Journal of Food Measurement and Characterization最新文献

Native huauzontle protein (P_native) structure was modified by thermal (P_heat), ultrasound (P_US) and pH shifting (P_pH11). Soluble complexes (SC) were formed between the huauzontle proteins and a commercial octenyl succinic anhydride modified starch (S). The secondary structure of the native and modified huauzontle proteins differed in terms of abundance of β-sheet, α-helix, and β-turn structures. The pH at which maximum presence of SC was observed varied from 5.1 for P_native-S to 5.8 for P_us-S complexes, and being the required protein: polysaccharide weight ratio of 1:1 for P_native-S and of 1:2 for the modified proteins-S. FT-IR confirmed the formation of SC, as the characteristic carboxylate group in S disappeared from its spectra. Also, the absorption peaks of the proteins in the Amide I and II bands shifted slightly from 1630 to 1635 cm^− 1 and 1520 to 1510 cm^− 1 in the SC, indicating conformational changes due to protein-starch interactions. Aggregation of the biopolymers into relatively large particles was observed by SEM in the SC made with modified proteins. SC showed significant differences in the in vitro protein digestibility values, the lowest (85.1 ± 2.3%) occurring for P_native-S and the highest (92.7 ± 0.7%) for P_US-S. P_pH11-S presented the highest resistant starch content (92.6 ± 0.4%). It is concluded that the modification of P_native through heat, ultrasound and pH shifting allowed establishing different driving conditions for the formation of SC with S, and in vitro digestibility of protein and starch could also be modified. The improved nutritional properties of SC through modification of the protein structure make them potential ingredients for the formulation of sports drinks or low-calorie dairy products.

Calcium chloride treatment is an effective preservative that is widely utilized for the purpose of maintaining the quality of harvested fruits. A 5% calcium chloride solution was utilized for the soaking of postharvested passion fruit stored under ambient conditions for a period of eight days. The textural properties, pectins, hemicellulose content, and enzyme activities in passion fruit peels were determined through a series of analytical procedures. These enzymes were found to be involved in the carbohydrate metabolism of the fruit peels. Furthermore, the data were subjected to correlation determination and principal component analysis. The findings demonstrated that the calcium ion treatment preserved the firmness, elasticity, glutenability, cohesion, resilience, and chewiness of passion fruit while regulating the alterations in pectin and hemicellulose content observed in the treated fruit peels. The treatment also resulted in a reduction in the activities of cell wall-metabolizing enzymes within the fruit peel, leading to a slowing down of the degradation of cell wall materials. The corresponding activities of polygalacturonase, pectin methylesterase, cellulase, and β-galacturonase in the fruit peels were found to be reduced following the treatment. It can therefore be concluded that the calcium chloride treatment is an effective method of maintaining the quality of passion fruit by regulating the carbohydrate metabolism in the fruit peels and achieving a fruit preservation effect.

In this research, ozone gas was used at concentrations of 2 and 5ppm in different stages of brined ultrafiltered cheese production and then the samples were subjected to microbial and chemical (protein, pH 4.6-SN/TN, TCA-SN/TN, PTA-SN/TN, fat, monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA)) analyses during ripening. Ozone treatments included: ozonation of concentrate simultaneously with starter inoculation (OA), ozonation of concentrate before starter inoculation (OB), ozonation of concentrate and brine (OC), ozonation of brine (OD) and control (C). Based on the results, the values of the cheese proteolysis products (pH 4.6-SN/TN, TCA-SN/TN, and PTA-SN/TN) and their protein and fat contents significantly (p ≤ 0.05) increased and decreased, respectively, over the ripening period. The level of MUFA also experienced a significant (p ≤ 0.05) decrease until day 35 of the ripening, followed by an increase until the end of the ripening period. The highest levels of pH 4.6-SN/TN, TCA-SN/TN, and PTA-SN/TN were associated with samples OB5, OC5, and OC5, respectively, whereas the control exhibited the lowest values for these parameters. The fat content of the OA5 sample was significantly (p ≥ 0.05) lower than other samples. On most ripening days, ozonation of the samples did not significantly change their MUFA levels. The PUFA content of the treated samples was also variable on different treatment days. The counts of mold and yeast initially increased until day 70 but subsequently decreased until the end of the ripening period. Throughout the ripening period, the mold and yeast counts of the OA5 and OC5 samples were significantly (p ≤ 0.05) lower than the other treatments. As a result, the use of ozone treatment increased the shelf life of the cheese samples and also enhanced the production of products resulting from proteolysis.

The visible/near-infrared (Vis/NIR) spectroscopy technique is effective for fruit quality detection. The distinct spectral features can reflect the internal composition of fruits, while variations in external orientation may induce interference. Considering both external and internal factors, we improved the discrimination accuracy of pest-infested crabapples by compensating for variations in orientation and amplifying differences in spectral morphological features (SMFs). Firstly, spectral intensity variations caused by orientations and morphological differences caused by pest infestation were analyzed. Based on these differences, the global model was established to mitigate the external orientation influence. Subsequently, SMFs, derived from spectral peaks and troughs, were employed to amplify spectral features. Finally, with the supplementation using 1^st deviation, SMFs improved the discrimination performance of the partial least square–linear discriminant analysis (PLS-LDA) model for pest infestation, yielding results of sensitivity, specificity, and accuracy as 95.14%, 96.32%, and 95.94%, respectively. Overall, compensating for external orientation variations and exploiting internal spectral features enhanced the detection accuracy of pest infestation, providing valuable insights for internal defect discrimination based on Vis/NIR spectroscopy.

Mexico is one of the main countries in the production and exportation of bell pepper (Capsicum annuum) hence, emerging techniques to monitor and assess quality parameters postharvest is a constant topic of interest. On the other hand, color image processing is a non-invasive technique that is gaining popularity in the agro-industrial sector. Color analysis helps as an indirect or correlation measure to quantify and qualify visual quality attributes (size, shape, maturity, etc.) and even non-visual ones such as flavor. Recent techniques involve a pre-processing of the information (changing the RGB space into another) in order to obtain the chromaticity and luminescence parameters that point to the characterization of the physicochemical profile; this stage may present a loss of information. Therefore, this work presents the use of Quaternion Algebra for the management of information as a single entity, avoiding the pre-processing stage. The image is transformed into a pure quaternion; processed using the Fast Fourier Transform described in Quaternions. Image acquisition is carried out using any mobile device or low-cost sensor, which provides an advantage over other proposals. The results show that the determination of physical measurements such as length, width and thickness are characterized according to pre-established standards. In addition, we identify the state of maturity; as well as areas in which damage or injuries are found. The validation of the results obtained was done in consideration of Good Management Practices as well as, the state of the art having a high agreement with them.

The effect of partial whole wheat flour substitution by quinoa flour (QF) and defatted apple seed flour (DASF) on the nutritional, antioxidant and sensory properties of gingerbread cookies was studied. Four cookies were prepare with 10% quinoa flour, and three of them contained DASF in three different ratios: 5%, 10% and 15%. They were compared with a control cookie made from 100% whole wheat flour. To predict the functionality of composite flours, the assessment of their technological properties was conducted. Water holding capacity increased, but oil holding and swelling capacity did not change by the addition of DASF to gingerbread cookies. Solvent retention capacity tests revealed an increase in retention of water, lactic acid and sucrose solutions while retention of sodium carbonate decreased by the addition DASF to composite flours compared to the control. Proximate composition analysis suggested that the use of DASF increased lipid and crude fibre content in 15% DASF cookies while protein, ash, total carbohydrates and energy values were unchanged in all tested samples. Analysis of total phenolic, flavonoid and dihydroxycinnamic derivative content in gingerbread cookies extracts indicated that phenolic acids were the main extract constituents and mostly contributed to their antioxidant properties. Antioxidant tests showed that enrichment of gingerbread cookies with DASF improved their antioxidant properties, especially DPPH radical scavenging activity. Sensory analysis revealed that the DASF and quinoa enriched gingerbread cookies were in the category of excellent quality (overall sensory quality 4.91).

Graphical Abstract

The current investigation addresses the pressing need to integrate orphan or underutilized crops into mainstream agriculture, focusing on Perilla (Perilla frutescens L.) due to its superior nutritional profile. A major challenge is the lack of fast, cost-effective, and labor-efficient screening methods for germplasm. Near-Infrared Reflectance Spectroscopy (NIRS) addresses this by providing precise and rapid determination of crucial biochemical parameters. This study developed Modified Partial Least Squares (mPLS) regression-based NIRS prediction models using WinISI and 1D Convolutional Neural Networks (CNN) to enable high-throughput screening for moisture, ash, proteins, total soluble sugars (TSS), and phenols in Perilla germplasm. Calibration with WinISI involved mathematical treatments, optimizing for each trait: “2,6,6,1” for moisture, “3,4,4,1” for ash and TSS, “3,4,6,1” for protein, and “2,4,6,1” for phenols. The 1D CNN model, with lower mean absolute error (MAE), was further validated. External validation metrics, including RSQexternal, SEP(C), slope, bias, and RPD, assessed prediction accuracy. Comparative evaluation showed WinISI performed better for moisture prediction, while the 1D CNN model excelled in predicting ash, protein, TSS, and total phenol, highlighting the importance of model selection for specific traits. This rapid screening tool aids in identifying nutritionally dense Perilla genotypes, guiding targeted breeding efforts, and represents the first comparative mPLS and DL-based modeling using NIRS data for Perilla.