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Abstract: Abstract A novel method to evaluate rice drying method was investigated based on water migration and molecular motion law analysis. Three typical drying methods were selected, including continuous constant temperature drying at 50 °C (CCTD), constant temperature drying at 50 °C combined with tempering at 50 °C (CTD-T), and constant temperature drying at 50 °C combined with tempering at 65 °C (CTD-HT). Before sample analysis, single-husked rice was cut into four parts equally with its central axis. During rice drying, the smallest cytoplasmic viscosity (1.28 × 10−10 poise) was observed in CTD-HT samples, compared with CCTD (1.45 × 10−10 poise) and CTD-T (1.36 × 10−10 poise) samples, which resulted in the highest drying efficiency of CTD-HT. After rice drying, the smallest moisture gradients (only 1.25%) between adjacent parts of rice and the lower molecular mobility were found in CTD-HT samples, which gave rise to the highest physicochemical, texture, and storage quality of dried rice. Optimal drying method can be identified quickly and accurately as CTD-HT. Reliability and accuracy of the evaluation method were confirmed by the classic methods. PubDate: 2023-12-02
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Abstract: Abstract The mold contamination caused by Aspergillus flavus poses a serious threat to food safety. In this study, three artificially inoculating strains of Aspergillus flavus (A. flavus 142,801, A. flavus 142,803, A. flavus 336,156) were used to infect two healthy peanut varieties (variety A: GS1210, variety B: fengyingluohan) kernels. These healthy and Aspergillus flavus-infected peanut kernels were identified and differentiated by using a line-scan Raman hyperspectral imaging system. Firstly, the average spectra of healthy and infected peanuts were extracted, followed by preprocessing using Savitzky-Golay smoothing and airPLS for fluorescence background removal. Finally, four feature variable selection methods were used to optimize the models. In the binary classification model (healthy vs. A. flavus), the SVM method yielded the best modeling results, with accuracy above 99%. The best accuracy achieved in the three-classification model for mold on variety A peanut was 88.9%, and for variety B, it was 92.4%. In the model for mold on a mixture of both varieties, the highest accuracy reached was 74.8%. The results show that line-scan Raman hyperspectral imaging technology is practical in identifying healthy and Aspergillus flavus-infected peanut kernels. Moreover, this technique has great potential in identifying different Aspergillus flavus of a single peanut variety and provides a feasible method for fungal species identification. PubDate: 2023-11-29
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Abstract: Abstract The present study aimed to build calibration models based on smartphone digital images to estimate bananas and papayas’ sensory and physicochemical characteristics at different ripening stages. Three distinct image processing were evaluated: (i) the average red, green, and blue (RGB) values of the entire image, (ii) the number of pixels in each RGB value (the RGB histogram), and (iii) a reflectance spectrum mathematically obtained from the RGB triplet. Each approach was modeled with either multiple linear regression (MLR) or partial least squares (PLS) regression. The predicted variables were the sensory characteristics of ideal sweetness, ideal firmness, and global acceptance, and the physicochemical characteristics of total soluble solids (TSS) and firmness. The models obtained good responses for sensory and instrumental parameters, with the best being the modeled from the reflectance spectrum. The uniqueness of the obtained reflectance spectra captured the color changes throughout the fruit ripening. Furthermore, the obtained spectra allowed for data pre-treatments to be employed, leading to high R2 > 0.9 and low error measured by external validation. Each modeled variable had a better performance with a specific pre-treatment. Therefore, the adoption of reflectance spectra from smartphone digital images led to a promising option to improve models’ predictive performance, especially to assess fruit quality parameters. PubDate: 2023-11-28
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Abstract: Abstract In China, herbal drinks possess long-standing traditional cultural characteristics cater to consumers’ demand for both natural ingredients and functional benefits. So far, the sensory properties of herbal beverages have not been subjected to descriptive analysis. Here, we selected 12 high-selling herbal beverages containing chrysanthemum samples on China’s largest online shopping website. A total of 11 sensory descriptors have been associated with the samples, while assessed panel performance and sensory characteristics of samples by PanelCheck software. In addition, use ConsumerCheck to investigate the consumer acceptance of the same samples, and apply preference mapping analysis to address the relationship between descriptive and consumer liking date. Box plot and Stacked histogram visualise the distributions of the liking ratings across all consumers for each of the tested products . Preference mapping revealed that the main sensory attributes driving consumers’ preferences are fragrant sweet flavour, brillancy, lubrication, sweet taste and overly sweet taste. Thus, this study could guide the development of Chinese traditional chrysanthemum drink. At the same time, the results also provided a simple and open-source software to data statistical method for practitioner without commercial software and programming skills. PubDate: 2023-11-27
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Abstract: Abstract Ergot alkaloids are a group of toxic compounds, formed by fungi on infested grasses. In 2022, the European Commission set into effect maximum levels for the sum of the twelve major ergot alkaloids in multiple foods. To facilitate the laborious and costly individual quantification of the twelve major ergot alkaloids by HPLC–MS/MS or -FLD, we recently reported a sum parameter method (SPM) for ergot alkaloid quantification. Here, derivatization to lysergic acid hydrazide—a derivative of the mutual ergoline backbone in all ergot alkaloids—allowed simplified determination of all ergot alkaloids in flour via HPLC-FLD. For the measurement of more complex matrices like processed foods, we now developed a MS/MS-based SPM. Two internal standards (IS), isotopically labelled at different positions of the molecule, were synthesized and employed in the MS/MS-measurements. Method performance using either the 13CD3-labelled or the 15N2-labelled IS was evaluated on naturally contaminated rye and wheat flour samples as well as on processed food matrices. Employing the 13CD3-labelled IS leads to lower variances and better consistency with the reference data (obtained by the FLD-based SPM) in flour samples compared to the 15N2-labelled IS. The novel method significantly improves the measurement of ergot alkaloids in complex food matrices, due to their increased selectivity and thus lower interferences. Furthermore, the application of isotope labelled IS obviates the need for time-consuming steps like the determination of recovery rate based, matrix specific correction factors as described in the MS/MS-based European standard method for ergot alkaloid quantification (EN 17425). PubDate: 2023-11-18
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Abstract: Abstract The present study demonstrates that the albedo (AP) and flavedo (FP) portions of Citrus maxima, are often discarded as agricultural waste that has the potential to manufacture high-quality pectin. The efficacy of green microwave aided extraction (MAE) technology for pectin extraction yield from both the portions of citrus peels was examined using a response surface technique. However, further advancement has to be made in improving the functional parameters required for MAE. The optimal conditions for increased pectin yields for albedo (YAP %) and flavedo (YFP %) were found to be solid to solvent ratio (1:15), time (95 s) and power (450 watt). The predicted values of YAP (5.35%) and YFP (3.13) were in accordance with experimental values of YAP (5.57 %) and YFP (3.09 %) with small error % i.e., 3.90 % and 1.29 % for AP and FP respectively. The AP and FP extracted at optimum conditions were compared with commercial pectin (Cp) based on physicochemical properties, color, FT-IR, FE-SEM/EDX, XRD, and particle size analysis. Experimental result shows that AP and FP were classified as high methoxy pectin due to high DE values 72.76 % and 74.98 % respectively. PubDate: 2023-11-17
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Abstract: Abstract Coconut oil is the main edible oil used in South and Southeast Asian countries. Different types of coconut oils are available in the market including virgin coconut oil (VCO), copra coconut oil (CCO), coconut oil extracted by desiccated coconut (DC oil), and refined bleached and deodorized coconut oil based on the manufacturing process. Due to recently identified medical and cosmetic benefits, a huge market has opened for VCO. On top of that, vendors tend to mislead consumers by marketing DC oil instead of VCO for unscriptural financial gain. A reliable accurate method was developed to differentiate VCO from other coconut oils based on their process-based markers. A headspace solid-phase microextraction sampling method combined with gas chromatography was used for the isolation and separation of volatiles, respectively. Mass chromatography was used for the analysis of different constituents in coconut oils. A set of unique chemical compounds was identified for each coconut oil type such as 2-pentanone for VCO extracted from the dry method, hexanal for CCO, and acetic acid for VCO extracted from wet method. It was able to identify four compounds, δ-caprolactone, oxime-methoxy-phenyl, δ-octalactonone, and δ-decalactone which were common to oil coconut oil types. Since these unique compounds are only available in particular oil types, it enables them to be used as marker or tracer compounds to confirm their authenticity. PubDate: 2023-11-16
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Abstract: Abstract Chlorogenic acid isomers have been increasingly studied because of their beneficial biological effects in humans. However, their commercial analytical standards are high cost, a fact that limits research. Yerba mate (Ilex paraguariensis) is a low-cost, natural plant matrix with marked contents of chlorogenic acids, but its potential as a source of analytical standards of chlogenic acids has never been investigated. Thus, this study aimed to optimize a method to extract, isolate, and purify analytical standards of six chlorogenic acids (3-caffeoylquinic, 4-caffeoylquinic, 5-caffeoylquinic, 3,4-dicaffeoylquinic, 3,5-dicaffeoylquinic, and 4,5-dicaffeoylquinic) from yerba mate (Ilex paraguariensis) using semi-preparative high-performance liquid chromatography. For this, sequential statistical multivariate approaches (central composite designs) were utilized. Using the optimized extraction conditions (5 mL of ethanol:water 26:74 v/v, stirring for 30 min at 60 °C), 1000 g of yerba mate gave a concentrated extract totalizing 21.57 g of chlorogenic acid isomers. We established optimized chromatographic conditions to obtain analytical standards of each compound individually, as well as to produce a mix containing all the compounds, with high yields and purities above 97%. Thus, the optimized conditions to obtain the standards have an excellent yield, employed a natural low-cost matrix, and used simple and automated processes with potential to produce in laboratory and industrial scale. These results show the potential of yerba mate as a novel source of standards of chlorogenic acids, and provide an effective method to produce them in laboratories worldwide, which may contribute to advance the research on these compounds. PubDate: 2023-11-14
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Abstract: Abstract Veterinary drugs (VDs) are regulated to prevent their abuse or misuse and protect humans that consume animal-based food products from exposure to VD residues. VD residues are managed according to the maximum residue limits (MRLs) or by prohibiting the use of VDs based on their residual properties and toxicities. However, all VD residues, even those that are not managed by MRLs, in animal-based food products will be regulated for public health improvement. Accordingly, herein, the applicability of an existing multiclass analytical method for the analysis of 59 VDs in fishery foods was validated. Applicability of this method to the analysis of VDs in livestock foods has already been confirmed. In this method, the sample was extracted with water:acetonitrile (1:4, v/v) followed by cooling, concentration, and analysis via liquid chromatography-mass spectrometry. Accuracies and precisions for three fishery foods (namely, flat fish, eel, and shrimp) were 63.7–120% and 1.9–30%, respectively, and a minimum of 63% (44/70) compounds could be quantified. This method is expected to improve the capabilities and efficiencies of monitoring VD residues in animal-based food products and will enhance food safety. PubDate: 2023-11-11
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Abstract: Abstract The objective was the development and validation of a method for simultaneous mycotoxins determination (aflatoxins B1 — AFB1, G1 — AFG1, G2 — AFG2 and M1 — AFM1, ochratoxin — OTA, and zearalenone — ZEA) in milk by high-performance liquid chromatography with fluorescence detector. A mixture planning was used to define the mobile phase and a fractional factorial design to define a flow rate of 1.4 mL min−1, allowing the subsequent application of a rotational central composite design (CCRD). Through the CCRD, it was possible to obtain the desired resolution of 1.86 and 2.95 between the peaks of AFM1-AFG2 and ZEA-OTA, respectively, using acidification of the mobile phase 0.85%, column temperature 38 °C, and injection volume of 40 µL. In parallel, an extraction method based on the QuEChERS method was developed. The limits of quantification were 0.16, 1.08, 0.01, 0.12, 0.33, and 8.93 µg·kg−1 for AFM1, AFB1, AFG1, AFG2, OTA, and ZEA, respectively. Recovery varied between 73 and 114%. The method was applied to evaluate multi-mycotoxins’ occurrence in fluid milk (n = 30). The presence of AFB1, AFG1, AFG2, and AFM1 was detected in 26%, 30%, 93%, and 80% of the samples, respectively; however, the presence of AFM1 was below the maximum limit allowed by Brazilian legislation (0.5 µg·kg−1). OTA and ZEA were below the limit of detection. Thus, the method was capable and efficient in quantifying multi-mycotoxins in fluid milk and can also be applied as a routine method to monitor milk quality. PubDate: 2023-11-11
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Abstract: Abstract Plant-derived extra-cellular vesicles are a new food resource, rich in functional factors. However, the extraction rate of nanoparticles is low. Therefore, in this experiment, single-factor experiments were carried out using Chinese wild rice as the raw material, and the vesicle-like nanoparticles were successfully extracted from Chinese wild rice. The optimization of Chinese wild rice nanoparticle (WRNP) extraction process was conducted based on the response surface method. When the extraction time was 1 hour (h), and the ratio of material to liquid was 1:8.48 (w/v), the protein concentration of WRNPs was 10.28 ± 0.31 mg/mL after repeated extraction for five times. The obtained WRNPs were characterized, and its stability, antioxidant activity, and cytotoxicity assays were also evaluated. The particle size and zeta potential were 150.40 ± 3.11 nm and −8.95 ± 0.11 mV, respectively. The molecular weight of protein was mainly between 25 and 37 kDa, and the β-folds were the main content in the secondary structure of protein. The nanoparticles remained stable for 22 days at 4 °C, and nanoparticles could be digested by the human body. In addition, the antioxidant activity of WRNPs with a protein concentration of 1.6 mg/mL was not significantly different from that of vitamin C. Finally, nanoparticles have no significant toxic effect. The current study can provide a more perfect method for water frying and a reference for the development of natural antioxidant plant nanoparticles. PubDate: 2023-11-09
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Abstract: Abstract Ethylene is a primary plant hormone associated with the ripening process of fruits. Ethylene can initiate the ripening process in fruits even at sub-parts per million concentrations. Therefore, ethylene monitoring during fruit transport and storage is very important in order to ensure optimum quality control and shelf-life extension. However, due to small molecular size, non-polar and highly stable nature of ethylene, the development of ethylene detectors on trace level concentration always remains a challenge. The ubiquitous interference of water molecule to various types of ethylene gas-sensing technologies require efforts to design and utilize effective and durable moisture filters for accurate ethylene gas detection. This work compares various ethylene detection methods for laboratory use as well as portable devices for field applications. Particularly, three methods have shown the most encouraging results in ethylene detection and are used to manufacture portable devices for fruit supply chains: electrochemical, gas chromatography and optical detection. New chemical and physical sensors for ethylene detection and quantification have been compared with scientific literature based on comparable parameters. The parameters specifically focus on the needs of horticulture industry like sensitivity, selectivity, price, robustness and inexpensiveness. This study shall assist the fruit logistics in better selection of ethylene sensing technologies in the fruit supply chain, resulting in better fruit quality and reduced losses after harvest. PubDate: 2023-11-03
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Abstract: Abstract Considering the increased consumption of organic foods, it is important to propose analytical methods to evaluate these ones. The basic difference between organic and non-organic food products is how they are produced and processed, and methods to discriminate among them are a current trend in food science and analytical chemistry. In this way, this research aimed to propose an analytical method based on a handheld ultraviolet (UV) spectroscopy dispositive coupled with a multivariate control chart based on principal component analysis (MCC-PCA) for differentiation of organic rosemary (Rosmarinus officinalis L.), a plant employed in popular medicine and as a food condiment. Using a simple extraction in a magnetic stirrer showed that UV coupled with MCC-PCA could promote a rapid analysis in the differentiation of organic samples. The proposal was validated, and the robustness was evaluated with a slight modification in the extraction step and by correctly predicting samples obtained in another country. PubDate: 2023-11-02
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Abstract: Abstract Sulforaphane (SFN) is an isothiocyanate and the product of the hydrolysis of glucoraphanin (GRA) by myrosinase. Broccoli is one of the rich sources of GRA and thus SFN. SFN possess a wide range of bioactivities and is considered an anti-cancer phytochemical. Most of the current common methods used to quantify SFN are based on high-pressure liquid chromatography (HPLC) with diode array detection (DAD) — also known as HPLC-DAD. Although this technique has shown encouraging results, the detection of SFN by DAD is relatively weak and affected by high interference of sample matrices. Therefore, the aim of this study was to develop a liquid chromatography-mass spectrometry (LC-MS) method in which SFN is identified by molecular mass to give more accurate results. The developed method demonstrated a highly reproducible retention time (7.204 ± 0.008 min), producing a sharp, symmetrical and well-defined sulforaphane peak in standard and test samples. The most dominant ion of sulforaphane in the pure and test samples was 178 m/z ([M + H]+). In terms of linearity, the calibration curve had a coefficient of determination (R2) of 0.9963. The limit of detection of this method is 1.3 ng/mL, and the limit of quantification is 3.9 ng/mL, indicating high sensitivity. The uniformity of peak shape and retention time in both pure and test samples were the same suggesting excellent selectivity. Overall, the developed method showed promising results in identifying and quantifying broccoli SFN. PubDate: 2023-11-02
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Abstract: Abstract The research on methods for radiochemical determination of alpha-emitting radioactive elements is constantly evolving, and is essentially focused on reducing sample analysis times and using increasingly less aggressive and polluting chemical reagents. Even the most widely used chromatographic resins can be dangerous for operators and for the environment, and researchers try as much as possible to reduce the quantities used. In particular, an attempt is made to reuse the chromatographic resins at least a second time, also considering the fact that these reagents can also be quite expensive for a test laboratory. The present study presents a radiochemical method for the simultaneous determination of alpha-emitting isotopes of thorium, uranium, plutonium, americium, and curium in agri-food matrices and water, using a single commercially available chromatographic resin that is used twice in the same analytical run. The method, designed for laboratories that need to analyze many matrices for radioactivity monitoring programs, has proven to be precise and accurate, achieving very high values of chemical yield (> 75% in solid matrices, > 90% in water) and z-scores lower than 2 in the context of two important international proficiency tests. PubDate: 2023-10-31
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Abstract: Abstract Pymetrozine, a member of the azomethine pyridine group, is gaining popularity among paddy farmers due to its anti-feeding properties against homopteran insects like planthoppers, whiteflies, and aphids on a wide range of fields, fruits, and ornamental crops. To analyze this insecticide in different food and environmental samples of crop ecosystems, an eco-friendly, rapid, sensitive, and reproducible method was developed using triple quadrupole LC-MS/MS and validated as per SANTE/12682/2019 for the detection of pymetrozine residues in paddy leaf, straw, husk, brown rice, and soil. The half-life in paddy leaf ranged from 4.27 to 5.14 days during rabi 2019-20 and 3.95 to 4.58 days during kharif 2020-21, at field application rate of 150 g.a.i. ha−1 and 300 g.a.i. ha−1, respectively. The half-life in paddy soil ranged from 5.56 to 6.69 days during rabi and 4.45 to 5.74 days during kharif at the respective doses. The hazard index value was less than one in brown rice at harvest, which indicates the product is safe for consumption at both doses. The risk quotient was less than one for earthworms (Eisenia foetida), indicating low-to-moderate risk. Dietary risk of paddy leaf (green fodder) was found safe for both dry and in-milk cattle consumption. The hazard index is less than one at 7 to 21 days onwards during rabi; 7 to 15 days onwards during kharif upon application of pymetrozine at 150 and 300 g.a.i. ha−1, respectively. PubDate: 2023-10-21
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Abstract: Abstract The adverse effects of acrylamide (AA) on humans are becoming clear, especially after a series of related investigations reported the dependence on consuming foods prepared by exposure to high temperatures for a long-time and cancer risk. Accurate determination of AA in food samples at trace amount is considered the first step to overcome this significant problem. The determination of AA using coal tar pitch modified pencil graphite (PGE/CTP) electrode was reported. The bare PGE and PGE/CTP electrodes were characterized using microscopic imaging technique scanning electron microscopy (SEM). The electrochemical behavior of AA was studied on PGE/CTP electrode in different medium acidities (pH) of phosphate and Briton-Robinson (BR) buffer solutions by employing square wave voltammetry (SWV). Linear sweep voltammetry (LSV) technique was applied to determine the mass transfer mode of AA from bulk solution to the PGE/CTP electrode surface. The optimum conditions were using phosphate buffer solution (PBS) at pH 7.0. The detectability of AA on the surfaces of bare PGE and PGE/CTP electrodes was compared, and the suitability of PGE/CTP electrode usage was determined. The linear relationship between peak current and AA concentration was in the range of 1000.0 to 0.5 nM. The limit of detection of AA was 0.2094 nM, and the limit of quantitation was 0.6912 nM. In addition, the PGE/CTP electrode as a sensor was successfully used for the determination of AA in the instant coffee sample. PubDate: 2023-10-18
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Abstract: Abstract Interest in extracting mucilage from natural sources like taro corms stems from its potential applications in various industries, including food, pharmaceuticals, and cosmetics, while traditional extraction methods are often inefficient and time-consuming. Hence, the critical purposes of the current research trends are to use an efficient and sustainable extraction method, optimize the process conditions for maximum yield and quality. Nevertheless, this research aimed to optimize the conditions for ultrasonic-assisted extraction (UAE) of mucilage from taro corms and compare its extraction efficacy and functional properties with conventional methods like heat extraction and Soxhlet extraction. As a consequence, the extraction conditions were optimized with fifteen experimental trials using response surface methodology (RSM) combined with a Box-Behnken design (BBD) (three-factor-three-level), considering ultrasonic temperature (X1, 40–60 °C), ultrasonic time (X2, 15–45 min), and water-to-solvent ratio (X3: 3:1–7:1). Moreover, a second-order polynomial model predicted the responses, and model validity was confirmed through analysis of variance (ANOVA). Briefly, the results revealed the optimal extraction parameters for maximizing taro mucilage extraction (14.315 ± 0.015%) were 60 °C ultrasonic temperature, 45 min ultrasonic time, and a 5:1 water-to-solid ratio. This outperformed heating extraction (4.15 ± 0.029%) and Soxhlet extraction (6.05 ± 0.011%). Furthermore, the UAE extracted mucilage exhibited superior functional properties, including higher emulsion stability against heat (92 ± 0.023%), water holding capacity (65 ± 0.013%), oil holding capacity (41 ± 0.01%), foaming capacity (38 ± 0.041%), and foaming stability (87 ± 0.021%) compared to the heating and Soxhlet methods. In addition, the experimental results supported the predicted values, confirming the appropriateness of the model and the efficacy of RSM in optimizing UAE extraction conditions. These results not only provide a practical solution for efficient taro mucilage extraction but also underscore the effectiveness of RSM in optimizing extraction conditions. Ultimately, the study’s findings have the potential to significantly impact various industries by enhancing product quality, reducing waste, and conserving valuable resources. PubDate: 2023-10-17
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Abstract: Abstract Given the urgent requirement for more laboratories to develop proficiency in detecting foodborne viruses, this case study charts the path to accreditation, demystifying the process of validating a method for detecting norovirus and hepatitis A virus in fresh produce. Securing accreditation is crucial to ensuring dependable and precise food analysis, particularly relevant for products frequently consumed raw, which are at risk of contamination by foodborne viruses. The study provides an in-depth look at the stringent procedures integral to achieving precision and dependability in results, underscoring the pivotal role of competency checks involving artificial contamination of samples. The case study also navigates the integral role of both external and internal quality assurance processes in affirming the consistency and accuracy of laboratory testing methods. The findings of this case study are transformative, amplifying confidence in laboratory results and potentially catalysing improvements in public health by ensuring accurate virus detection and identification in food samples. Furthermore, the accreditation process, as detailed in this case study, could pioneer a path for other laboratories, fostering best practices in virus detection and identification. PubDate: 2023-10-16
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Abstract: Abstract The protein and fat contents are important indicators for the quality evaluation of brewing sorghum, and a rapid and non-destructive testing method is urgently required to accurately detect them. Hyperspectral imaging (HSI) technology has been widely used in the assessment of the composition of various foods. In this study, different preprocessing methods were used to process the spectral data and determine the optimal preprocessing method. The characteristic spectra were extracted by three combination algorithms, namely, uninformative variable elimination-successive projections algorithm (UVE-SPA), competitive adaptive reweighted sampling-successive projections algorithm (CARS-SPA), and principal component analysis-successive projections algorithm (PCA-SPA). Four models (cascade forest (CF), the backpropagation-genetic algorithm (BP-GA), support vector regression (SVR), and partial least square regression (PLSR)) were established to predict the protein and fat contents based on the full spectrum, the feature spectrum, and fusion data (the integration of the feature spectrum with its corresponding texture features). A comparative analysis revealed that the BP-GA and CF models based on the visible light characteristic spectra extracted by PCA-SPA and UVE-SPA were the best models for predicting the protein and fat contents, respectively; they had respective RPD values of 5.1716 and 12.9724 and respective AB_RMSE values of 0.0916 and 0.0243 g/100 g. The overall results show that HSI combined with machine learning algorithms can rapidly and non-destructively predict the protein and fat contents of sorghum. PubDate: 2023-10-04
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