Measurement: Food最新文献

A theoretical-data-driven coupled model for drying history and shell formation of droplets with impermeable crust: Case study on oleaster low-fibrous extract 具有不透水外壳的液滴的干燥历史和壳形成的理论数据驱动耦合模型：以油棕低纤维提取物为例

IF 3.6

Measurement: Food Pub Date : 2025-09-14 DOI: 10.1016/j.meafoo.2025.100253

Sajad Jabari Neek, Mohammad Javad Ziabakhsh Ganji, Hojat Ghassemi

{"title":"A theoretical-data-driven coupled model for drying history and shell formation of droplets with impermeable crust: Case study on oleaster low-fibrous extract","authors":"Sajad Jabari Neek, Mohammad Javad Ziabakhsh Ganji, Hojat Ghassemi","doi":"10.1016/j.meafoo.2025.100253","DOIUrl":"10.1016/j.meafoo.2025.100253","url":null,"abstract":"<div><div>The drying history and shell formation of droplets, particularly those forming an impermeable crust, are critical for optimizing various industrial processes. This study introduces a novel theoretical model enhanced by machine learning principles to investigate the drying of single droplets, using oleaster (Elaeagnus angustifolia L.) low-fibrous extract (OLFE) as a representative case. Experimentally informed learning-based conditions are integrated within the theoretical framework to predict key drying behaviors, including shell formation and inflation., addressing the challenges posed by high sugar content and elastic crust properties. Experimental validation demonstrated the model’s high accuracy in predicting key drying kinetics, including droplet diameter, drying time, and crust dimensions under varying conditions. Key findings reveal that higher ambient temperatures expedite drying and lead to earlier shell formation, while larger initial droplet diameters prolong drying time and result in thicker final shells. Conversely, higher initial concentrations enhance crust impermeability and strength, offering valuable insights into particle design for encapsulation and drying applications. This model bridges the gap between theoretical prediction and experimental complexity utilizing a 6-condition shell evolution model, providing a powerful tool to optimize drying processes with reduced reliance on extensive experimental trials. Its applicability extends to a wide range of materials, offering enhanced control over product quality and efficiency in spray drying and related technologies.</div></div>","PeriodicalId":100898,"journal":{"name":"Measurement: Food","volume":"20 ","pages":"Article 100253"},"PeriodicalIF":3.6,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100053","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}

引用次数: 0

Effects of cooking methods on the elements concentrations in meats: Implications for dietary risk assessment 烹调方法对肉类中元素浓度的影响：对饮食风险评估的影响

IF 3.6

Measurement: Food Pub Date : 2025-09-03 DOI: 10.1016/j.meafoo.2025.100248

C.C. Augusto , W.D. Ascenção , T. Pedron , H.F. Maltez , B.A. Rocha , B.L. Batista

{"title":"Effects of cooking methods on the elements concentrations in meats: Implications for dietary risk assessment","authors":"C.C. Augusto , W.D. Ascenção , T. Pedron , H.F. Maltez , B.A. Rocha , B.L. Batista","doi":"10.1016/j.meafoo.2025.100248","DOIUrl":"10.1016/j.meafoo.2025.100248","url":null,"abstract":"<div><div>The process of cooking meat induces chemical and physical transformations, including decreasing the contents of volatile compounds and water loss, thereby concentrating less-volatile compounds. Regarding chemical elements (CEs), the literature has primarily focused on their concentrations in raw meat. Thus, studies investigating changes in CE concentrations in cooked meat, particularly those using modern techniques such as air frying, are limited. In this study, 14 CEs (As, Cd, Pb, Hg, Co, Cu, Fe, Mg, Mn, K, Se, Na, P, and Zn) in beef, fish, and shrimp meats before and after cooking using muffling, roasting, or air frying were examined for a health risk assessment. Hg concentrations were consistently below the instrumental limit of quantification across all samples and cooking methods. The air-frying method demonstrated the highest decreases in concentrations of potentially toxic elements. For example, As, Cd, and Pb concentrations decreased by 40 %–80 %. Essential elements (EEs), such as Cu and Zn, also decreased in concentration by 20 %–50 %. The estimated daily intake and hazard index values revealed that consuming air-fried meat samples reduced the non-carcinogenic risk by up to 76 % compared to that for raw samples. Thus, considering the cooking method is essential for food safety evaluations and accurate dietary risk assessments. Moreover, among all the tested cooking methods, air frying emerged as the most effective in minimizing toxic exposure without compromising the availability of EEs. This study contributes to understanding the factors affecting food safety is essential for improving global public health</div></div>","PeriodicalId":100898,"journal":{"name":"Measurement: Food","volume":"20 ","pages":"Article 100248"},"PeriodicalIF":3.6,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050505","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}

引用次数: 0

ML-driven olive oil quality prediction: Comparative evaluation of FTMIR data preprocessing techniques using RF and XGBoost models in multi-stage validation 机器学习驱动的橄榄油质量预测：在多阶段验证中使用RF和XGBoost模型对FTMIR数据预处理技术的比较评估

IF 3.6

Measurement: Food Pub Date : 2025-09-01 DOI: 10.1016/j.meafoo.2025.100249

Lahcen Hssaini

{"title":"ML-driven olive oil quality prediction: Comparative evaluation of FTMIR data preprocessing techniques using RF and XGBoost models in multi-stage validation","authors":"Lahcen Hssaini","doi":"10.1016/j.meafoo.2025.100249","DOIUrl":"10.1016/j.meafoo.2025.100249","url":null,"abstract":"<div><div>This study evaluates the impact of four mid-FTIR spectral preprocessing strategies—baseline correction, normalization, smoothing, first derivative transformation, all compared to raw data—on the performance of Random Forest (RF) and XGBoost (XGB) models for predicting key olive oil quality parameters mainly total phenolic content (TPC), total flavonoid content (TFC), DPPH radical scavenging activity, and carotenoid levels in the Picholine Marocaine cultivar. Using a dataset of 324 olive oil samples, models were trained and validated via a multi-stage framework (5-fold CV and 20 % external validation). Results revealed that smoothing significantly enhanced TPC prediction (XGB R² = 0.96, RMSE = 24.5 mg GAE/kg) while first derivative transformation optimized TFC prediction (R² = 0.93, RMSE = 18.2 mg QE/kg). Raw data sufficed for carotenoids (R² > 0.89). XGBoost consistently outperformed RF by 7–15 % across parameters due to its superior regularization capabilities. Notably, blind testing exposed a 25 % R² drop for DPPH with RF, underscoring the necessity of external validation. These findings support the development of rapid, non-destructive quality assessment tools with applications in industrial quality control, authentication systems, and regulatory compliance. Future research should explore hybrid preprocessing combinations, deep chemometric feature extraction, multi-cultivar validation, and seasonal model transferability to enhance robustness and commercial viability.</div></div>","PeriodicalId":100898,"journal":{"name":"Measurement: Food","volume":"19 ","pages":"Article 100249"},"PeriodicalIF":3.6,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145018627","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}

引用次数: 0

Prediction of sugar content in Java Plum using SW-NIR spectroscopy with CNN-LSTM based hybrid deep learning model 基于CNN-LSTM混合深度学习模型的SW-NIR预测爪哇李子含糖量

IF 3.6

Measurement: Food Pub Date : 2025-09-01 DOI: 10.1016/j.meafoo.2025.100246

M. Mirazus Salehin , Md. Rahber Islam Rafe , Al Amin, Kazi Shakibur Rahman, Md. Rakibul Islam Rakib, Sahabuddin Ahamed, Anisur Rahman

{"title":"Prediction of sugar content in Java Plum using SW-NIR spectroscopy with CNN-LSTM based hybrid deep learning model","authors":"M. Mirazus Salehin , Md. Rahber Islam Rafe , Al Amin, Kazi Shakibur Rahman, Md. Rakibul Islam Rakib, Sahabuddin Ahamed, Anisur Rahman","doi":"10.1016/j.meafoo.2025.100246","DOIUrl":"10.1016/j.meafoo.2025.100246","url":null,"abstract":"<div><div>Sugar content is the most important parameter for consumer acceptance and post-harvest management of Java Plum (<em>Syzygium cumini L</em>.). Traditional methods for sugar content analysis are often time-consuming and labor-intensive. The short wave-near infrared (SW-NIR) spectroscopy offers a rapid and non-destructive alternative for assessing sugar content in fruits. In this study proposed a Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) based hybrid deep neural network model and partial least square regression (PLSR) algorithm for predicting sugar content in Java Plum using SW-NIR spectroscopy. The proposed model combines the strengths of CNN-LSTM to capture sequential dependencies of SW-NIR data in the ranges of 900–1700 nm. The hybrid model is made of 17 layers of neural network and consists of 1D-CNN, LSTM, GroupNormalization and Regularizer layers. At first, the spectra data was preprocessed using several preprocessing techniques independently and developed PLSR model to select the best preprocessing technique. The Savitsky-Golay 2nd derivative preprocessing spectra yielded the most optimum result for PLSR model with coefficient of calibration <span><math><msub><mi>R</mi><mrow><mi>c</mi><mi>a</mi><mi>l</mi></mrow></msub></math></span> = 0.677 and coefficient of prediction <span><math><msub><mi>R</mi><mrow><mi>p</mi><mi>r</mi><mi>e</mi><mi>d</mi></mrow></msub></math></span> = 0.554 The proposed CNN-LSTM-based hybrid deep learning model showed the <span><math><msub><mi>R</mi><mrow><mi>c</mi><mi>a</mi><mi>l</mi></mrow></msub></math></span> = 0.843 and <span><math><msub><mi>R</mi><mrow><mi>p</mi><mi>r</mi><mi>e</mi><mi>d</mi></mrow></msub></math></span> = 0.83. The results demonstrated the potential of SW-NIR spectroscopy combined with CNN-LSTM-based hybrid deep learning model for determination of soluble sugar content in Java plum.</div></div>","PeriodicalId":100898,"journal":{"name":"Measurement: Food","volume":"19 ","pages":"Article 100246"},"PeriodicalIF":3.6,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048568","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}

引用次数: 0

Effect of plasma-modified rice starch on physicochemical and sensory properties of cheese 血浆改性大米淀粉对奶酪理化及感官特性的影响

IF 3.6

Measurement: Food Pub Date : 2025-09-01 DOI: 10.1016/j.meafoo.2025.100250

Bara Yudhistira , Adila Rifa Mutia , Riyanti Ekafitri , Ahmad Ni’matullah Al-Baarri , Putri Widyanti Harlina , Fuangfah Punthi , Novita Indrianti , Lia Ratnawati , Achmat Sarifudin , Maulana Furqon , Dayu Dian Perwatasari

{"title":"Effect of plasma-modified rice starch on physicochemical and sensory properties of cheese","authors":"Bara Yudhistira , Adila Rifa Mutia , Riyanti Ekafitri , Ahmad Ni’matullah Al-Baarri , Putri Widyanti Harlina , Fuangfah Punthi , Novita Indrianti , Lia Ratnawati , Achmat Sarifudin , Maulana Furqon , Dayu Dian Perwatasari","doi":"10.1016/j.meafoo.2025.100250","DOIUrl":"10.1016/j.meafoo.2025.100250","url":null,"abstract":"<div><div>Processed cheese is a milk-based product that is widely consumed because it has a longer shelf life, stable texture, and adjustable taste. However, stabilizers are needed to improve its physicochemical and sensory characteristics. Rice starch can be a potential alternative as a natural stabilizer in processed cheese, but it has limitations such as low viscosity and retrogradation tendencies. This study aims to examine the effect of rice starch modified with dielectric barrier discharge (DBD) plasma on the physicochemical and sensory characteristics of processed cheese. Rice starch was extracted and modified using DBD plasma at 10 kV for 20 min to improve its functional properties. The modified starch was then applied to processed cheese with varying concentrations (4 %, 7 %, 10 %, 13 %, and 16 %). The analysis carried out included amylose content, pasting properties, hydration properties, texture, and sensory tests. DBD samples showed a swelling power reduction of 18.97 %, and an enhancement in amylose and solubility levels of 7.01 % and 31.77 %, respectively, compared to untreated samples. The application of 4–16 % DBD starch showed a cheese sample with an increase in hardness of 21.14 % and a decrease in water content of 4.14 %, ash of 47.76 %, fat of 16.40 %, protein of 16.52 %, and carbohydrate of 47.03 %. Sensory testing showed that the formulation with 10 % modified starch had the best acceptance by panelists. DBD plasma-modified rice starch has the potential as a natural stabilizer in processed cheese, offering an alternative for the food industry that is more environmentally friendly and healthy.</div></div>","PeriodicalId":100898,"journal":{"name":"Measurement: Food","volume":"19 ","pages":"Article 100250"},"PeriodicalIF":3.6,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048567","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}

引用次数: 0

Optimising QuEChERS method for determining five amanita peptide toxins in mixed wild mushrooms 优化QuEChERS法测定混合野生蘑菇中五种毒伞菌肽毒素的方法

IF 3.6

Measurement: Food Pub Date : 2025-09-01 DOI: 10.1016/j.meafoo.2025.100247

JiYan Duan , Yan Zhang , QiXin Guo , YuYuan Huang , Xing Xu

{"title":"Optimising QuEChERS method for determining five amanita peptide toxins in mixed wild mushrooms","authors":"JiYan Duan , Yan Zhang , QiXin Guo , YuYuan Huang , Xing Xu","doi":"10.1016/j.meafoo.2025.100247","DOIUrl":"10.1016/j.meafoo.2025.100247","url":null,"abstract":"<div><h3>Introduction</h3><div>This study establishes an optimised quick, easy, cheap, effective, rugged and safe (QuEChERS) method integrated with high-performance liquid chromatography–tandem mass spectrometry for detecting five amatoxins in wild mushrooms.</div></div><div><h3>Methods</h3><div>Samples were ultrasonically extracted using a methanol-water mixture and purified using an adsorbent. The separation of the five amatoxins was performed in a C<sub>18</sub> column using 5-mmol/L ammonium formate solution (0.1 % formic acid) and acetonitrile as the mobile phases. The five peptide toxins exhibit a remarkable linear relationship in the range of 10–500 μg/L.</div></div><div><h3>Results</h3><div>The limits of detection and quantification were 8–13 and 26–42 μg/kg, respectively. Moreover, recoveries ranged from 80.1 % to 120.3 %. The peptide toxin can still be detected in a mixed sample containing positive and negative samples.</div></div><div><h3>Conclusion</h3><div>This method is simple, accurate and suitable for detecting amatoxins in mixed wild mushrooms. It holds significant potential for addressing wild mushroom poisoning incidents and enhancing food safety regulation.</div></div>","PeriodicalId":100898,"journal":{"name":"Measurement: Food","volume":"19 ","pages":"Article 100247"},"PeriodicalIF":3.6,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004280","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}

引用次数: 0

Optical gas sensors in smart food bio-packaging: Innovation for monitoring the product freshness and safety 智能食品生物包装中的光学气体传感器：监测产品新鲜度和安全性的创新

IF 3.6

Measurement: Food Pub Date : 2025-08-08 DOI: 10.1016/j.meafoo.2025.100245

Sarah Siciliano, Catia Giovanna Lopresto, Domenico Luca Carnì, Francesco Lamonaca

引用次数: 0

Quantitative analysis of pesticides in vegetables: A study on tomatoes and onions from Ethiopian farms 蔬菜中农药的定量分析：埃塞俄比亚农场番茄和洋葱的研究

Measurement: Food Pub Date : 2025-07-19 DOI: 10.1016/j.meafoo.2025.100242

Bezuayehu Tadesse , Melese Asrat , Balkew Zewge , Asmamaw Tesfaw

{"title":"Quantitative analysis of pesticides in vegetables: A study on tomatoes and onions from Ethiopian farms","authors":"Bezuayehu Tadesse , Melese Asrat , Balkew Zewge , Asmamaw Tesfaw","doi":"10.1016/j.meafoo.2025.100242","DOIUrl":"10.1016/j.meafoo.2025.100242","url":null,"abstract":"<div><div>Vegetables are crucial for a healthy diet, but they can be exposed to pesticides throughout the growing process. This study investigated pesticide residues in tomatoes and onions using the QuEChERS extraction method and gas chromatography with an electron capture detector (GC-ECD). Samples from Ziway, Shewa Robit, Majete, and Meki regions were analyzed for pesticide residues, including organophosphates (OPPs), organochlorines (OCPs), and synthetic pyrethroids. Calibration curves demonstrated linearity (r² ≥ 0.9962), and recoveries ranged from 81–114 %, indicating analytical precision and accuracy. Findings showed high pesticide levels, especially those of malathion (112–286 µg/kg) and chlorpyrifos (53–153 µg/kg), with some values surpassing the FAO/WHO and European Union maximum residue limits (MRLs), even if the majority of pesticides were at safe levels. Pesticide residues in tomatoes were below MRLs, while chlorpyrifos and malathion levels in onions surpassed these limits, presenting health risks and impacting market access. The report emphasizes the necessity of strict pesticide control and ongoing oversight to safeguard public health and promote agricultural exports.</div></div>","PeriodicalId":100898,"journal":{"name":"Measurement: Food","volume":"19 ","pages":"Article 100242"},"PeriodicalIF":0.0,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704552","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}

引用次数: 0

Proximate, mineral, and anti-nutrient compositions of selected wild edible plants consumed in Northwestern Ethiopia 埃塞俄比亚西北部食用的选定野生可食用植物的近似、矿物和抗营养成分

Measurement: Food Pub Date : 2025-07-18 DOI: 10.1016/j.meafoo.2025.100243

Daniel Tadesse , Getinet Masresha , Ermias Lulekal , Paulos Getachew , Tilahun Belayneh

{"title":"Proximate, mineral, and anti-nutrient compositions of selected wild edible plants consumed in Northwestern Ethiopia","authors":"Daniel Tadesse , Getinet Masresha , Ermias Lulekal , Paulos Getachew , Tilahun Belayneh","doi":"10.1016/j.meafoo.2025.100243","DOIUrl":"10.1016/j.meafoo.2025.100243","url":null,"abstract":"<div><div>Wild edible plants (WEPs) are essential food and nutritional sources in low-income countries like Ethiopia. Despite their significance, limited research exists on their nutritional profiles. Five WEPs from northwestern Ethiopia were analyzed for proximate, mineral, and antinutrient compositions using standard food analysis methods. Nutritional variation was assessed using one-way ANOVA. Nutrient ranges were moisture (6.14–10.48 %), crude protein (2.55–23.14 %), crude fat (0.67–4.00 %), crude fiber (4.18–14.42 %), crude ash (3.05–12.05 %), carbohydrate (43.21–77.96 %), and gross energy (282.92–347.42 kcal/100 g). Mineral content (mg/100 g dry weight) included Mg (87.96–473.24), K (661.09–2147.23), Ca (158.43–1000.63), P (152.91–426.88), Na (trace amounts), Fe (7.70–22.07), Zn (0.30–3.55), Cu (0.63–1.37), and Mn (trace to 2.67). Anti-nutrient levels (mg/100 g) were 80.78–168.99 for phytate, 281.99–936.83 for tannin, and 609.29–945.45 for oxalate. Molar ratios for antinutrients and minerals were below critical thresholds, indicating favorable bioavailability in <em>Abelmoschus ficulneus</em> and <em>Corchorus olitorius</em>. Results suggest that these WEPs, particularly <em>Abelmoschus ficulneus</em> and <em>Corchorus olitoriu</em>s, offer substantial nutrients to address deficiencies. Sustainable conservation, increased consumption, and domestication of these WEPs could supplement common crops and reduce malnutrition in Ethiopia.</div></div>","PeriodicalId":100898,"journal":{"name":"Measurement: Food","volume":"19 ","pages":"Article 100243"},"PeriodicalIF":0.0,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704550","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}

引用次数: 0

Authentication of avocado oil mixed with cooking oils (branded and loose palm oil) utilizing fourier transform infrared spectroscopy in conjunction with chemometrics 利用傅里叶变换红外光谱与化学计量学相结合，对牛油果油与食用油（品牌和松散棕榈油）混合进行认证

Measurement: Food Pub Date : 2025-07-09 DOI: 10.1016/j.meafoo.2025.100241

David Fernando , Desy Ayu Irma Permatasari , Agustina Ari Murti Budi Hastuti , Abdul Rohman

{"title":"Authentication of avocado oil mixed with cooking oils (branded and loose palm oil) utilizing fourier transform infrared spectroscopy in conjunction with chemometrics","authors":"David Fernando , Desy Ayu Irma Permatasari , Agustina Ari Murti Budi Hastuti , Abdul Rohman","doi":"10.1016/j.meafoo.2025.100241","DOIUrl":"10.1016/j.meafoo.2025.100241","url":null,"abstract":"<div><div>Avocado oil (AVO) has become popular for its health advantages and culinary variety, while its elevated cost has rendered it susceptible to adulteration practices, frequently with less expensive edible oils such as palm oil. Attenuated total reflectance-fourier transform infrared spectroscopy (ATR-FTIR) in conjunction with chemometrics is a promising way to quickly, rapidly, and non-destructively detect AVO adulterated with branded palm oil (BPO) or loose palm oil (LPO). AVO can be distinctly categorized apart from BPO and LPO using FTIR analysis corroborated by principal component analysis (PCA). Principal component (PC) 1 is primarily influenced by absorption at a wavenumber of 1743 cm⁻¹, whereas PC2 is impacted by absorption at a wavenumber of 2953 cm⁻¹. With first derivative data and multiplicative scatter correction (MSC), multivariate calibration of principal component regression (PCR) was able to correctly predict the amount of BPO in AVO. This approach yielded root mean squared error of calibration (RMSEC) and root mean square error for prediction (RMSEP) values of 0.56 and 0.55, alongside coefficient of determination for the calibration and prediction model (R²-cal and R²-val) values of 0.9998 and 0.9999, respectively. In addition, PCR using first-derived data without MSC adjustment accurately quantified BPO levels in AVO, with RMSEC and RMSEP values of 0.60 and 0.61, respectively, along with R²-cal and R²-val values of 0.9998. This PCA-based discriminant analysis correctly separated the real AVO samples from the adulterated AVO samples with classification accuracies of 98.18 % for BPO and 100 % for LPO. This method may also be applicable further for detecting other possible edible oil adulteration, including soybean oil, rapeseed oil, and sunflower oil.</div></div>","PeriodicalId":100898,"journal":{"name":"Measurement: Food","volume":"19 ","pages":"Article 100241"},"PeriodicalIF":0.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144672192","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}

引用次数: 0