Pub Date : 2026-01-24DOI: 10.1016/j.jspr.2026.102960
Abhishek Dasore , Norhashila Hashim , Rosnah Shamsudin , Hasfalina Che Man , Maimunah Mohd Ali , Opeyemi Michael Ageh
Infrared thermal imaging (ITI) has emerged as a promising tool for non-destructive evaluation of agricultural product quality. This study investigates the application of ITI for monitoring the quality attributes and milling metrics of glutinous rice (GR) during storage under varying conditions. GR samples were first dried at 50 °C, 60 °C, and 70 °C, then stored at freezing (−10 °C), cold room (6 °C), and ambient (26 °C) temperatures for 6 months (24 weeks). Thermal images (TI) of the GR were acquired biweekly to evaluate the changes in key quality indicators, including moisture content (MC), germination growth rate (GGR), water absorption capacity (WAC), whiteness index (WI), head rice yield (HRY), and broken rice yield (BRY). Relevant features were extracted from the TI and correlated with the corresponding physicochemical properties of the GR. Ten machine learning (ML) algorithms were tested to predict the quality attributes of GR based on the features extracted from TI data. Among them, the ET model demonstrated superior performance compared to the others. Its predictive capability was further enhanced through grid search (GS) hyperparameter tuning (HPT), achieving an R2 of 0.939 and an RMSE of 0.178 for MC. The accuracy and reliability of the ET model were further supported by parity plots. Overall, the findings underscore the potential of integrating ITI with ML for non-destructive, real-time monitoring of GR quality, offering valuable insights for optimizing postharvest handling and storage practices.
{"title":"Evaluation of quality attributes and milling metrics of glutinous rice stored under different storage conditions using infrared thermal imaging","authors":"Abhishek Dasore , Norhashila Hashim , Rosnah Shamsudin , Hasfalina Che Man , Maimunah Mohd Ali , Opeyemi Michael Ageh","doi":"10.1016/j.jspr.2026.102960","DOIUrl":"10.1016/j.jspr.2026.102960","url":null,"abstract":"<div><div>Infrared thermal imaging (ITI) has emerged as a promising tool for non-destructive evaluation of agricultural product quality. This study investigates the application of ITI for monitoring the quality attributes and milling metrics of glutinous rice (GR) during storage under varying conditions. GR samples were first dried at 50 °C, 60 °C, and 70 °C, then stored at freezing (−10 °C), cold room (6 °C), and ambient (26 °C) temperatures for 6 months (24 weeks). Thermal images (TI) of the GR were acquired biweekly to evaluate the changes in key quality indicators, including moisture content (MC), germination growth rate (GGR), water absorption capacity (WAC), whiteness index (WI), head rice yield (HRY), and broken rice yield (BRY). Relevant features were extracted from the TI and correlated with the corresponding physicochemical properties of the GR. Ten machine learning (ML) algorithms were tested to predict the quality attributes of GR based on the features extracted from TI data. Among them, the ET model demonstrated superior performance compared to the others. Its predictive capability was further enhanced through grid search (GS) hyperparameter tuning (HPT), achieving an R<sup>2</sup> of 0.939 and an RMSE of 0.178 for MC. The accuracy and reliability of the ET model were further supported by parity plots. Overall, the findings underscore the potential of integrating ITI with ML for non-destructive, real-time monitoring of GR quality, offering valuable insights for optimizing postharvest handling and storage practices.</div></div>","PeriodicalId":17019,"journal":{"name":"Journal of Stored Products Research","volume":"116 ","pages":"Article 102960"},"PeriodicalIF":2.7,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Real-time monitoring of key gases (O2, CO2, PH3) is essential for ensuring food security and intelligent grain management. However, conventional offline methods are labor-intensive, lack the precision, and cannot provide timely data on deep grain conditions. Furthermore, the long-term stability of gas sensors is challenged by the highly corrosive conditions in grain silos, such as those during phosphine fumigation. This study develops and validates a multi-gas analyzer designed for automated, multi-point, and high-precision online monitoring under these adverse conditions. We develops a modular online gas analysis system featuring an 11-channel automatic sampler with solenoid valves, a precision pneumatic circuit, and a single-block computer numerical control machined flow manifold. Its core detection unit uses a hybrid sensing strategy, combining optimized techniques for each gas to achieve accuracies of ≤2 % Full Scale (F.S.) for O2, ≤3 % F.S. for CO2, and ≤3 % F.S. for PH3. We calibrated the system and compared the chemical robustness of our deposition-based oxygen sensor against a traditional electrochemical sensor under harsh conditions, including 1017 ppm phosphine and a complex mixture of volatiles from construction materials. Calibration confirmed high analytical precision (R2 = 0.99) for O2, CO2, and PH3. In corrosion resistance testing, a conventional electrochemical oxygen sensor failed within 1 h under 1017 ppm PH3. In contrast, our deposition-based sensor demonstrated exceptional resilience, maintaining 96.5 % of its initial sensitivity after 5 h of continuous exposure. Furthermore, the system's sensor also exhibited a significantly slower performance degradation rate than its electrochemical counterpart when exposed to complex volatiles from construction materials. Our study successfully demonstrates a multi-gas analyzer capable of providing long-term, stable, and automated monitoring in the harsh, corrosive environments typical of grain storage. The system represents a robust technological foundation for enabling truly intelligent grain management.
{"title":"Multi-gas monitoring system with enhanced chemical resilience for intelligent grain management","authors":"Xuemei Jiang , Yiao Zou , Haojie Li , Ting Guan , Mincheng Bai , Yufeng chen , Lanyue Huang , Hao Feng , Bingzhao Zheng , Zhaolin Gu , Zhongke Qu","doi":"10.1016/j.jspr.2026.102957","DOIUrl":"10.1016/j.jspr.2026.102957","url":null,"abstract":"<div><div>Real-time monitoring of key gases (O<sub>2</sub>, CO<sub>2</sub>, PH<sub>3</sub>) is essential for ensuring food security and intelligent grain management. However, conventional offline methods are labor-intensive, lack the precision, and cannot provide timely data on deep grain conditions. Furthermore, the long-term stability of gas sensors is challenged by the highly corrosive conditions in grain silos, such as those during phosphine fumigation. This study develops and validates a multi-gas analyzer designed for automated, multi-point, and high-precision online monitoring under these adverse conditions. We develops a modular online gas analysis system featuring an 11-channel automatic sampler with solenoid valves, a precision pneumatic circuit, and a single-block computer numerical control machined flow manifold. Its core detection unit uses a hybrid sensing strategy, combining optimized techniques for each gas to achieve accuracies of ≤2 % Full Scale (F.S.) for O<sub>2</sub>, ≤3 % F.S. for CO<sub>2</sub>, and ≤3 % F.S. for PH<sub>3</sub>. We calibrated the system and compared the chemical robustness of our deposition-based oxygen sensor against a traditional electrochemical sensor under harsh conditions, including 1017 ppm phosphine and a complex mixture of volatiles from construction materials. Calibration confirmed high analytical precision (R<sup>2</sup> = 0.99) for O<sub>2</sub>, CO<sub>2</sub>, and PH<sub>3</sub>. In corrosion resistance testing, a conventional electrochemical oxygen sensor failed within 1 h under 1017 ppm PH<sub>3</sub>. In contrast, our deposition-based sensor demonstrated exceptional resilience, maintaining 96.5 % of its initial sensitivity after 5 h of continuous exposure. Furthermore, the system's sensor also exhibited a significantly slower performance degradation rate than its electrochemical counterpart when exposed to complex volatiles from construction materials. Our study successfully demonstrates a multi-gas analyzer capable of providing long-term, stable, and automated monitoring in the harsh, corrosive environments typical of grain storage. The system represents a robust technological foundation for enabling truly intelligent grain management.</div></div>","PeriodicalId":17019,"journal":{"name":"Journal of Stored Products Research","volume":"116 ","pages":"Article 102957"},"PeriodicalIF":2.7,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-22DOI: 10.1016/j.jspr.2026.102952
Yongzheng Li , Kaili Liu , Dianbin Su , Weiqiao Lv , Yemin Guo , Xia Sun
Improving drying efficiency while maintaining product quality is a key challenge in microwave-hot air (M-H) food processing. Despite its wide application, the hydrothermal mechanisms driving moisture migration and quality changes remain poorly understood. To clarify the hydrothermal mechanisms involved in microwave-hot air drying, this study employed a novel microwave-infrared hot air rolling bed dryer (MIHRBD) to systematically evaluate the effects of M-H on moisture migration, dielectric properties, microstructure, and quality characteristics of Pleurotus eryngii. An integrated approach combining drying kinetics, low-field nuclear magnetic resonance (LF-NMR), dielectric analysis, and comprehensive quality evaluations was used to obtain a multi-scale understanding of the drying process. The results showed that M-H significantly enhanced drying efficiency compared to single-mode drying, with improvements ranging from 20 % to 72.32 %, the maximum achieved under the M0.5-H60 condition. Meanwhile, the maximum effective moisture diffusivity increased by 237.33 % and 370.26 %, respectively. LF-NMR analysis revealed that M-H effectively promoted internal moisture redistribution. This was reflected in the dielectric constant and dielectric loss factor, both of which first increased and then decreased, jointly regulated by moisture content and temperature. Moreover, this intrinsic regulation was manifested in the improvement of P. eryngii quality attributes. Under the M0.3-H50 condition, the retention of phenolics, flavonoids, organic acids, and polysaccharides was optimal. SEM observations further confirmed a more intact microstructure with fewer loss channels. These findings provide new insights for the establishment and optimization of M-H food processing systems and offer a feasible technical approach for the efficient processing of P. eryngii.
{"title":"Enhancing drying efficiency and quality retention of Pleurotus eryngii through microwave- hot air synergy: Insights into hydrothermal dynamics, moisture migration, and dielectric behavior","authors":"Yongzheng Li , Kaili Liu , Dianbin Su , Weiqiao Lv , Yemin Guo , Xia Sun","doi":"10.1016/j.jspr.2026.102952","DOIUrl":"10.1016/j.jspr.2026.102952","url":null,"abstract":"<div><div>Improving drying efficiency while maintaining product quality is a key challenge in microwave-hot air (M-H) food processing. Despite its wide application, the hydrothermal mechanisms driving moisture migration and quality changes remain poorly understood. To clarify the hydrothermal mechanisms involved in microwave-hot air drying, this study employed a novel microwave-infrared hot air rolling bed dryer (MIHRBD) to systematically evaluate the effects of M-H on moisture migration, dielectric properties, microstructure, and quality characteristics of <em>Pleurotus eryngii</em>. An integrated approach combining drying kinetics, low-field nuclear magnetic resonance (LF-NMR), dielectric analysis, and comprehensive quality evaluations was used to obtain a multi-scale understanding of the drying process. The results showed that M-H significantly enhanced drying efficiency compared to single-mode drying, with improvements ranging from 20 % to 72.32 %, the maximum achieved under the M0.5-H60 condition. Meanwhile, the maximum effective moisture diffusivity increased by 237.33 % and 370.26 %, respectively. LF-NMR analysis revealed that M-H effectively promoted internal moisture redistribution. This was reflected in the dielectric constant and dielectric loss factor, both of which first increased and then decreased, jointly regulated by moisture content and temperature. Moreover, this intrinsic regulation was manifested in the improvement of <em>P. eryngii</em> quality attributes. Under the M0.3-H50 condition, the retention of phenolics, flavonoids, organic acids, and polysaccharides was optimal. SEM observations further confirmed a more intact microstructure with fewer loss channels. These findings provide new insights for the establishment and optimization of M-H food processing systems and offer a feasible technical approach for the efficient processing of <em>P. eryngii</em>.</div></div>","PeriodicalId":17019,"journal":{"name":"Journal of Stored Products Research","volume":"116 ","pages":"Article 102952"},"PeriodicalIF":2.7,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-22DOI: 10.1016/j.jspr.2026.102956
Sookyung Oh , Rippy Singh , Yong-Biao Liu
This study investigated the fungicidal efficacy of nitrogen dioxide (NO2) fumigation against Aspergillus flavus on unshelled peanuts. Artificially infected peanuts were fumigated with NO2 at doses of 0.0 % (control), 0.1 %, 0.3 %, and 1.0 % for 1, 2, and 3 days. Quantitative analysis using the GreenLight™ enumeration test showed a dose-dependent inhibitory effect. For instance, after one day, intact peanuts treated with 0.1 %, 0.3 %, and 1.0 % NO2 showed Log CFU/mL values of 1.11, 0.24, and 0.00, respectively, compared to the control's 3.17 Log CFU/mL. Molecular corroboration through PCR showed reduced amplifiable A. flavus-specific DNA with complete inactivation at 1.0 % NO2. A key observation was the differential efficacy over extended durations. After three days, 0.1 % NO2 significantly reduced surface A. flavus but failed to yield a significant reduction for internal populations in cracked peanuts (2.38 Log CFU/mL vs. 3.05 Log CFU/mL in control), highlighting the protective barrier of the peanut shell. This research underscored the potential of NO2 fumigation for mitigating aflatoxin risk. Future studies should evaluate efficacy against other foodborne pathogens, assess safety regulations, quality attributes, and residue levels for commercial use.
{"title":"Antifungal effect of nitrogen dioxide fumigation on Aspergillus flavus in artificially infected unshelled peanuts","authors":"Sookyung Oh , Rippy Singh , Yong-Biao Liu","doi":"10.1016/j.jspr.2026.102956","DOIUrl":"10.1016/j.jspr.2026.102956","url":null,"abstract":"<div><div>This study investigated the fungicidal efficacy of nitrogen dioxide (NO<sub>2</sub>) fumigation against <em>Aspergillus flavus</em> on unshelled peanuts. Artificially infected peanuts were fumigated with NO<sub>2</sub> at doses of 0.0 % (control), 0.1 %, 0.3 %, and 1.0 % for 1, 2, and 3 days. Quantitative analysis using the GreenLight™ enumeration test showed a dose-dependent inhibitory effect. For instance, after one day, intact peanuts treated with 0.1 %, 0.3 %, and 1.0 % NO<sub>2</sub> showed Log CFU/mL values of 1.11, 0.24, and 0.00, respectively, compared to the control's 3.17 Log CFU/mL. Molecular corroboration through PCR showed reduced amplifiable <em>A. flavus</em>-specific DNA with complete inactivation at 1.0 % NO<sub>2</sub>. A key observation was the differential efficacy over extended durations. After three days, 0.1 % NO<sub>2</sub> significantly reduced surface <em>A. flavus</em> but failed to yield a significant reduction for internal populations in cracked peanuts (2.38 Log CFU/mL vs. 3.05 Log CFU/mL in control), highlighting the protective barrier of the peanut shell. This research underscored the potential of NO<sub>2</sub> fumigation for mitigating aflatoxin risk. Future studies should evaluate efficacy against other foodborne pathogens, assess safety regulations, quality attributes, and residue levels for commercial use.</div></div>","PeriodicalId":17019,"journal":{"name":"Journal of Stored Products Research","volume":"116 ","pages":"Article 102956"},"PeriodicalIF":2.7,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, the chitinase enzyme purified from Bacillus amyloliquefaciens M6 was immobilized on Zinc oxide/reduced graphene oxide nanocomposites (ZnO/RGO NCs), and its activity on Rhyzopertha dominica and Oryzaephilus surinamensis was tested. To optimize the culture medium, the M6 strain was developed under varying conditions, and the optimum substrate concentration, temperature, pH, and incubation time for chitinase production were determined as 5 g/L chitin, 35 °C, 6.0 pH, and 24 h. Compared to its activity prior to optimization (10.42 U/mL), the chitinase activity of the strain was observed to increase by 2.2 times. Under these conditions, chitinase was purified 6.75-fold from strain M6 with a specific activity of 228.90 U/mg (activity: 11,48 U/mL) and a yield of 1.84 %, and its molecular weight was determined to be ∼50 kDa. Chitinase was immobilized on ZnO/RGO NCs with 99.68 % immobilization efficiency and 94.30 % recovered activity. The optimum pH and temperature values of free and immobilized chitinase were determined as 6.0 and 45 °C. The activity of immobilized chitinase against R. dominica and O. surinamensis was tested and the LC50 and LC90 values for R. dominica were calculated as 1.8 mg/mL (32.8 U/mL) and 3.8 mg/mL (69.2 U/mL) and 4.8 mg/mL (87.4 U/mL) and 10.0 mg/mL (182.0 U/mL) for O. surinamensis. Thus, the obtained results concluded that the immobilized chitinase proved an alternative biocontrol agent to hazardous synthetic pesticides, the application of this biocontrol agent to make biopesticides will prove more reliable for sustaining the crop productivity and in crop protection.
{"title":"An efficient chitinase from Bacillus amyloliquefaciens M6: Immobilization to ZnO/RGO nanocomposite and its application in biocontrol","authors":"Sevda Uçar , Neslihan Dikbaş , Şeyma Alım , Emir Çepni , Göksel Tozlu , Merve Şenol Kotan , Tuba Öznülüer Özer , Muhammed Tatar , Kağan Kökten , Tolga Karaköy , Barış Binay","doi":"10.1016/j.jspr.2026.102958","DOIUrl":"10.1016/j.jspr.2026.102958","url":null,"abstract":"<div><div>In this study, the chitinase enzyme purified from <em>Bacillus amyloliquefaciens</em> M6 was immobilized on Zinc oxide/reduced graphene oxide nanocomposites (ZnO/RGO NCs), and its activity on <em>Rhyzopertha dominica</em> and <em>Oryzaephilus surinamensis</em> was tested. To optimize the culture medium, the M6 strain was developed under varying conditions, and the optimum substrate concentration, temperature, pH, and incubation time for chitinase production were determined as 5 g/L chitin, 35 °C, 6.0 pH, and 24 h. Compared to its activity prior to optimization (10.42 U/mL), the chitinase activity of the strain was observed to increase by 2.2 times. Under these conditions, chitinase was purified 6.75-fold from strain M6 with a specific activity of 228.90 U/mg (activity: 11,48 U/mL) and a yield of 1.84 %, and its molecular weight was determined to be ∼50 kDa. Chitinase was immobilized on ZnO/RGO NCs with 99.68 % immobilization efficiency and 94.30 % recovered activity. The optimum pH and temperature values of free and immobilized chitinase were determined as 6.0 and 45 °C. The activity of immobilized chitinase against <em>R. dominica</em> and <em>O. surinamensis</em> was tested and the LC<sub>50</sub> and LC<sub>90</sub> values for <em>R. dominica</em> were calculated as 1.8 mg/mL (32.8 U/mL) and 3.8 mg/mL (69.2 U/mL) and 4.8 mg/mL (87.4 U/mL) and 10.0 mg/mL (182.0 U/mL) for <em>O. surinamensis</em>. Thus, the obtained results concluded that the immobilized chitinase proved an alternative biocontrol agent to hazardous synthetic pesticides, the application of this biocontrol agent to make biopesticides will prove more reliable for sustaining the crop productivity and in crop protection.</div></div>","PeriodicalId":17019,"journal":{"name":"Journal of Stored Products Research","volume":"116 ","pages":"Article 102958"},"PeriodicalIF":2.7,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-22DOI: 10.1016/j.jspr.2026.102959
M.J. Gidado , Ahmad Anas Nagoor Gunny , Subash C.B. Gopinath , Monisha Devi , Azhar Mohd Ibrahim
The postharvest phase is critical to maintaining the quality, safety, and marketability of horticultural produce. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative tools in this domain, offering rapid, non-destructive, and highly accurate methods for assessing fruit quality. This review provides a comprehensive and critical analysis of the current state of AI and ML applications in postharvest quality assessment, with an emphasis on recent advancements in deep learning, computer vision, and predictive modelling. Despite significant progress, notable challenges persist including limited model generalizability across fruit types and environments, the high cost of implementation, data scarcity, and a lack of standardized protocols. These issues are particularly acute for smallholder farmers and low-resource settings. This review identifies critical research gaps such as the need for scalable, interpretable, and low-cost AI solutions, robust models capable of operating under dynamic environmental conditions, and interdisciplinary collaboration for practical deployment. It highlights novel approaches, including lightweight AI for edge computing, multi-modal sensor integration, and the use of open-source platforms to enhance accessibility. By synthesizing existing knowledge and mapping out future research directions, this review offers a roadmap for the development of inclusive, efficient, and sustainable AI-driven postharvest systems.
{"title":"Artificial intelligence and machine learning in postharvest fruit quality assessment: Current challenges, recent advances, and future prospects","authors":"M.J. Gidado , Ahmad Anas Nagoor Gunny , Subash C.B. Gopinath , Monisha Devi , Azhar Mohd Ibrahim","doi":"10.1016/j.jspr.2026.102959","DOIUrl":"10.1016/j.jspr.2026.102959","url":null,"abstract":"<div><div>The postharvest phase is critical to maintaining the quality, safety, and marketability of horticultural produce. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative tools in this domain, offering rapid, non-destructive, and highly accurate methods for assessing fruit quality. This review provides a comprehensive and critical analysis of the current state of AI and ML applications in postharvest quality assessment, with an emphasis on recent advancements in deep learning, computer vision, and predictive modelling. Despite significant progress, notable challenges persist including limited model generalizability across fruit types and environments, the high cost of implementation, data scarcity, and a lack of standardized protocols. These issues are particularly acute for smallholder farmers and low-resource settings. This review identifies critical research gaps such as the need for scalable, interpretable, and low-cost AI solutions, robust models capable of operating under dynamic environmental conditions, and interdisciplinary collaboration for practical deployment. It highlights novel approaches, including lightweight AI for edge computing, multi-modal sensor integration, and the use of open-source platforms to enhance accessibility. By synthesizing existing knowledge and mapping out future research directions, this review offers a roadmap for the development of inclusive, efficient, and sustainable AI-driven postharvest systems.</div></div>","PeriodicalId":17019,"journal":{"name":"Journal of Stored Products Research","volume":"116 ","pages":"Article 102959"},"PeriodicalIF":2.7,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-21DOI: 10.1016/j.jspr.2026.102954
Dalene de Beer , Chantelle Human , Brigitte V.P. du Preez , Erika I. Moelich , Marique Aucamp , Marieta van der Rijst , Elizabeth Joubert
A stable, palatable, aspalathin-rich rooibos iced tea powder in a convenient single-serve format offers a viable functional beverage for reducing sugar intake. Our initial goal was to determine the optimal ratio of green rooibos extract (GRE) to fermented rooibos extract (FRE). This was essential to create a formulation that combined high aspalathin content with the sought-after sensory profile of traditional fermented rooibos. The second goal was to ascertain how the addition of common beverage ingredients (xylitol, citric, and ascorbic acid) and moisture (6 % and 53 % relative humidity, RH) affected the physicochemical stability of the mixtures during accelerated shelf-life storage (40 °C; 12 weeks). An FRE:GRE ratio of 1:0.5 was found to have a similar sensory profile as FRE, generally accepted by consumers, with a high aspalathin content (83.5 mg L−1) compared to FRE alone (5.5 mg L−1). During storage at 53 % RH, crystalline ingredients significantly decreased the color (lower L∗ and h°) and aspalathin (based on first-order reaction rate constants) stability. Changes in the crystal structure, affected by the interaction between ingredients, were observed using powder X-ray diffraction and Fourier-transform infrared spectroscopy. Minimal changes were observed for all parameters when storing the iced tea powders at 6 % RH, regardless of formulation. Ready-to-reconstitute aspalathin-rich rooibos iced tea powders should be stored in moisture-impermeable packaging to ensure a physically (including color) and chemically stable product.
一种稳定、美味、富含芦笋素的路易波士冰茶粉，以方便的单份形式提供了一种可行的功能性饮料，可以减少糖的摄入量。我们最初的目标是确定绿色路易波士提取物（GRE）与发酵路易波士提取物（FRE）的最佳比例。这对于创造一种将高aspalathin含量与传统发酵路易波士受欢迎的感官特征相结合的配方至关重要。第二个目标是确定添加常见的饮料成分（木糖醇、柠檬酸和抗坏血酸）和水分（6%和53%相对湿度，RH）如何影响混合物在加速保质期（40°C； 12周）期间的物理化学稳定性。研究发现，FRE:GRE比例为1:0.5与消费者普遍接受的FRE具有相似的感官特征，与单独的FRE （5.5 mg L - 1）相比，其aspalathin含量（83.5 mg L - 1）较高。在53% RH下储存时，结晶成分显著降低了颜色（降低L *和h°）和石笋黄素（基于一级反应速率常数）的稳定性。利用粉末x射线衍射和傅里叶变换红外光谱观察了受成分相互作用影响的晶体结构变化。当冰茶粉在6% RH下储存时，无论配方如何，所有参数的变化都很小。富含阿斯巴冬素的路易波士冰茶粉应储存在不透湿的包装中，以确保产品的物理（包括颜色）和化学稳定性。
{"title":"Physicochemical stability of aspalathin-rich rooibos iced tea powders under accelerated storage conditions as affected by formulation","authors":"Dalene de Beer , Chantelle Human , Brigitte V.P. du Preez , Erika I. Moelich , Marique Aucamp , Marieta van der Rijst , Elizabeth Joubert","doi":"10.1016/j.jspr.2026.102954","DOIUrl":"10.1016/j.jspr.2026.102954","url":null,"abstract":"<div><div>A stable, palatable, aspalathin-rich rooibos iced tea powder in a convenient single-serve format offers a viable functional beverage for reducing sugar intake. Our initial goal was to determine the optimal ratio of green rooibos extract (GRE) to fermented rooibos extract (FRE). This was essential to create a formulation that combined high aspalathin content with the sought-after sensory profile of traditional fermented rooibos. The second goal was to ascertain how the addition of common beverage ingredients (xylitol, citric, and ascorbic acid) and moisture (6 % and 53 % relative humidity, RH) affected the physicochemical stability of the mixtures during accelerated shelf-life storage (40 °C; 12 weeks). An FRE:GRE ratio of 1:0.5 was found to have a similar sensory profile as FRE, generally accepted by consumers, with a high aspalathin content (83.5 mg L<sup>−1</sup>) compared to FRE alone (5.5 mg L<sup>−1</sup>). During storage at 53 % RH, crystalline ingredients significantly decreased the color (lower L∗ and h°) and aspalathin (based on first-order reaction rate constants) stability. Changes in the crystal structure, affected by the interaction between ingredients, were observed using powder X-ray diffraction and Fourier-transform infrared spectroscopy. Minimal changes were observed for all parameters when storing the iced tea powders at 6 % RH, regardless of formulation. Ready-to-reconstitute aspalathin-rich rooibos iced tea powders should be stored in moisture-impermeable packaging to ensure a physically (including color) and chemically stable product.</div></div>","PeriodicalId":17019,"journal":{"name":"Journal of Stored Products Research","volume":"116 ","pages":"Article 102954"},"PeriodicalIF":2.7,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-20DOI: 10.1016/j.jspr.2026.102955
Kuncan Yu, Shidan Zhang, Xiufang Bi, Chunlei Ni, Xi Cao, Yuanyuan Liu
This study hypothesized that the specific moisture migration patterns during the drying process of Stropharia rugosoannulata are intrinsically linked to the evolution of its physicochemical and nutritional qualities. To test this, the impacts of two drying methods—hot air drying (HAD) and vacuum drying (VD) at 50, 60, and 70 °C—on drying kinetics, color, microstructure, water mobility, and nutrient retention were systematically evaluated, with low-field nuclear magnetic resonance (LF-NMR) employed to elucidate moisture dynamics. Results demonstrated that HAD outperformed VD, exhibiting higher drying rates, less color degradation (smaller ΔE values), and better preservation of microstructure and structural integrity. LF-NMR revealed that free water was effectively removed during drying, with partial conversion to immobilized and bound water, while VD exhibited irregular moisture migration with higher residual water content. The contents of soluble total protein, crude polysaccharides, and phenolic substances decreased with drying time, with HAD showing superior retention of proteins and polysaccharides, while VD better preserved phenolic compounds. Among all treatments, HAD at 60 °C was identified as the optimal condition, demonstrating the smallest color change, minimal shrinkage, the most uniform moisture migration, and the highest crude polysaccharide retention. These findings confirm the intrinsic relationship between moisture migration and quality evolution in S. rugosoannulata during drying, providing a theoretical foundation for optimizing industrial drying protocols to balance efficiency with quality preservation.
{"title":"Moisture migration and quality evolution of Stropharia rugosoannulata during hot air and vacuum drying: An LF-NMR approach","authors":"Kuncan Yu, Shidan Zhang, Xiufang Bi, Chunlei Ni, Xi Cao, Yuanyuan Liu","doi":"10.1016/j.jspr.2026.102955","DOIUrl":"10.1016/j.jspr.2026.102955","url":null,"abstract":"<div><div>This study hypothesized that the specific moisture migration patterns during the drying process of <em>Stropharia rugosoannulata</em> are intrinsically linked to the evolution of its physicochemical and nutritional qualities. To test this, the impacts of two drying methods—hot air drying (HAD) and vacuum drying (VD) at 50, 60, and 70 °C—on drying kinetics, color, microstructure, water mobility, and nutrient retention were systematically evaluated, with low-field nuclear magnetic resonance (LF-NMR) employed to elucidate moisture dynamics. Results demonstrated that HAD outperformed VD, exhibiting higher drying rates, less color degradation (smaller ΔE values), and better preservation of microstructure and structural integrity. LF-NMR revealed that free water was effectively removed during drying, with partial conversion to immobilized and bound water, while VD exhibited irregular moisture migration with higher residual water content. The contents of soluble total protein, crude polysaccharides, and phenolic substances decreased with drying time, with HAD showing superior retention of proteins and polysaccharides, while VD better preserved phenolic compounds. Among all treatments, HAD at 60 °C was identified as the optimal condition, demonstrating the smallest color change, minimal shrinkage, the most uniform moisture migration, and the highest crude polysaccharide retention. These findings confirm the intrinsic relationship between moisture migration and quality evolution in <em>S. rugosoannulata</em> during drying, providing a theoretical foundation for optimizing industrial drying protocols to balance efficiency with quality preservation.</div></div>","PeriodicalId":17019,"journal":{"name":"Journal of Stored Products Research","volume":"116 ","pages":"Article 102955"},"PeriodicalIF":2.7,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-19DOI: 10.1016/j.jspr.2026.102951
Zhilei Yang , Lijun Wang , Yanyu Zhang , Shuheng Wang , Wenyao Huang , Lixiang Liao
Grain cleaning is a critical process for ensuring storage safety and reducing postharvest losses, primarily by removing impurities such as stalks and cobs and improving grain quality. However, uneven transverse dispersion of particles on the sieve surface often resulted in material accumulation and reduced cleaning efficiency. To address this issue, a multi-dovetail shape and planar combined sieve (M-DSPCS) was designed to promote rapid transverse dispersion of particles on the sieve surface. The dispersion mechanism of the dovetail-shaped units was analyzed using Computational Fluid Dynamics and the Discrete Element Method (CFD-DEM), and the simulation results were validated through physical experiments. The results show that the transverse dispersion of particles is accelerated by the dovetail-shaped unit structure, thereby improving the transverse dispersion uniformity of particles on the sieve. Simultaneously, the effective screening area of the sieve was increased and the contact rate between particles and the sieve surface (CRPSS) was enhanced, which increased the probability of maize grains passing through the sieve and thereby reduced maize grain losses. Under a feeding rate of 7 kg s−1, the M-DSPCS achieved a cleaning rate and loss rate of 99.03 % and 0.81 %, respectively. Compared with the planar sieve, cleaning rate increased by 1.87 %, adding 123.1 kg of effective maize grains per hectare, while loss rate decreased by 1.40 %, saving 92.3 kg of maize grains per hectare. This study proposed an effective approach for improving maize grain cleaning quality prior to storage and provided scientific guidance for the design and optimization of grain cleaning devices.
粮食清洗是确保储存安全和减少采后损失的关键过程，主要是去除秸秆和穗轴等杂质，提高粮食品质。然而，颗粒在筛面横向分散不均匀，往往造成物料堆积，降低了清洗效率。为了解决这一问题，设计了一种多燕尾形状和平面组合筛（M-DSPCS），以促进颗粒在筛表面的快速横向分散。采用计算流体力学和离散元法（CFD-DEM）分析了燕尾形单元的分散机理，并通过物理实验对仿真结果进行了验证。结果表明，燕尾状单元结构加速了颗粒的横向分散，从而提高了颗粒在筛上横向分散的均匀性。同时，增加了筛网的有效筛分面积，提高了颗粒与筛网表面的接触率（CRPSS），提高了玉米籽粒通过筛网的概率，减少了玉米籽粒的损失。在投料速率为7 kg s−1的条件下，M-DSPCS的清洁率和损失率分别为99.03%和0.81%。与平面筛相比，筛净率提高1.87%，每公顷增加有效玉米粒123.1 kg，损失率降低1.40%，每公顷节约玉米粒92.3 kg。本研究为提高玉米籽粒储运前清洗质量提供了有效途径，为籽粒清洗装置的设计和优化提供了科学指导。
{"title":"Enhancing maize grain cleaning before storage using a multi-dovetail shape and planar combined sieve: CFD-DEM simulation and experimental validation","authors":"Zhilei Yang , Lijun Wang , Yanyu Zhang , Shuheng Wang , Wenyao Huang , Lixiang Liao","doi":"10.1016/j.jspr.2026.102951","DOIUrl":"10.1016/j.jspr.2026.102951","url":null,"abstract":"<div><div>Grain cleaning is a critical process for ensuring storage safety and reducing postharvest losses, primarily by removing impurities such as stalks and cobs and improving grain quality. However, uneven transverse dispersion of particles on the sieve surface often resulted in material accumulation and reduced cleaning efficiency. To address this issue, a multi-dovetail shape and planar combined sieve (M-DSPCS) was designed to promote rapid transverse dispersion of particles on the sieve surface. The dispersion mechanism of the dovetail-shaped units was analyzed using Computational Fluid Dynamics and the Discrete Element Method (CFD-DEM), and the simulation results were validated through physical experiments. The results show that the transverse dispersion of particles is accelerated by the dovetail-shaped unit structure, thereby improving the transverse dispersion uniformity of particles on the sieve. Simultaneously, the effective screening area of the sieve was increased and the contact rate between particles and the sieve surface (CRPSS) was enhanced, which increased the probability of maize grains passing through the sieve and thereby reduced maize grain losses. Under a feeding rate of 7 kg s<sup>−1</sup>, the M-DSPCS achieved a cleaning rate and loss rate of 99.03 % and 0.81 %, respectively. Compared with the planar sieve, cleaning rate increased by 1.87 %, adding 123.1 kg of effective maize grains per hectare, while loss rate decreased by 1.40 %, saving 92.3 kg of maize grains per hectare. This study proposed an effective approach for improving maize grain cleaning quality prior to storage and provided scientific guidance for the design and optimization of grain cleaning devices.</div></div>","PeriodicalId":17019,"journal":{"name":"Journal of Stored Products Research","volume":"116 ","pages":"Article 102951"},"PeriodicalIF":2.7,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Postharvest losses caused by insect infestation remain a major threat to grain security, particularly in long-term storage systems. Ethyl formate (EF) is a promising alternative fumigant to phosphine and methyl bromide, but its efficacy is strongly influenced by storage conditions and grain type. In this study, we evaluated and optimized EF fumigation against adults of Tribolium castaneum and Rhyzopertha dominica in stored wheat and maize. Single-factor experiments were conducted to examine the effects of temperature (15–35 °C), grain moisture content (12–16 %) and EF concentration (50–90 μL/L) on insect mortality. Mortality decreased significantly with increasing temperature and grain moisture content, but increased with EF concentration in both grain types. R. dominica was more susceptible to EF than T. castaneum, and insect mortality was generally higher in wheat than in maize. Based on these results, a three-factor, three-level Box–Behnken design was applied to develop response surface models for each pest-grain combination. EF concentration was the dominant factor in all models, followed by grain moisture and temperature. The models showed good fit (R2 = 0.93–0.97) and predicted optimal conditions of approximately 16–18 °C, 12 % grain moisture content and 85–90 μL/L EF. Under these conditions, validation trials achieved 97.8–100 % mortality, with relative errors ≤2.22 %. These findings demonstrated that EF can provide effective control of major stored-grain insects when application parameters are tailored to grain type and storage environment, and offer a quantitative basis for optimising EF fumigation in practice.
{"title":"Optimization of ethyl formate fumigation for controlling Tribolium castaneum and Rhyzopertha dominica in stored wheat and maize","authors":"Junyu He, Zhonghao He, Yuxiao Fan, Peian Tang, Xue Dong","doi":"10.1016/j.jspr.2026.102948","DOIUrl":"10.1016/j.jspr.2026.102948","url":null,"abstract":"<div><div>Postharvest losses caused by insect infestation remain a major threat to grain security, particularly in long-term storage systems. Ethyl formate (EF) is a promising alternative fumigant to phosphine and methyl bromide, but its efficacy is strongly influenced by storage conditions and grain type. In this study, we evaluated and optimized EF fumigation against adults of <em>Tribolium castaneum</em> and <em>Rhyzopertha dominica</em> in stored wheat and maize. Single-factor experiments were conducted to examine the effects of temperature (15–35 °C), grain moisture content (12–16 %) and EF concentration (50–90 μL/L) on insect mortality. Mortality decreased significantly with increasing temperature and grain moisture content, but increased with EF concentration in both grain types. <em>R. dominica</em> was more susceptible to EF than <em>T. castaneum</em>, and insect mortality was generally higher in wheat than in maize. Based on these results, a three-factor, three-level Box–Behnken design was applied to develop response surface models for each pest-grain combination. EF concentration was the dominant factor in all models, followed by grain moisture and temperature. The models showed good fit (R<sup>2</sup> = 0.93–0.97) and predicted optimal conditions of approximately 16–18 °C, 12 % grain moisture content and 85–90 μL/L EF. Under these conditions, validation trials achieved 97.8–100 % mortality, with relative errors ≤2.22 %. These findings demonstrated that EF can provide effective control of major stored-grain insects when application parameters are tailored to grain type and storage environment, and offer a quantitative basis for optimising EF fumigation in practice.</div></div>","PeriodicalId":17019,"journal":{"name":"Journal of Stored Products Research","volume":"116 ","pages":"Article 102948"},"PeriodicalIF":2.7,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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