Pub Date : 2026-06-01Epub Date: 2026-01-20DOI: 10.1016/j.foodcont.2026.111996
Jingrong Cheng , Zhenhua Shi , Xueming Liu , Huaigu Yang , Xuping Wang , Yaosheng Lin , Mingjun Zhu , Daobang Tang
This study systematically evaluated the effects of combining ε-polylysine (ε-PL) with high-temperature sterilization (TH), high-pressure processing (HPP), and cold plasma (CP) on the overall quality of braised beef, aiming to optimize non-thermal sterilization processes for meat products. Analyses encompassed microbial safety, textural properties, volatile profiles and sensory attributes, alongside a shelf-life prediction model established using first-order kinetics and the Arrhenius equation. Although all treatments achieved complete microbial elimination, the ε-PL (0.2 g/kg) + CP treatment exhibited superior performance. It reduced hardness by 55.27 % (732.51 g) and chewiness by 59.69 % (322.08) (P < 0.05), preserved sensory quality (score: 80.80), and enhanced total volatile compounds by 106 % versus CK group (no sterilization, no additives). In contrast, ε-PL + TH caused texture hardening and significant flavor loss, while ε-PL + HPP showed moderate quality retention. In contrast, ε-PL + TH caused texture hardening and significant flavor loss, while ε-PL + HPP showed moderate quality retention. The shelf-life model predicted 35.27 days at 4 °C for CP+ε-PL-treated samples, validated experimentally (34 days, 3.74 % error). These findings confirm CP+ε-PL as the optimal process, providing theoretical and technical support for meat sterilization.
{"title":"Quality optimization and shelf-life prediction of braised beef using synergistic ε-polylysine-integrated sterilization technologies","authors":"Jingrong Cheng , Zhenhua Shi , Xueming Liu , Huaigu Yang , Xuping Wang , Yaosheng Lin , Mingjun Zhu , Daobang Tang","doi":"10.1016/j.foodcont.2026.111996","DOIUrl":"10.1016/j.foodcont.2026.111996","url":null,"abstract":"<div><div>This study systematically evaluated the effects of combining ε-polylysine (ε-PL) with high-temperature sterilization (TH), high-pressure processing (HPP), and cold plasma (CP) on the overall quality of braised beef, aiming to optimize non-thermal sterilization processes for meat products. Analyses encompassed microbial safety, textural properties, volatile profiles and sensory attributes, alongside a shelf-life prediction model established using first-order kinetics and the Arrhenius equation. Although all treatments achieved complete microbial elimination, the ε-PL (0.2 g/kg) + CP treatment exhibited superior performance. It reduced hardness by 55.27 % (732.51 g) and chewiness by 59.69 % (322.08) (<em>P</em> < 0.05), preserved sensory quality (score: 80.80), and enhanced total volatile compounds by 106 % versus CK group (no sterilization, no additives). In contrast, ε-PL + TH caused texture hardening and significant flavor loss, while ε-PL + HPP showed moderate quality retention. In contrast, ε-PL + TH caused texture hardening and significant flavor loss, while ε-PL + HPP showed moderate quality retention. The shelf-life model predicted 35.27 days at 4 °C for CP+ε-PL-treated samples, validated experimentally (34 days, 3.74 % error). These findings confirm CP+ε-PL as the optimal process, providing theoretical and technical support for meat sterilization.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"184 ","pages":"Article 111996"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-06-01Epub Date: 2026-01-20DOI: 10.1016/j.foodcont.2026.111990
Zhuoer Chen, Ying Yang, Yaning Liang, Xue Wang, Qingqing Yang, Tao Le
Food safety is a growing global health concern. Numerous aptasensors have emerged for rapid detection of harmful residues and adulteration in food. However, most rely on bulky instrumentation, severely limiting their practical application and confining them to the laboratory. The fluorescence dye-displacement-based method is a classic and well-established design for aptasensors, yet it still requires instrumentation. Recently, the emergence of colorimetric dyes such as Cy7 and MTC shows great promise in overcoming this instrumental dependency. Additionally, light-up aptamers are increasingly being applied in food safety detection. Both engineered allosteric light-up aptamers and those capable of directly binding targets and enhancing their luminescence contribute to simplifying sensing systems. Third, aptasensors based on the aggregation–dispersion of AuNPs have faced considerable challenges in recent years. Many target molecules can directly interact with AuNPs and induce aggregation, potentially leading to severe false-positive results. This review critically analyzes this phenomenon and advises future researchers to exercise caution when employing this approach. Finally, the review proposes multiple design guidelines for each type of aptasensor discussed, drawing on findings from the literature and our laboratory's prior experience, offering practical solutions to challenges faced by researchers in the field.
{"title":"Portable, label-free, and unmodified aptasensors for monitoring small-molecule residues in food safety","authors":"Zhuoer Chen, Ying Yang, Yaning Liang, Xue Wang, Qingqing Yang, Tao Le","doi":"10.1016/j.foodcont.2026.111990","DOIUrl":"10.1016/j.foodcont.2026.111990","url":null,"abstract":"<div><div>Food safety is a growing global health concern. Numerous aptasensors have emerged for rapid detection of harmful residues and adulteration in food. However, most rely on bulky instrumentation, severely limiting their practical application and confining them to the laboratory. The fluorescence dye-displacement-based method is a classic and well-established design for aptasensors, yet it still requires instrumentation. Recently, the emergence of colorimetric dyes such as Cy7 and MTC shows great promise in overcoming this instrumental dependency. Additionally, light-up aptamers are increasingly being applied in food safety detection. Both engineered allosteric light-up aptamers and those capable of directly binding targets and enhancing their luminescence contribute to simplifying sensing systems. Third, aptasensors based on the aggregation–dispersion of AuNPs have faced considerable challenges in recent years. Many target molecules can directly interact with AuNPs and induce aggregation, potentially leading to severe false-positive results. This review critically analyzes this phenomenon and advises future researchers to exercise caution when employing this approach. Finally, the review proposes multiple design guidelines for each type of aptasensor discussed, drawing on findings from the literature and our laboratory's prior experience, offering practical solutions to challenges faced by researchers in the field.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"184 ","pages":"Article 111990"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-06-01Epub Date: 2026-02-03DOI: 10.1016/j.foodcont.2026.112029
Fizanaz Kabir , Amit Hasan Anik , Farhan Ishrak Tahmid , Md Nur E. Alam , Mahbub Alam
This study provides the first comprehensive evaluation of PTM concentrations by employing a paired food–water framework with probabilistic health risk assessment, thereby addressing limitations of previous single-matrix and deterministic studies and placing particular emphasis on children. A total of 84 samples collected from 42 sites across the megacity of Dhaka, Bangladesh, were analyzed for 13 elements (Pb, Cd, Cr, As, Ni, Zn, Cu, Sb, Fe, Mn, Co, Al, and Hg) using Inductively Coupled Plasma–Optical Emission Spectrometry. Several metal(loid)s exceeded the permissible thresholds in both fuchka shells and tamarind water, the highest exceedances were observed for Pb (30.4–2228.86 μg/kg), Al (3145.25–26466.57 μg/kg), and Zn (3358.7–31048.80 μg/kg) in fuchka shells, and for Al (0.01–18762.66 μg/L), Fe (966.79–42499.78 μg/L), Mn (99.95–7096.55 μg/L), and Cd (1.17–33.7 μg/L) in tamarind water. Heavy Metal Index (HMI) exceeded safe levels in 23.8% of samples, Heavy Metal Pollution Index (HPI) in 59.5%, and >95% tamarind water was strongly polluted. Source apportionment through receptor models, Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) indicated dominant geogenic and road dust inputs (Fe, Al, Mn), Ni and Cr from mineral and utensil-related activities, and utensil-driven leaching of Cu, Zn, and Al in tamarind water, with additional Pb, Sb, and As contributions. Health risk analysis showed children were most vulnerable, and Monte Carlo Simulations (MCS) confirmed non-carcinogenic risks mainly from Mn and Pb. Incremental Lifetime Cancer Risk (ILCR) surpassed 1 × 10−4 for Pb, Cr, Ni, and Cd, underscoring urgent public health concerns.
{"title":"Unveiling potential toxic metal(loid)s in popular street-vended food from a mega city (Dhaka, Bangladesh): Insights into sources, pollution status, and probabilistic risk modeling","authors":"Fizanaz Kabir , Amit Hasan Anik , Farhan Ishrak Tahmid , Md Nur E. Alam , Mahbub Alam","doi":"10.1016/j.foodcont.2026.112029","DOIUrl":"10.1016/j.foodcont.2026.112029","url":null,"abstract":"<div><div>This study provides the first comprehensive evaluation of PTM concentrations by employing a paired food–water framework with probabilistic health risk assessment, thereby addressing limitations of previous single-matrix and deterministic studies and placing particular emphasis on children. A total of 84 samples collected from 42 sites across the megacity of Dhaka, Bangladesh, were analyzed for 13 elements (Pb, Cd, Cr, As, Ni, Zn, Cu, Sb, Fe, Mn, Co, Al, and Hg) using Inductively Coupled Plasma–Optical Emission Spectrometry. Several metal(loid)s exceeded the permissible thresholds in both fuchka shells and tamarind water, the highest exceedances were observed for Pb (30.4–2228.86 μg/kg), Al (3145.25–26466.57 μg/kg), and Zn (3358.7–31048.80 μg/kg) in fuchka shells, and for Al (0.01–18762.66 μg/L), Fe (966.79–42499.78 μg/L), Mn (99.95–7096.55 μg/L), and Cd (1.17–33.7 μg/L) in tamarind water. Heavy Metal Index (HMI) exceeded safe levels in 23.8% of samples, Heavy Metal Pollution Index (HPI) in 59.5%, and >95% tamarind water was strongly polluted. Source apportionment through receptor models, Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) indicated dominant geogenic and road dust inputs (Fe, Al, Mn), Ni and Cr from mineral and utensil-related activities, and utensil-driven leaching of Cu, Zn, and Al in tamarind water, with additional Pb, Sb, and As contributions. Health risk analysis showed children were most vulnerable, and Monte Carlo Simulations (MCS) confirmed non-carcinogenic risks mainly from Mn and Pb. Incremental Lifetime Cancer Risk (ILCR) surpassed 1 × 10<sup>−4</sup> for Pb, Cr, Ni, and Cd, underscoring urgent public health concerns.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"184 ","pages":"Article 112029"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146170612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-06-01Epub Date: 2026-01-31DOI: 10.1016/j.foodcont.2026.112002
Alberto Ortiz , Javier García-Gudiño , Lucía León , María Freire , David Tejerina
The feasibility of Near-infrared spectroscopy (NIR) for the in vivo authentication of feeding regimen in purebred Iberian pigs during the final fattening stage in the dehesa was evaluated. A total of 167 animals were monitored across three feeding strategies that differed in the level and timing of supplementary feed; Acorn-fed (n = 40), Supplemented Partial (n = 83) and Supplemented Complete groups (n = 44). Following the final fattening stage, NIR spectra were collected from each animal. The model developed by Partial Least Squares-Discriminant Analysis achieved accuracy values above 90% in external validation, with a Matthews Correlation Coefficient of 0.77, demonstrating a strong ability to distinguish between feeding regimes despite their high similarity and shared access to natural resources., These results confirm that NIRS provides a reliable, non-destructive, and rapid tool for the in vivo authentication of acorn-fed Iberian pigs, offering substantial potential for strengthening traceability, preventing fraudulent practices, and supporting official inspection and certification processes in the Iberian pig sector.
{"title":"In vivo authentication of acorn-fed purebred Iberian pigs in dehesa ecosystem using Near-Infrared Spectroscopy","authors":"Alberto Ortiz , Javier García-Gudiño , Lucía León , María Freire , David Tejerina","doi":"10.1016/j.foodcont.2026.112002","DOIUrl":"10.1016/j.foodcont.2026.112002","url":null,"abstract":"<div><div>The feasibility of Near-infrared spectroscopy (NIR) for the <em>in vivo</em> authentication of feeding regimen in purebred Iberian pigs during the final fattening stage in the <em>dehesa</em> was evaluated. A total of 167 animals were monitored across three feeding strategies that differed in the level and timing of supplementary feed; Acorn-fed (n = 40), Supplemented Partial (n = 83) and Supplemented Complete groups (n = 44). Following the final fattening stage, NIR spectra were collected from each animal. The model developed by Partial Least Squares-Discriminant Analysis achieved accuracy values above 90% in external validation, with a Matthews Correlation Coefficient of 0.77, demonstrating a strong ability to distinguish between feeding regimes despite their high similarity and shared access to natural resources., These results confirm that NIRS provides a reliable, non-destructive, and rapid tool for the <em>in vivo</em> authentication of acorn-fed Iberian pigs, offering substantial potential for strengthening traceability, preventing fraudulent practices, and supporting official inspection and certification processes in the Iberian pig sector.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"184 ","pages":"Article 112002"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146170690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-06-01Epub Date: 2026-01-23DOI: 10.1016/j.foodcont.2026.112011
Raquel Martínez-Peña , Salvador Castillo , Sergio Vélez , Sara Álvarez
Pistachio quality is a major determinant of market value, particularly in Mediterranean environments strongly influenced by irrigation and climate. This study evaluated effects of orchard location and irrigation on pistachio nutritional content and assessed VIS–NIR hyperspectral imaging coupled with machine-learning techniques as a non-destructive predictive approach. Field experiments were conducted in 2022 in two commercial orchards in Castilla y León, Spain, under control and high-irrigation treatments. A total of 2818 pistachio kernels were analysed using a portable VIS–NIR hyperspectral camera (400–1000 nm). Mean spectra were extracted for each nut, pre-processed using standard normal variate correction, and linked to reference measurements of minerals, proximate composition and fatty acids. Partial Least Squares regression, Support Vector Regression and Extra Trees Regressor models were calibrated and validated to predict quality parameters from spectral data. Location, irrigation and their interaction significantly affected most nutritional and lipid traits. Pistachios from Moraleja de las Panaderas showed higher nitrogen, phosphorus, protein, ash and oleic acid contents, whereas samples from La Seca exhibited relatively higher sodium and linoleic acid levels. Increased irrigation enhanced the accumulation of several minerals and saturated fatty acids. Among the evaluated algorithms, Partial Least Squares regression provided the most consistent performance, accurately predicting nitrogen (R2 = 0.75), zinc (R2 = 0.81), oleic acid (R2 = 0.91), linoleic acid (R2 = 0.87), ash (R2 = 0.81), carbohydrates (R2 = 0.87) and humidity (R2 = 0.84). Overall, VIS–NIR HSI with machine learning enables non-destructive, data-driven optimisation of pistachio irrigation management.
{"title":"HSI and ML for non-destructive pistachio quality assessment: Influence of location and irrigation on nutrient and fat composition","authors":"Raquel Martínez-Peña , Salvador Castillo , Sergio Vélez , Sara Álvarez","doi":"10.1016/j.foodcont.2026.112011","DOIUrl":"10.1016/j.foodcont.2026.112011","url":null,"abstract":"<div><div>Pistachio quality is a major determinant of market value, particularly in Mediterranean environments strongly influenced by irrigation and climate. This study evaluated effects of orchard location and irrigation on pistachio nutritional content and assessed VIS–NIR hyperspectral imaging coupled with machine-learning techniques as a non-destructive predictive approach. Field experiments were conducted in 2022 in two commercial orchards in Castilla y León, Spain, under control and high-irrigation treatments. A total of 2818 pistachio kernels were analysed using a portable VIS–NIR hyperspectral camera (400–1000 nm). Mean spectra were extracted for each nut, pre-processed using standard normal variate correction, and linked to reference measurements of minerals, proximate composition and fatty acids. Partial Least Squares regression, Support Vector Regression and Extra Trees Regressor models were calibrated and validated to predict quality parameters from spectral data. Location, irrigation and their interaction significantly affected most nutritional and lipid traits. Pistachios from Moraleja de las Panaderas showed higher nitrogen, phosphorus, protein, ash and oleic acid contents, whereas samples from La Seca exhibited relatively higher sodium and linoleic acid levels. Increased irrigation enhanced the accumulation of several minerals and saturated fatty acids. Among the evaluated algorithms, Partial Least Squares regression provided the most consistent performance, accurately predicting nitrogen (R<sup>2</sup> = 0.75), zinc (R<sup>2</sup> = 0.81), oleic acid (R<sup>2</sup> = 0.91), linoleic acid (R<sup>2</sup> = 0.87), ash (R<sup>2</sup> = 0.81), carbohydrates (R<sup>2</sup> = 0.87) and humidity (R<sup>2</sup> = 0.84). Overall, VIS–NIR HSI with machine learning enables non-destructive, data-driven optimisation of pistachio irrigation management.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"184 ","pages":"Article 112011"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146075234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-06-01Epub Date: 2026-01-23DOI: 10.1016/j.foodcont.2026.112016
Lu Yao , Zhang Rongyao , Lu Yingzhe , Li Xuefeng , Hou Bingqian , Song Zhanhua , Yang Qinglu , Yan Yinfa
Fusarium head blight (FHB), together with its primary mycotoxin deoxynivalenol (DON), poses a significant threat to wheat yield and food security. In this study, visible near-infrared hyperspectral imaging (VNIR-HSI) combined with scanning electron microscopy (SEM) and synchrotron radiation Fourier transform infrared (SR-FTIR) microspectroscopy were integrated to investigate the spatial heterogeneity and enable nondestructive detection of DON in field-contaminated wheat kernels. Specifically, SR-FTIR combined with SEM was used to reveal the micro-phenotypic characteristics and nutrient distribution of wheat kernels. VNIR-HSI was employed to extract spectral fingerprint of DON and achieve its quantitative detection. Using measured DON levels and spectral features, simplified classification and regression models were developed, achieving DWT + SVM (AC = 97.21 %, AP = 94.44 %) for FHB grading and SG + GA-RF (R2P = 0.9347, RMSEP = 1.8460, RPD = 4.0249) for DON toxin regression. It provided new insights on how to clarify heterogeneity patterns and quantify DON levels in single wheat kernel.
{"title":"Nondestructive detection of deoxynivalenol in wheat kernels using VNIR-HSI supported by spatial heterogeneity analysis with SEM and SR-FTIR","authors":"Lu Yao , Zhang Rongyao , Lu Yingzhe , Li Xuefeng , Hou Bingqian , Song Zhanhua , Yang Qinglu , Yan Yinfa","doi":"10.1016/j.foodcont.2026.112016","DOIUrl":"10.1016/j.foodcont.2026.112016","url":null,"abstract":"<div><div>Fusarium head blight (FHB), together with its primary mycotoxin deoxynivalenol (DON), poses a significant threat to wheat yield and food security. In this study, visible near-infrared hyperspectral imaging (VNIR-HSI) combined with scanning electron microscopy (SEM) and synchrotron radiation Fourier transform infrared (SR-FTIR) microspectroscopy were integrated to investigate the spatial heterogeneity and enable nondestructive detection of DON in field-contaminated wheat kernels. Specifically, SR-FTIR combined with SEM was used to reveal the micro-phenotypic characteristics and nutrient distribution of wheat kernels. VNIR-HSI was employed to extract spectral fingerprint of DON and achieve its quantitative detection. Using measured DON levels and spectral features, simplified classification and regression models were developed, achieving DWT + SVM (<em>A</em><sub><em>C</em></sub> = 97.21 %, <em>A</em><sub><em>P</em></sub> = 94.44 %) for FHB grading and SG + GA-RF (<em>R</em><sup><em>2</em></sup><sub><em>P</em></sub> = 0.9347, <em>RMSE</em><sub><em>P</em></sub> = 1.8460, <em>RPD</em> = 4.0249) for DON toxin regression. It provided new insights on how to clarify heterogeneity patterns and quantify DON levels in single wheat kernel.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"184 ","pages":"Article 112016"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146075237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-06-01Epub Date: 2026-01-20DOI: 10.1016/j.foodcont.2026.111997
Jiahui Du , Jiushi Guo , Ganqi Yang , Boyu Wang , Jie Cao , Tungalag Dong , Terigen Bao , Shan Qing , Ying Fu , Xueyan Yun
The global rise in mutton consumption has highlighted the need for efficient processing of sheep liver, a nutritious by-product prone to rapid quality degradation and off-odor development. This study investigated the combined effect of a high-barrier PA6-based packaging film and Cistanche deserticola aqueous extract (CAE) pretreatment on the storage quality of cooked sheep liver. Results demonstrated that the developed packaging significantly reduced oxygen permeability and UV transmittance, while the CAE exhibited notable antioxidant activity. The group treated with the high-barrier packaging combined with CAE showed the best overall performance, significantly better than those using commercial polypropylene packaging or water pretreatment, in maintaining sensory attributes, texture, color stability, and key nutritional components such as vitamin A throughout the 40-day storage period at 25 °C. Volatile compound analysis via GC-MS further confirmed reduced formation of lipid oxidation-derived volatiles and microbial metabolites in the same group. The synergistic combination of high-barrier packaging and natural antioxidant treatment offers an effective strategy for extending the shelf life of cooked sheep liver products.
{"title":"A novel strategy for cooked sheep liver preservation: Integrating high-barrier polymer packaging with Cistanche deserticola aqueous extract treatment","authors":"Jiahui Du , Jiushi Guo , Ganqi Yang , Boyu Wang , Jie Cao , Tungalag Dong , Terigen Bao , Shan Qing , Ying Fu , Xueyan Yun","doi":"10.1016/j.foodcont.2026.111997","DOIUrl":"10.1016/j.foodcont.2026.111997","url":null,"abstract":"<div><div>The global rise in mutton consumption has highlighted the need for efficient processing of sheep liver, a nutritious by-product prone to rapid quality degradation and off-odor development. This study investigated the combined effect of a high-barrier PA6-based packaging film and <em>Cistanche deserticola</em> aqueous extract (CAE) pretreatment on the storage quality of cooked sheep liver. Results demonstrated that the developed packaging significantly reduced oxygen permeability and UV transmittance, while the CAE exhibited notable antioxidant activity. The group treated with the high-barrier packaging combined with CAE showed the best overall performance, significantly better than those using commercial polypropylene packaging or water pretreatment, in maintaining sensory attributes, texture, color stability, and key nutritional components such as vitamin A throughout the 40-day storage period at 25 °C. Volatile compound analysis via GC-MS further confirmed reduced formation of lipid oxidation-derived volatiles and microbial metabolites in the same group. The synergistic combination of high-barrier packaging and natural antioxidant treatment offers an effective strategy for extending the shelf life of cooked sheep liver products.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"184 ","pages":"Article 111997"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146075299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-06-01Epub Date: 2026-01-23DOI: 10.1016/j.foodcont.2026.112015
Tao Jiang , Jinfang Zhu , Aying Wen , Jianjun Ding , Yuhang Du , Shaofeng Yuan , Yahui Guo , Yuliang Cheng , Hang Yu , Weirong Yao
Owing to the geographical indication (GI) advantages of Hongmeiren (HMR) citrus, economically driven fraudulent practices have emerged. The objective of this study is to propose a machine learning-based feature fusion method of mineral elements and quality components for GI authentication in HMR citrus. The characteristic mineral elements and quality components were identified by variable importance in projection (VIP) and Boruta algorithm (BA) to construct feature fusion datasets. Machine learning models including k-nearest neighbours (KNN), extreme gradient boosting (XGB), partial least squares discriminant analysis (PLSDA), and multi-layer feedforward neural network (MFNN) were applied for GI authentication of HMR citrus. VIP and BA feature fusion datasets exhibited higher generalization performance of models than raw feature fusion dataset and individual datasets. Compared to VIP, BA enhanced feature selection and showed more effective model performance improvement with feature fusion datasets. The XGB with BA feature fusion dataset demonstrated the best generalization performance, achieving an overall accuracy of 87.7 %, as well as a recall and precision of 93.8 % for GI origin with an area under the curve (AUC) of receiver operating characteristic (ROC) of 0.997. The characteristic mineral elements (K, Mg, Mn, Fe) and characteristic quality components (soluble solids content (SSC), fructose (Fru), ascorbic acid (AA), total phenolics (TP)) can be regarded as the authenticity markers. A Shiny application of XGB with the BA feature fusion dataset was developed for online GI authentication. Overall, this study provides an effective strategy to avoid the origin fraud of fruits.
{"title":"Geographical indication authentication of Hongmeiren citrus using machine learning-based feature fusion of mineral elements and quality components","authors":"Tao Jiang , Jinfang Zhu , Aying Wen , Jianjun Ding , Yuhang Du , Shaofeng Yuan , Yahui Guo , Yuliang Cheng , Hang Yu , Weirong Yao","doi":"10.1016/j.foodcont.2026.112015","DOIUrl":"10.1016/j.foodcont.2026.112015","url":null,"abstract":"<div><div>Owing to the geographical indication (GI) advantages of Hongmeiren (HMR) citrus, economically driven fraudulent practices have emerged. The objective of this study is to propose a machine learning-based feature fusion method of mineral elements and quality components for GI authentication in HMR citrus. The characteristic mineral elements and quality components were identified by variable importance in projection (VIP) and Boruta algorithm (BA) to construct feature fusion datasets. Machine learning models including k-nearest neighbours (KNN), extreme gradient boosting (XGB), partial least squares discriminant analysis (PLSDA), and multi-layer feedforward neural network (MFNN) were applied for GI authentication of HMR citrus. VIP and BA feature fusion datasets exhibited higher generalization performance of models than raw feature fusion dataset and individual datasets. Compared to VIP, BA enhanced feature selection and showed more effective model performance improvement with feature fusion datasets. The XGB with BA feature fusion dataset demonstrated the best generalization performance, achieving an overall accuracy of 87.7 %, as well as a recall and precision of 93.8 % for GI origin with an area under the curve (AUC) of receiver operating characteristic (ROC) of 0.997. The characteristic mineral elements (K, Mg, Mn, Fe) and characteristic quality components (soluble solids content (SSC), fructose (Fru), ascorbic acid (AA), total phenolics (TP)) can be regarded as the authenticity markers. A Shiny application of XGB with the BA feature fusion dataset was developed for online GI authentication. Overall, this study provides an effective strategy to avoid the origin fraud of fruits.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"184 ","pages":"Article 112015"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dry-aging is a controlled, unpackaged maturation process of beef that relies on low temperature, regulated humidity, and continuous airflow to concentrate flavor, enhance tenderness, and develop a distinctive sensory profile. This review consolidates current knowledge on the physical, biochemical, and microbiological mechanisms driving quality changes during dry-aging, and summarizes key processing parameters, safety considerations, and economic implications. Moisture evaporation and crust formation promote surface dehydration and weight loss, while endogenous proteases accelerate myofibrillar degradation, thereby reducing shear force and improving tenderness. Concurrent lipolysis increases free fatty acids, which, together with controlled oxidation, generate volatile compounds responsible for characteristic nutty and buttery flavor notes. Surface microbiota, predominantly composed of non-pathogenic yeasts and moulds, influence aroma development but require appropriate control to minimize pathogen risk. Microbial metabolic activity contributes to flavor formation through proteolysis and lipolysis; however, monitoring is necessary to limit biogenic amine accumulation and maintain meat quality and safety. Processing variables, including temperature, relative humidity, air velocity, and aging duration, determine proteolysis and oxidation kinetics, yield loss, and trimming requirements, ultimately affecting product quality and economic return. Evidence highlights the roles of marbling, carcass hygiene, and postmortem handling in shaping aging outcomes. Remaining gaps include standardized process reporting, multi-omics characterization of microbial communities, and predictive models linking processing factors to sensory and economic outputs. This review provides practical guidance for robust process control and identifies research priorities to support safe and cost-effective dry-aging practices in the beef industry.
{"title":"Transformative effects of dry aging on beef quality, sensory attributes, and process control","authors":"Salma Mohamad Yusop , Mohd Azri Azman , Premy Puspitawati Rahayu , Nurul Huda","doi":"10.1016/j.foodcont.2026.111986","DOIUrl":"10.1016/j.foodcont.2026.111986","url":null,"abstract":"<div><div>Dry-aging is a controlled, unpackaged maturation process of beef that relies on low temperature, regulated humidity, and continuous airflow to concentrate flavor, enhance tenderness, and develop a distinctive sensory profile. This review consolidates current knowledge on the physical, biochemical, and microbiological mechanisms driving quality changes during dry-aging, and summarizes key processing parameters, safety considerations, and economic implications. Moisture evaporation and crust formation promote surface dehydration and weight loss, while endogenous proteases accelerate myofibrillar degradation, thereby reducing shear force and improving tenderness. Concurrent lipolysis increases free fatty acids, which, together with controlled oxidation, generate volatile compounds responsible for characteristic nutty and buttery flavor notes. Surface microbiota, predominantly composed of non-pathogenic yeasts and moulds, influence aroma development but require appropriate control to minimize pathogen risk. Microbial metabolic activity contributes to flavor formation through proteolysis and lipolysis; however, monitoring is necessary to limit biogenic amine accumulation and maintain meat quality and safety. Processing variables, including temperature, relative humidity, air velocity, and aging duration, determine proteolysis and oxidation kinetics, yield loss, and trimming requirements, ultimately affecting product quality and economic return. Evidence highlights the roles of marbling, carcass hygiene, and postmortem handling in shaping aging outcomes. Remaining gaps include standardized process reporting, multi-omics characterization of microbial communities, and predictive models linking processing factors to sensory and economic outputs. This review provides practical guidance for robust process control and identifies research priorities to support safe and cost-effective dry-aging practices in the beef industry.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"184 ","pages":"Article 111986"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-06-01Epub Date: 2026-01-20DOI: 10.1016/j.foodcont.2026.111991
Zhoujian He , Meng Ye , Jie Huan , Huaxue Wu , Xiaomei Luo , Liqiong Jiang , Xiao Gong , Li Zheng
As a globally utilized spice, cinnamon finds extensive applications across food, pharmaceutical, and cosmetic industries. The term “Cinnamon” collectively refers to dried inner bark products from multiple Cinnamomum species, with diverse commercial nomenclature arising from varied plant parts and processing methods. However, the potential food safety risks associated with this nomenclature complexity remain understudied. This review systematically examines the botanical origins of commercial cinnamon products and analyzes their associated food safety hazards. Ceylon cinnamon (Cinnamomum verum) represents the premium commercial variety, while cassia cinnamon familycomprising six Cinnamomum species dominates global market share. Chemical variability among products may induce allergic reactions. Lead (Pb) emerges as the predominant heavy metal contaminant, with bark-derived products showing highest contamination levels of heavy metals. Economically motivated adulteration constitutes the primary source of food fraud. We propose a comprehensive safety framework involving standardized labeling protocols, enhanced authentication technologies, and improved traceability systems to mitigate cinnamon-related food safety concerns.
{"title":"The relationship between cinnamon's diverse commercial names and food safety risks","authors":"Zhoujian He , Meng Ye , Jie Huan , Huaxue Wu , Xiaomei Luo , Liqiong Jiang , Xiao Gong , Li Zheng","doi":"10.1016/j.foodcont.2026.111991","DOIUrl":"10.1016/j.foodcont.2026.111991","url":null,"abstract":"<div><div>As a globally utilized spice, cinnamon finds extensive applications across food, pharmaceutical, and cosmetic industries. The term “Cinnamon” collectively refers to dried inner bark products from multiple <em>Cinnamomum</em> species, with diverse commercial nomenclature arising from varied plant parts and processing methods. However, the potential food safety risks associated with this nomenclature complexity remain understudied. This review systematically examines the botanical origins of commercial cinnamon products and analyzes their associated food safety hazards. Ceylon cinnamon (<em>Cinnamomum verum</em>) represents the premium commercial variety, while cassia cinnamon familycomprising six <em>Cinnamomum</em> species dominates global market share. Chemical variability among products may induce allergic reactions. Lead (Pb) emerges as the predominant heavy metal contaminant, with bark-derived products showing highest contamination levels of heavy metals. Economically motivated adulteration constitutes the primary source of food fraud. We propose a comprehensive safety framework involving standardized labeling protocols, enhanced authentication technologies, and improved traceability systems to mitigate cinnamon-related food safety concerns.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"184 ","pages":"Article 111991"},"PeriodicalIF":6.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}