory of Modern Agricultural Machinery Corps, Shihezi 832003, China
| | - Hongwei Xiao
- College of Engineering, China Agricultural University, Beijing 100080, China;
| | - Yican Li
- College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China; (J.Z.); (Y.L.); (T.Y.)
- Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China
- Key Laboratory of Modern Agricultural Machinery Corps, Shihezi 832003, China
| | - Taoqing Yang
- College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China; (J.Z.); (Y.L.); (T.Y.)
- Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China
- Key Laboratory of Modern Agricultural Machinery Corps, Shihezi 832003, China
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Cai X, Deng H, Li W, Li H, Li M. Study on fresh processing key technology and quality influence of Cut Ophiopogonis Radix based on multi-index evaluation. Open Life Sci 2023; 18:20220638. [PMID: 37483425 PMCID: PMC10358751 DOI: 10.1515/biol-2022-0638] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 05/04/2023] [Accepted: 05/22/2023] [Indexed: 07/25/2023] Open
Abstract
The purpose of this study was to ascertain the fresh processing technology of Cut Ophiopogonis Radix using a multi-index evaluation. This study comprehensively evaluated the fresh processing technology of sliced Cut Ophiopogonis Radix by investigating the cutting methods, cutting thickness, and drying conditions, and referring to The Chinese Pharmacopoeia 2020 edition. The appearance traits, internal quality (extract, total saponins, total flavonoids, total polysaccharides), and drying efficiency were used as evaluation indexes. The physical attributes of Cut Ophiopogonis Radix were found to vary based on the processing techniques employed. The shape, surface characteristics, texture, and color were observed to differ across the different methods. Notably, the apparent quality of Cut Ophiopogonis Radix was superior in samples processed using A1B1C1, A1B2C2, and A3B1C3 techniques. Drying time and energy consumption of Cut Ophiopogonis Radix produced by the A1B2C2 and A2B1C2 processes were less than those of other treatments, making them the optimal process for fresh processing Cut Ophiopogonis Radix. The impact of the cutting method and thickness on the extract was found to be statistically insignificant (P > 0.05). However, the drying method was observed to have a significant impact on the extract (P < 0.05). The cutting method, Cut thickness, and drying method did not affect the total saponin content (P > 0.05), but they had significant effects on the total polysaccharide and flavonoid contents (P < 0.01). Total polysaccharides were most affected by the cutting method, while total flavonoids were most affected by the drying condition. Based on the characteristics and internal quality, the fresh processing technology for Cut Ophiopogonis Radix was determined: fresh Ophiopogonis Radix was sliced to a thickness of 2-4 mm and dried at 55°C or a low temperature. The feasibility of Cut Ophiopogonis Radix is improved through its fresh processing. According to the evaluation indices, it is recommended to utilize the novel processing technique involving "fresh Ophiopogonis Radix" with fresh cuts, a cut thickness ranging from 2 to 4 mm, and drying at a temperature of 55℃ or through low-temperature drying. The Cut Ophiopogonis Radix exhibited favorable appearance and internal characteristics, thereby furnishing a scientific basis and innovative insights for the production of ophiopogon decoction slices.
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Affiliation(s)
- Xiaoyang Cai
- Key Laboratory of Standardization of Chinese Herbal Medicine, State Key Laboratory Breeding Base of Systematic Research, Development and Utilization of Chinese Medicine Resources, Ministry of Education, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Hongmei Deng
- Key Laboratory of Standardization of Chinese Herbal Medicine, State Key Laboratory Breeding Base of Systematic Research, Development and Utilization of Chinese Medicine Resources, Ministry of Education, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Wenjing Li
- Key Laboratory of Standardization of Chinese Herbal Medicine, State Key Laboratory Breeding Base of Systematic Research, Development and Utilization of Chinese Medicine Resources, Ministry of Education, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Hongyan Li
- Key Laboratory of Standardization of Chinese Herbal Medicine, State Key Laboratory Breeding Base of Systematic Research, Development and Utilization of Chinese Medicine Resources, Ministry of Education, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Min Li
- Key Laboratory of Standardization of Chinese Herbal Medicine, State Key Laboratory Breeding Base of Systematic Research, Development and Utilization of Chinese Medicine Resources, Ministry of Education, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
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