Journal of Agriculture and Food Research最新文献

{"title":"Investigating the impact of the key processing stages on flavor components and lipid flavor formation of Tibetan dried pork slice","authors":"Xue Xiao ,&nbsp;Huaying Chen ,&nbsp;Xuehai Ge ,&nbsp;Jiangping Fan ,&nbsp;Liangyu Yang ,&nbsp;Junhua Shao ,&nbsp;Shijun Li ,&nbsp;Changrong Ge ,&nbsp;Zhichao Xiao","doi":"10.1016/j.jafr.2026.102696","DOIUrl":"10.1016/j.jafr.2026.102696","url":null,"abstract":"<div><div>This study aimed to explore the aroma formation mechanism of Tibetan dried pork slice by investigating changes of their volatile compounds and lipid molecules across four key processing stages (mincing, seasoning, drying, and baking). E-nose analysis revealed significant differences in the odor profiles of dried pork slice at different processing stages. Furthermore, the drying and baking processes significantly enhanced the odor profiles of dried pork slice. The GC-IMS detected 61 volatile compounds, among which PLS-DA highlighted nine key contributors to the final flavor profile: ethyl 2-hydroxypropanoate-M, butanal, propanal, 3-methyl butanal, benzaldehyde, 1-nonanal, 1-hexanal-D, (Z)-2-pentenal, and 2-methylpyrazine. Additionally, the four processes significantly changed the content and composition of lipid molecules analyzed through LC-MS. Glycerolipids and phospholipids metabolism were identified as the primary metabolic pathway during the processing stages. Triglycerides (TG) and phosphatidylcholine (PC), such as TG (13:1/13:1/13:1), TG (17:0/18:1/18:1), TG (13:1/21:4/21:4), TG (12:0/12:0/19:3), TG (16:0/22:1/22:1), PC (18:4e/18:5) and PC (18:3/22:6), played a vital role in the generation of aroma compounds. Furthermore, the correlation between the lipid molecules and the key volatile compounds suggested the role of lipid oxidation, the Maillard reaction, as well as the interaction between these reactions in the aroma formation of dried pork slice. Therefore, this study provides the first evidence that lipid oxidation in the drying and baking stages is a critical factor in the aroma evolution of Tibetan dried pork slice. These findings provide a scientific basis for understanding the flavor formation mechanism and inform the development of optimized processing strategies for Tibetan dried pork slice.</div></div>","PeriodicalId":34393,"journal":{"name":"Journal of Agriculture and Food Research","volume":"26 ","pages":"Article 102696"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pesticide handling practices, occupational risks, and health expenses among Bangladeshi smallholder vegetable farmers","authors":"Md. Shakhawat Hossain ,&nbsp;Shah Fahad ,&nbsp;Tanwne Sarker ,&nbsp;Md. Ghulam Rabbany ,&nbsp;Sabina Yeasmin ,&nbsp;Rana Roy","doi":"10.1016/j.jafr.2026.102727","DOIUrl":"10.1016/j.jafr.2026.102727","url":null,"abstract":"<div><div>Overlooking fundamental safety measures when applying pesticides in agriculture endangers farmers' health, increases healthcare expenses, and harms the environment. It's well-documented that Bangladeshi farmers use pesticides without taking enough precautions. Employing cross-sectional data, this study utilizes the theory of averting behavior model to assess pesticide handling practices, occupational hazards, and health expenditures among smallholder vegetable producers. While previous Bangladeshi studies focused solely on farmers' attitudes, knowledge, and practices regarding the use of pesticides, the current research identifies a critical gap and presents some new insights. The findings reveal that the application of safety equipment and pesticide container disposal methods was significantly influenced by farmers' investments in health and safety measures (P &lt; 0.05) and the health consequences (P &lt; 0.05) they faced. Farmers spent 4.21 US dollars per farm on health and safety measures against pesticide exposure during the 2023 vegetable season. Most farmers were unaware of properly managing pesticide equipment and disposal techniques for pesticide containers. The logit model results also reveal that farmers were more likely to adhere to precautionary measures and dispose of empty pesticide containers correctly as their age, educational level, and participation in the IPM (Integrated Pest Management) training program increased. These findings emphasize the need for practical IPM training and farmers' educational programs to ensure safe pesticide use. Findings can assist policymakers in understanding the reasons behind the improper application and disposal of pesticide containers. Moreover, the research suggests improved pesticide handling practices can boost sustainable agriculture and reduce health and occupational risks in Bangladesh.</div></div>","PeriodicalId":34393,"journal":{"name":"Journal of Agriculture and Food Research","volume":"26 ","pages":"Article 102727"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of machine learning based techniques for crop yield estimation of corn and cotton using multi-sensor data fusion","authors":"Mohammad Abdus Shahid Rafi ,&nbsp;Volkan Senyurek ,&nbsp;Ardeshir Adeli ,&nbsp;Huang Yanbo ,&nbsp;John E. Ball ,&nbsp;Ali C. Gurbuz","doi":"10.1016/j.jafr.2026.102676","DOIUrl":"10.1016/j.jafr.2026.102676","url":null,"abstract":"<div><div>Accurate crop yield estimation is crucial for decision-making and planning in modern agriculture with increasing challenges with food security. Yield predictions provide farmers with insights into expected production, facilitating optimized resource allocation, improved agricultural management strategies, and enhanced profitability. This study investigates the application of machine learning (ML) techniques, including Feedforward Neural Networks (FNN), Long Short-Term Memory (LSTM), and Random Forest (RF) models, for predicting crop yields using multi-sensory time-series data that has been collected on two fields over a four-year timeframe. The focus is on corn (<em>Zea mays</em>) and cotton (<em>Gossypium hirsutum</em>) yield, two of the top critical crops in Mississippi region. A multi-sensory dataset was collected using multispectral cameras and LiDAR sensors mounted on unmanned aircraft systems (UAS), along with soil moisture and temperature data from volumetric probes and environmental data from a nearby weather station. Over four years, more than 30 features were extracted weekly from five major categories, with 235 ground truth yield records from plots in the field. The study outlines the methodology for feature selection and examines its impact on yield prediction accuracy. Using percentile root mean square error (RRMSE) and mean absolute percentage error (MAPE) as performance metrics, the study found that the proposed LSTM model produced lower field-wise errors (9 − 21 % MAPE) compared to other models and validation, indicating superior performance in predicting yields across selected weeks. The proposed ML-based approach, validated through year-based and field-wise cross-validation methods, demonstrates the effectiveness of using UAS-collected multi-sensor data for accurate yield estimation in corn and cotton.</div></div>","PeriodicalId":34393,"journal":{"name":"Journal of Agriculture and Food Research","volume":"26 ","pages":"Article 102676"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Repurposing the human antiviral phytochemical drug, agathisflavone, for management of begomoviruses infecting plants","authors":"Mehulee Sarkar ,&nbsp;Firoz Mondal ,&nbsp;Dipsikha Mondal ,&nbsp;Shyam Kumar Gupta ,&nbsp;Yeluru Mohan Babu ,&nbsp;Anik Majumdar ,&nbsp;Supradip Saha ,&nbsp;Sneha Murmu ,&nbsp;Mahender Singh ,&nbsp;Girish Kumar Jha ,&nbsp;Bikash Mandal ,&nbsp;Anirban Roy","doi":"10.1016/j.jafr.2025.102624","DOIUrl":"10.1016/j.jafr.2025.102624","url":null,"abstract":"<div><h3>Background</h3><div>Begomoviruses are whitefly-transmitted circular single-stranded DNA viruses causing severe yield losses in economically important crops, particularly in tropical and subtropical regions. Current management strategies depend mainly on pesticide-based vector control and host resistance, which are limited by environmental concerns and frequent resistance breakdown due to rapid viral evolution. This study aimed to identify and validate a small-molecule inhibitor targeting the replication initiator protein (Rep) of tomato leaf curl New Delhi virus (ToLCNDV), a major begomovirus infecting tomato.</div></div><div><h3>Methods</h3><div>Fifteen plant-derived phytochemicals with reported antiviral activity against human viruses were screened <em>in silico</em> against the ToLCNDV Rep protein. Molecular docking and molecular dynamics simulations were used to evaluate binding affinity and stability, while protein–DNA docking assessed overlap between inhibitor-binding residues and the viral DNA-binding domain. As agathisflavone showed the most stable binding with Rep, it was isolated from cashew (<em>Anacardium occidentale</em>) leaves and formulated as an agathisflavone-enriched formulation (AGT-F). AGT-F was applied as a foliar spray and seed treatment, alone or in combination, under different inoculation regimes. Antiviral efficacy was assessed through symptom development, viral load estimation, and oxidative stress analysis.</div></div><div><h3>Results</h3><div>Agathisflavone emerged as the lead compound, showing high binding affinity (−8.6 kcal/mol) toward Rep and stable interaction during a 100 ns molecular dynamics simulation. Protein–DNA docking revealed overlapping residues between the agathisflavone-binding site and the viral DNA-binding domain of Rep. <em>In planta</em> studies showed delayed symptom development up to 20 days post-inoculation (dpi), compared to 8 dpi in control plants, and up to 99 % reduction in viral accumulation following combined seed treatment and foliar spray. AGT-F also reduced virus-induced oxidative stress and improved antioxidant status and seedling vigour.</div></div><div><h3>Conclusion</h3><div>This study demonstrates cross-kingdom repurposing of agathisflavone as a promising eco-friendly antiviral molecule targeting the Rep protein of ToLCNDV, providing a rational strategy for begomovirus disease management.</div></div>","PeriodicalId":34393,"journal":{"name":"Journal of Agriculture and Food Research","volume":"26 ","pages":"Article 102624"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145895945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of high temperature hot-air blanching pretreatment on the quality of shiitake mushrooms under different hot-air drying modes","authors":"Min Tan ,&nbsp;Ling Tang ,&nbsp;Yu Chen ,&nbsp;Hui Zeng ,&nbsp;Shaobin Fu ,&nbsp;Xiaogang Zhang","doi":"10.1016/j.jafr.2026.102652","DOIUrl":"10.1016/j.jafr.2026.102652","url":null,"abstract":"<div><div>The low input and easily controlled hot-air drying (HAD) is the most widely used drying technology, while the quality of shiitake mushrooms varied with different drying temperature or pretreatment modes, driving exploration of environmentally friendly drying strategy that is conducive to product quality. The focus of this study is the effects of high temperature hot-air blanching pretreatment (100 °C, 10 min) combined with different HAD-modes (constant temperature at 35 and 65 °C, and temperature gradient at 35–65 °C) on quality of shiitake mushrooms. Overall, high temperature hot-air blanching induced darker color and severe shrinkage, caused higher extent of browning and cross-linking and aggregation of proteins, and reduced the chemical antioxidant capacities in mushrooms. For unblanched samples, compared to those dried at constant temperature of 35 and 65 °C, the sample under temperature gradient at 35–65 °C (G) showed lower browning degree based on color index and the absorbance at 420 nm, and a better appearance was also observed. The higher chemical antioxidant capacities were observed in G containing higher contents of free amino group and total phenols. The protein molecular weights of G were mainly ranged at 50–70 kDa, and proteins below 50 kDa were also widely distributed. In addition, the amino acid patterns suggested G had high-quality protein, which was rich in free amino acids with sweetness and umami. Thus, hot-air blanching may not contribute to the quality of dried shiitake mushrooms, and temperature gradient HAD without blanching could be a practical approach for drying of shiitake mushrooms.</div></div>","PeriodicalId":34393,"journal":{"name":"Journal of Agriculture and Food Research","volume":"26 ","pages":"Article 102652"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global research hotspots and trends in polysaccharide anti-tumor therapy: A systematic bibliometric analysis and review","authors":"Yuyang Su ,&nbsp;Weiqing Qian ,&nbsp;Xiaohan Cao ,&nbsp;Hongying Wang ,&nbsp;Xiaocan Lei ,&nbsp;Weidong Gong ,&nbsp;Jialin Hu","doi":"10.1016/j.jafr.2026.102635","DOIUrl":"10.1016/j.jafr.2026.102635","url":null,"abstract":"<div><h3>Objective</h3><div>Polysaccharides, as natural bioactive macromolecules with anti-tumor potential, have become a research hotspot in the context of limited traditional cancer treatment methods. However, there is a lack of systematic reviews and clear delineation of future trends in this field regarding polysaccharide-based anti-tumor therapy. To fill this gap, this study aims to analyze the research hotspots and trends using bibliometric methods, providing support for promoting clinical translation.</div></div><div><h3>Method</h3><div>Relevant literature was retrieved from the Web of Science database, and key indicators such as annual publication volume, national/institutional collaboration models, and research hotspots were visually analyzed.</div></div><div><h3>Result</h3><div>The global publications on polysaccharide-based anti-tumor therapy have been on the rise. China, the United States, and India are the top three countries in terms of output. The research hotspots can be clustered into three major directions: “Polysaccharide-based nanocarriers and tumor-targeted delivery”, “Polysaccharide-mediated drug delivery systems and efficacy enhancement”, and “Polysaccharide anti-tumor mechanisms and tumor treatment effects”. Current research focuses on nanocarrier construction, targeted delivery mechanisms, and exploration of the anti-tumor activity of natural polysaccharides.</div></div><div><h3>Conclusion</h3><div>Research on polysaccharide-based anti-tumor therapy is steadily developing and has a cross-disciplinary characteristic. Based on the analysis of the research dynamics in this field, this study not only further validates and highlights the anti-tumor potential of polysaccharides, but also clearly indicates that future research will focus on precision medicine, combined treatment, and green synthesis technologies, providing key references for promoting clinical innovation and transformation in tumor treatment.</div></div>","PeriodicalId":34393,"journal":{"name":"Journal of Agriculture and Food Research","volume":"26 ","pages":"Article 102635"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145979564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing meteorological effects on crop yield and yield prediction through machine learning with different data partitioning approaches: A case study from Czech Republic","authors":"Bojana Petrovic ,&nbsp;Daniel Paluba ,&nbsp;Adenan Yandra Nofrizal ,&nbsp;Ales Kucera","doi":"10.1016/j.jafr.2026.102662","DOIUrl":"10.1016/j.jafr.2026.102662","url":null,"abstract":"<div><div>Climate change and increasing weather variability pose significant challenges to agricultural productivity, particularly in temperate regions. This study examines climate impacts on yields of barley, rapeseed, rye, and wheat across the Czech Republic (2016–2024) using meteorological data and evaluates three machine learning models (Random Forest, Gradient Boosting, Support Vector Regression) for yield prediction solely on meteorological variables. Three validation strategies were tested: random (70/30 %), spatial (region-based), and temporal (last three years). Random partitioning yielded the highest accuracy, but risks data leakage and is therefore not recommended for forecasting. Spatial partitioning showed low to moderate accuracy, suggesting ML approaches can partially interpolate yields in areas with no data (interpolation), particularly for barley and wheat. Temporal partitioning caused a substantial drop in predictive skill, producing unreliable forecasts for rye and rapeseed and indicating that meteorological data alone are insufficient for robust yield prediction. Support Vector Regression produced consistently negative R² values across all validation strategies, demonstrating fundamental model-task incompatibility. Wheat showed highest accuracy (random: 72.57 ± 7.19 %; spatial: 53.45 ± 19.31 %; temporal: 25.10 %), driven largely by Year (&gt;50 % importance). Without Year, spatial R² dropped to 0.2–27 %, confirming limited predictive power of meteorological variables alone. Crop climate analysis revealed distinct responses: rye was highly heat-sensitive, wheat and rapeseed benefited from late-season warmth, excess soil moisture during dormancy reduced rapeseed and wheat yields, and barley responded positively to stable warm conditions. These findings emphasize the importance of choosing an appropriate validation approach for yield prediction, depending on the intended task (interpolation or forecasting), as well as the value of feature interpretability. Key limitations include reliance on meteorology-only predictors without management or soil data, a small temporal test set (3 years, 42 observations per crop), and models' strong dependence on Year and Region features that limit operational forecasting utility.</div></div>","PeriodicalId":34393,"journal":{"name":"Journal of Agriculture and Food Research","volume":"26 ","pages":"Article 102662"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145979548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying and monetising externalities in Kenya's green bean value chain: implications for stakeholder and policy actions","authors":"Valiant O. Odhiambo ,&nbsp;Sheryl L. Hendriks ,&nbsp;Odirilwe Selomane","doi":"10.1016/j.jafr.2026.102639","DOIUrl":"10.1016/j.jafr.2026.102639","url":null,"abstract":"<div><div>Growing international demand for fresh green beans is driving producers in Kenya to expand and intensify crop production for export, creating negative environmental, health and social externalities (hidden costs). However, empirical evidence on the magnitude of these externalities remains limited. Estimating these externalities to reveal their magnitude could encourage stakeholder and policy actions that ensure a more environmentally sustainable, health-protective and socially equitable value chain. This study quantified and monetised negative environmental, health and social externalities in Kenya's green bean value chain. True cost accounting approaches, including life cycle assessment, disability-adjusted life years, the True Price methodology and the value of statistical life years, were used to analyse data from secondary sources. The total hidden costs were estimated at 124.03 million USD (range 115.93–132.20), at least twice the 53.92 million USD market value of green beans and almost three times the export value (42.15 million USD). Environmental externalities accounted for 86.87 million USD (range 79.16–94.65), driven mainly by scarce blue water use and greenhouse gas emissions. Health externalities accounted for 0.97 million USD (range 0.58–1.36), primarily from pesticide exposure. Social externalities (36.20 million USD) reflected a large living income gap among smallholder farming households and the presence of child labour. In conclusion, Kenya's green bean value chain creates substantial negative environmental, health and social externalities. There is a need for stakeholder and policy actions to internalise externalities in the value chain. The findings can guide stakeholders and policymakers in developing and implementing strategies to reduce externalities.</div></div>","PeriodicalId":34393,"journal":{"name":"Journal of Agriculture and Food Research","volume":"26 ","pages":"Article 102639"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time-series UAV multispectral imaging for HLB detection via improved U-Net under dynamic orchard environment","authors":"Haiyong Weng ,&nbsp;Hairong Luo ,&nbsp;Leilei Su ,&nbsp;Boyu Zhang ,&nbsp;Dawei Sun ,&nbsp;Liangquan Jia ,&nbsp;Dapeng Ye","doi":"10.1016/j.jafr.2026.102643","DOIUrl":"10.1016/j.jafr.2026.102643","url":null,"abstract":"<div><div>Citrus Huanglongbing (HLB) is the most devastating disease threatening citrus growth, posing a significant challenge to citrus cultivation due to its difficult cure and high transmissibility. Therefore, rapid detection and then removal of HLB infected trees is essential for orchard management. However, the complex and dynamic orchard environment often blocks HLB detection. Using time series analysis methods for large-scale monitoring of citrus orchards is uncommon. This study proposed a two-stage method for HLB detection utilizing time-series multispectral unmanned aerial vehicle (UAV) remote sensing images. The citrus canopy segmentation was carried out firstly using a proposed Canopy-Net with MIoU of 95.4 %, which minimized background interference due to dynamic orchard conditions caused by weed. To improve labeling efficiency of UAV-based HLB datasets, an auxiliary labeling strategy was proposed for 551 trees which only costed approximately 30 min by combining previous canopy segmentation outputs and plant polymerase chain reaction (PCR) results. Furthermore, RS-HLBNet was established for HLB detection in different seasons. It introduced a 2D-3D parallel convolution block in head to enhance spectral feature extraction. To resolve potential semantic mismatches in the original UNet, a CBDCA block was proposed to integrate multi-level skip connection features. The EUCB block further improved feature representation during upsampling. Finally, an MIoU of 88.5 % was achieved during the asymptomatic period (1st August) and 92.2 % in the symptomatic period (22nd November), respectively. In conclusion, this study demonstrated the capability of a time-series UAV multispectral imaging for the rapid HLB detection across orchard scale under dynamic orchard environment.</div></div>","PeriodicalId":34393,"journal":{"name":"Journal of Agriculture and Food Research","volume":"26 ","pages":"Article 102643"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of scientific communications on the acceptance of PFAS alternatives on disposable dinnerware and take-out containers, by information source","authors":"Alicia Rihn ,&nbsp;Pralhad Bajgain ,&nbsp;Nicole Labbé ,&nbsp;Gourav Kamboj","doi":"10.1016/j.jafr.2026.102646","DOIUrl":"10.1016/j.jafr.2026.102646","url":null,"abstract":"<div><div>Per- and polyfluoroalkyl substances (PFAS) are “forever chemicals” used as treatments on disposable dinnerware and take-out containers to improve their water and oil/grease resistance. They are currently being phased out of use, and alternative options are in development. The objective of this study is to assess how four different information sources (social media influencer, local news, university, and company) influence consumer acceptance of PFAS and PFAS-free alternative treatments. Each treatment presented identical scientific information about PFAS contamination, regulations, and risk mitigation strategies but was attributed to a different source. An online survey of 835 U S. consumers was conducted in 2024. Analysis of Variance (ANOVA) and pairwise t-tests identified significant differences across information sources. Generally, information from influencers was perceived as easier to understand than information from companies. Information from universities and influencers was perceived as more trustworthy than information from news or companies. Regardless of the information source, plant-based treatments were perceived as the most acceptable, followed by generic PFAS-free alternatives. Exposure to information decreased customer acceptance of PFAS, bio-based, and lignin treatments, while acceptance of PFAS-free alternatives improved acceptance. Company-provided information resulted in the largest decrease in PFAS acceptability (by 20.5 %), however this decline was not significantly different from the decreases observed in other information source treatments. Overall, our findings suggest that even brief, source-labeled communications can meaningfully shift consumer acceptance of PFAS alternatives. Importantly, familiar framings such as “plant-based” and “PFAS-free” resonate more strongly than technical terms like “lignin” and “bio-based,” offering a straightforward strategy for shaping public attitudes and supporting the adoption of safer materials.</div></div>","PeriodicalId":34393,"journal":{"name":"Journal of Agriculture and Food Research","volume":"26 ","pages":"Article 102646"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}