Method For Determination Of Protein Research Articles

Application of the Bernstein protein determination method in the study of the quality of feed raw materials of plant and animal origin

For the purpose of practical application of the method of determining the mass fraction of protein according to Barnstein for various one-component feed raw materials of animal and vegetable origin, we conducted a series of experiments on four types of raw materials: fish meal, meat and bone meal, corn gluten, sunflower cake. To do this, each sample of feed was divided into 2 samples and an additive was introduced into each (one additive contained protein, and the other non– protein nitrogen). Determination of the protein nitrogen content in feed was carried out under the same conditions as the analysis of the initial samples. When comparing the theoretically calculated value and the practical result for all types of feed samples, reliable results were obtained. The conducted studies have shown the need to control raw materials to establish the true protein content in order to exclude the possibility of contamination with nitrogen-containing substances of non -protein origin.

A rapid determination of wheat flours components based on near infrared spectroscopy and chemometrics

In this work, a rapid and simple analytical method for the quantitative determination of moisture, protein, wet gluten, starch and sedimentation index in the wheat flour was established by the combination of near infrared spectroscopy and chemometrics. The spectra of the 229 wheat flour samples were collected by a portable near infrared fast analyzer. The contents of these components were determined according to the relevant Chinese National Standards, and were taken as the corresponding reference database. Seven spectral pretreatment methods were employed to eliminate the optical interference from background and other noise information. The best result was obtained with FD+SG(15, 3)+MC method for moisture, protein, wet gluten and sedimentation index, FD+SG(15, 2)+MC method was more suitable for starch. The principal component numbers (PCs) were also optimized to obtain a superior model effect. Furthermore, partial least squares (PLS) and multiple linear regression (MLR) modeling methods were used to quantify the content of the components. When using FD+SG(15, 3)+MC pretreatment, all the PLS model parameters were significantly better than the MLR model. Both the predicted values and the reference values showed superior linear relationship within the calibration range. Moreover, the absolute error of the predicted values and their corresponding reference values in the PLS model were within their confidence intervals, respectively. The relative errors for moisture, protein, wet gluten and starch fluctuated little, only sedimentation index fluctuated greatly. The actual prediction correct rate of moisture, protein, wet gluten, starch and sedimentation index were 96.8%, 96.8%, 90.3%, 100.0% and 80.6%, respectively, which indicated the prediction was excellent.

A Comparative Study of Fourier Transform Near-Infrared Spectroscopy and Physicochemical Methods in Wheat Quality Analysis

Near-infrared spectroscopy is a non-invasive, rapid, and efficient analytical method widely employed in agricultural quality assessment. This study aims to explore the potential of Fourier transform near-infrared (FT-NIR) spectroscopy in the analysis of wheat quality in comparison to traditional physicochemical methods. Key quality parameters such as protein content, bulk density, dough extensibility, development and stability time, wet gluten, and extension area were considered. To compare the similarities between the two methods in an irregular manner and to make the trials more representative, randomized combinations of different samples were made by planting different wheat genotypes in different locations. In wheat protein determination (r = 0.92, p < 0.001), the correlation between protein determinations was very high and highly statistically significant. This indicates that the Fourier transform near-infrared (FT-NIR) assay is highly consistent and accurate with the physicochemical method for protein determination. In the quality indices of bulk density (r = 0.46, p < 0.05), dough extensibility (r = 0.46, p < 0.05), development time (r = 0.37, p < 0.05), stability time (r = 0.49, p < 0.01), wet gluten (r = 0.54, p < 0.01), and dough extension area (r = 0.63, p < 0.001), there was a positive correlation between the two assays. Although the correlation was lower compared to the protein assay, it was still statistically significant. This suggests that the FT-NIR assay also has some accuracy in these indices, although there may be some differences from the physicochemical method. Through comparative analysis, we found that in wheat quality assessment, FT-NIR showed a strong correlation and was highly significant in the determination of wheat protein content; in the determination of the extension area, although highly significant, the correlation coefficient was not high, and there was a positive correlation between the two, and a lower correlation was shown in the bulk density, dough extensibility, and development time. These results indicate that FT-NIR can assess the wheat protein content quality indicator. However, its ability to accurately assess wheat quality indicators such as density, dough extensibility, development and stability time, wet gluten, and dough extensibility needs further investigation.

Improvement of the metod of protein content prediction in wheat kernels

The study was conducted in order to expand the possibilities of using the developed multiple nonlinear regression equation, re ecting the dependence of the protein content in wheat grain (Y, %) on the content of raw gluten (X1, %) and the mass of 1000 grains (X2, g). The possibility of practical use of the developed and three improved equations for predicting the protein content of wheat grain is shown. An algorithm and results of checking the prognostic capabilities and accuracy of predict equations from independent data are presented. Generalization of experimental data from 288 literature sources of domestic and foreign authors with a total number of observations n = 4604 on more than three hundred varieties of winter and spring soft and durum wheat grown in the period from 1959 to 2020 in Russia and abroad (Albania, Belarus, Bulgaria, Egypt, Kazakhstan, Lithuania, Poland, Slovakia and Ukraine) showed that the number of values that go beyond to limits regulated by GOST 10846-91 «Protein determination method» was 755 or 16.4 %. At the same time, the accuracy of prediction the protein content reached 83.6 %. The developed equations can be used to predict of protein content in almost all cases: when the results of the analysis of protein content and raw gluten in wheat kernel, as well the 1000-kernels weight are given at actual or fxed moisture content, or in terms of dry matter

Dependence of the nutritional value of meat on the quality category

In the literature data, information about the nutritional value of meat of different quality categories is mainly represented by its assessment in the presence of PSE and DFD defects either in pork or beef. There are practically no studies on the nutritional value of meat with the quality category RSE, RFN, PFN. Therefore, the assessment of the nutritional value of meat, depending on the quality categories, is of both scientific and practical interest.The purpose of the research was to study the dependence of the nutritional value of meat on the quality category.The research was carried out in the conditions of the educational and research center for the examination of food and animal feed of the St. Petersburg State University of Veterinary Medicine in the period 2020-2022.The materials for the study were 107 samples of meat of various quality categories obtained from different types of slaughter animals.The nutritional value of meat samples was determined according to GOST 34567-2019 "Meat and meat products. Method for determination of moisture, fat, protein, sodium chloride and ash using near-infrared spectroscopy (with Correction)" using infrared analyzer "InfraLUM FT-12". Processing of the received data was carried out using the software "Spectrum/Pro".As a result of determining the nutritional value of meat of different quality categories, it was found that the content of protein, fat and moisture depended on the category. It should be noted that information about the nutritional value of meat of various quality categories should be taken into account when conducting input control and processing meat raw materials at processing enterprises.

Correlation between 24-hour Urinary Total Protein Excretion and Single Urinary Protein Creatinine ratio in the Diagnosis of Childhood Nephrotic Syndrome : Study in a Tertiary Level Hospital

Introduction:Protein excretion varies in the course of the day, for this reason 24-hours urinary total protein excretion has been considered as the classic reference method for protein determination in nephotic syndrome. As the collection of urine for 24 hours is tedious and errors may occur during the process, so the protein:creatinine ratio was developed as a diagnostic alterative for Nephrotic syndrome.The main aim of this study is to determine the correlation between 24-hour urinary total protein excretion and single urinary protein creatinine ratio in childhood Nephrotic syndrome. Methods: This cross-sectional study was conducted in the department of Paediatrics,Shaheed Suhrawardy Medical College & Hospital from June 2018 to May 2019. After taking valid consent total 60 cases of Nephrotic syndrome were selected purposively according to inclusion and exclusion criteria. Here we tried to determine the correlation between 24-hour urinary total protein excretion and single urinary protein creatinine ratio in the diagnosis of childhood Nephrotic syndrome by measuring the spot urinary protein creatinine ratio and the 24 hours urinary total protein excretion of the patients. Results : Among total 60(N) children of Nephrotic syndrome 42 (70%) patients were male and 18 (30%) patients were female with M:F = 2.16:1.The mean age was 4.57 ± 2.01SD years. Most of the patients were presented with some associated diseases like urinary tract infection (30%), upper respiratory tract infection (28.3%), viral illness(8.3%), atopic dermatitis(3.3%) and nonspecific illnesses(30%). The main physical findings were only puffy face(100%), with ascites (86.6%) and swelling of genitalia (38.3%).The mean 24 hours urinary total protein excretion was 3114.45 ± 1627.89 mg/24 hours and spot urinary protein creatinine ratio was 5.57 ± 3.13 SD. There was a very significant correlation between 24 hour total urinary protein excretion and spot urinary protein creatinine ratio. The sensitivity of the study was 80.49 – 100% and specificity of 91.78 - 100% at £2000 mg /sqm body surface area/ day protein excretion. The p value was .002 with correlation coefficient was 0.39. Conclusion: The protein creatinine ratio of a random urine sample might be used as an alternative method for the diagnosis of Nephrotic syndrome in children in view of the obvious advantages in terms of cost, time and patient convenience. J Shaheed Suhrawardy Med Coll 2021; 13(2): 137-142

Comparison of methods for detecting protein extracted from excess activated sludge

The protein contents of hydrolyzed sludge supernatant are commonly determined with the Kjeldahl method, but this method suffers from complicated operations, long process times, and large quantities of chemicals consumed. In this paper, the Lowry, bicinchoninic acid (BCA), and Bradford methods were used to test the precision and spiked recovery of proteins from sludge supernatants hydrolyzed by alkaline-thermal hydrolysis (ATH), enzymatic hydrolysis (EH), and ultrasound-assisted enzymatic hydrolysis (UEH), and the results were compared with those obtained with the Kjeldahl method. For all the hydrolytic processes, the sludge protein values determined with the three tested methods were within 0.05 of each other, which met the experimental requirement for accuracy. Both the Lowry and BCA methods had recovery rates of 95-105%, while the Bradford method showed large deviations and was not highly reliable. The three protein determination methods showed significant differences with the Kjeldahl method (P<0.05). However, the relative deviation between the Kjeldahl and BCA methods was the smallest (3-5%), followed by those between the Kjeldahl and the Lowry (11-21%) and Bradford methods (21-90%), and the causes of the deviations were analyzed based on the protein hydrolysate components and the mechanisms for the different detection methods. On the basis of these results, the BCA method was chosen as the most appropriate quantification method for use with sludge protein extraction, and it was used to analyze the protein contents extracted from residual sludge samples obtained from two sewage treatment plants. The reliability of the method was verified, and this lays a foundation for the extraction and reclamation of sludge proteins.

Qualitative and quantitative determination of proteins in extracts of some medicinal plants

Introduction. Global consumption of plant protein is increasing and high-fiber plants have health benefits through valuable phytochemicals. Plant proteins serve as an alternative to animal proteins to meet consumer demand on the one hand and reduce the risk of disease on the other. Material and Methods. We performed qualitative and quantitative determination of proteins in extracts by sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) and total content of proteins by Bradford assay. Results. Applied methods for the qualitative and quantitative determination of proteins in dry extracts of medicinal plants: Agrimonia eupatoria L., Cichorium intybus L., Galium verum L., and Solidago virgaurea L. confirm that proteins were detected in all dry extracts and were determined the total content of them. Conclusion. For all extracts obtained from aerial parts of: Agrimonia eupatoria, Cichorium intybus, Galium verum and Solidago virgaurea we find a low protein concentration, which implies minimizing allergic reactions and intolerance to the extracts studied.

SERS for Detection of Proteinuria: A Comparison of Gold, Silver, Al Tape, and Silicon Substrates for Identification of Elevated Protein Concentration in Urine.

Excessive protein excretion in human urine is an early and sensitive marker of diabetic nephropathy and primary and secondary renal disease. Kidney problems, particularly chronic kidney disease, remain among the few growing causes of mortality in the world. Therefore, it is important to develop an efficient, expressive, and low-cost method for protein determination. Surface enhanced Raman spectroscopy (SERS) methods are potential candidates to achieve these criteria. In this paper, a SERS method was developed to distinguish patients with proteinuria from the healthy group. Commercial gold nanoparticles (AuNPs) with diameters of 60 nm and 100 nm, and silver nanoparticles (AgNPs) with a diameter of 100 nm were tested on the surface of four different substrates including silver and gold films, silicon, and aluminum tape. SERS spectra were acquired from 111 unique human urine samples prepared and measured for each of the seven different nanoparticle plus substrate combinations. Data analysis by the PCA-LDA algorithm and the ROC curves gave results for the diagnostic figures of merits. The best sensitivity, specificity, accuracy, and AUC were 0.91, 0.84, 0.88, and 0.94 for the set with 100 nm Au NPs on the silver substrate, respectively. Among the three metal substrates, the substrate with AuNPs and Al tape performed slightly worse than the other three substrates, and 100 nm gold nanoparticles on average produced better results than 60 nm gold nanoparticles. The 60 nm diameter AuNPs and silicon, which is about one order of magnitude more cost-effective than AuNPs and gold film, showed a relative performance close to the performance of 60 nm AuNPs and Au film (average AUC 0.88 (Si) vs. 0.89 (Au)). This is likely the first reported application of unmodified silicon in SERS substrates applied for direct detection of proteins in any biofluid, particularly in urine. These results position silicon and AuNPs@Si in particular as a perspective SERS substrate for direct urine analysis, including clinical diagnostics of proteinuria.

Determination and evaluation of whey protein content in matured cheese via liquid chromatography

To date, there is no valid analytical method available to determine the total whey protein (TWP) content in cheese. Therefore, the aim of this study was to develop HPLC methods for whey protein determination in mature cheese. For that purpose, foil-ripened whey protein-enriched model cheese and traditional Edam-type cheese were produced and analyzed. Suitable protein extraction methods and subsequent analytical methods to determine the acid-soluble whey protein (ASWP) and TWP content in cheese were developed. To characterize the influence of proteolysis on native and denatured whey proteins, the ASWP and TWP contents were determined throughout the ripening process. Both chromatographic methods showed that the individual whey proteins (α-lactalbumin and β-lactoglobulin) were not degraded during ripening. However, the analyzed ASWP content increased by up to 25% throughout ripening. Compared to traditional Edam-type cheese, the β-lactoglobulin content in whey protein-enriched cheese (containing 30% high-heat milk) increased by a factor of 3.5. To evaluate the chromatographic results, two different calculation models were used to estimate a reference value for the TWP content in the manufactured cheese. Further studies are required to optimize the quantification of TWP content in hard, semihard, soft, and cream cheeses.

Highly Sensitive Zinc Oxide Fiber-Optic Biosensor for the Detection of CD44 Protein

Currently, significant progress is being made in the prevention, treatment and prognosis of many types of cancer, using biological markers to assess current physiological processes in the body, including risk assessment, differential diagnosis, screening, treatment determination and monitoring of disease progression. The interaction of protein coding gene CD44 with the corresponding ligands promotes the processes of invasion and migration in metastases. The study of new and rapid methods for the quantitative determination of the CD44 protein is essential for timely diagnosis and therapy. Current methods for detecting this protein use labeled assay reagents and are time consuming. In this paper, a fiber-optic biosensor with a spherical tip coated with a thin layer of zinc oxide (ZnO) with a thickness of 100 nm, deposited using a low-cost sol-gel method, is developed to measure the CD44 protein in the range from 100 aM to 100 nM. This sensor is easy to manufacture, has a good response to the protein change with detection limit of 0.8 fM, and has high sensitivity to the changes in the refractive index (RI) of the environment. In addition, this work demonstrates the possibility of achieving sensor regeneration without damage to the functionalized surface. The sensitivity of the obtained sensor was tested in relation to the concentration of the control protein, as well as without antibodies-CD44.

Surface-enhanced Raman spectroscopy (SERS) for protein determination in human urine

Excessive protein excretion in human urine is an early and sensitive marker of diabetic nephropathy, primary and secondary renal disease. Kidney problems, particularly chronic kidney disease, remain among the few growing causes of mortality in the world. Therefore, it is important to develop efficient, expressive, and low-cost method for protein determination. Surface-enhanced Raman spectroscopy (SERS) methods are potential candidates to achieve those criteria. In this paper, the SERS method was developed to distinguish patients with proteinuria and the healthy group. Two types of commercial gold nanoparticles with a diameter of 60 nm and 100 nm were employed to prepare substrates for the analysis of 78 samples of unique patients. Data analysis by the PCA-LDA algorithm, and the ROC curves, gave results for diagnostic figures of merits. Sensitivity, specificity, accuracy, and AUC were 0.79, 0.89, 0.85, and 0.90 for the set with 60 nm Au NPs, respectively. Sensitivity, specificity, accuracy, and AUC were 0.79, 0.98, 0.90, and 0.91 for the set with 100 nm Au NPs, respectively. The results show the potential of SERS spectroscopy in differentiating between patients with proteinuria and healthy individuals for clinical diagnostics.

Nylon Membrane-Based Electromembrane Extraction Coupled with Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry for the Determination of Insulin

A rapid and sensitive protein determination method that uses electromembrane extraction (EME) and is coupled with matrix-assisted laser desorption/ionization mass spectrometry (MALDI/MS) is developed. A flat nylon membrane is used to collect proteins from an aqueous solution and is directly analyzed by MALDI/MS after the addition of the MALDI matrix. Insulin is used as a model protein to investigate the optimum extraction of the parameters. The optimum EME conditions are obtained at 12 V of voltage, 10 min of extraction time, 12 mL sample volume, and 400 rpm agitation rate. The linear dynamic range (LDR) of insulin in an aqueous solution is in the range of 1.0–100.0 nM. The limit of detection (LOD) for insulin in an aqueous solution is 0.3 nM with 103-fold signal-to-noise (S/N) ratio enhancement. Furthermore, the applicability of this method to determine insulin in complicated sample matrices is also investigated. The LDR of insulin in human urine samples is in the range of 5.0–100.0 nM, and the LOD of insulin in urine samples is calculated to be 1.5 nM. The precision and accuracy of this method are evaluated at three different concentration levels, and the coefficient of variation (CV) and relative error are less than 6%. This approach is time-efficient and economical, as the flat membrane mode of EME coupled with MALDI/MS is suitable.

Comparative study of the most commonly used methods for total protein determination in milk of different species and their ultrafiltration products.

Milk ultrafiltration is a widely used membrane filtration process that allows the recuperation of whey proteins in a concentrate high in total solids, which can later be transformed in multiple healthy dairy products with great prospects for the food industry. Protein content is a decisive factor for the technological performance of milk concentrates and currently, the ISO standard method for its determination is Kjeldahl, which is time-consuming and requires specific instrumentation. For this reason, the use of rapid methods to quantify protein would greatly facilitate the monitoring of the milk ultrafiltration process. In this study, the bicinchoninic acid assay (BCA), the detergent compatible Bradford assay and the Dumas method were compared to Kjeldahl protein determination to select a quick and accurate methodology suitable for milk of different species and its ultrafiltration products (retentates and permeates). The protein content obtained from Bradford assay and Dumas method in origin milk and retentate samples was consistent with Kjeldahl values. In contrast, BCA protein levels were significantly different when compared to Kjeldahl and no method was proved to be suitable for protein determination in permeate samples. The use of sodium dodecyl sulfate was also examined to improve protein measurements without success. In comparison with the official method, Bradford assay quantitatively provided the best results, and it would be recommended for a quick, economic and easy determination of total protein content in milk and retentate samples.

Development of a rapid, high-sensitivity, low-cost fluorescence method for protein surface hydrophobicity determination using a Nanodrop fluorospectrometer

A microvolumetric method for surface hydrophobicity (H0) determination of proteins using a Nanodrop fluorospectrometer was developed. This method reduces the protein and fluorophore quantities that are necessary for sample preparations and readings by two and three orders of magnitude, respectively, compared to conventional methods. In addition, readings can be obtained in just 2–6 s. Bovine serum albumin (BSA) and 1-anilino 8-naphthalene sulfonic acid (ANS) were used for the first optimization of appropriate fluorophore-protein conditions for H0 determination (20 μM ANS, 0.5–4 μM BSA, pH 5). Based on validation guidelines, the novel method shows linear behavior, good intraday precision, accuracy, and sensitivity. This method was robust against several factors, as determined by a Youden-Steiner test. Additional surface hydrophobicity determinations using several proteins demonstrate suitable method applicability. The present microvolumetric method provides a reliable technique to determine the H0 of proteins for pharmaceutical, biotechnological, and food applications.

Determination of the protein content of complex samples by aromatic amino acid analysis, liquid chromatography-UV absorbance, and colorimetry

Fast and accurate determination of the protein content of a sample is an important and non-trivial task of many biochemical, biomedical, food chemical, pharmaceutical, and environmental research activities. Different methods of total protein determination are used for a wide range of proteins with highly variable properties in complex matrices. These methods usually work reasonably well for proteins under controlled conditions, but the results for non-standard and complex samples are often questionable. Here, we compare new and well-established methods, including traditional amino acid analysis (AAA), aromatic amino acid analysis (AAAA) based on the amino acids phenylalanine and tyrosine, reversed-phase liquid chromatography of intact proteins with UV absorbance measurements at 220 and 280 nm (LC-220, LC-280), and colorimetric assays like Coomassie Blue G-250 dye-binding assay (Bradford) and bicinchoninic acid (BCA) assay. We investigated different samples, including proteins with challenging properties, chemical modifications, mixtures, and complex matrices like air particulate matter and pollen extracts. All methods yielded accurate and precise results for the protein and matrix used for calibration. AAA, AAAA with fluorescence detection, and the LC-220 method yielded robust results even under more challenging conditions (variable analytes and matrices). These methods turned out to be well-suited for reliable determination of the protein content in a wide range of samples, such as air particulate matter and pollen.

On-Line Monitoring of the Tobacco Leaf Composition during Flue-Curing by Near-Infrared Spectroscopy and Deep Transfer Learning

The yield, quality, and output value of tobacco leaves are strongly affected by the flue-curing conditions. To effectively control the flue-curing and guarantee quality, it is necessary to quantify the chemical composition of tobacco leaves and provide timely feedback during this process. Therefore, the practicability of on-line monitoring of moisture, starch, protein, and soluble sugars for tobacco leaves by near-infrared (NIR) spectroscopy and deep transfer learning was explored. The results showed that the use of an NIR spectrometer equipped with a fiber-optic probe with a deep learning algorithm accurately predicted the content of these components during the curing process. The convolutional neural networks model showed greater potential for on-line monitoring than partial least squares and support vector machines. Furthermore, a network-based deep transfer learning strategy was crafted to include seasonal and temperature variability to accurately predict samples from a new harvest season in a curing barn. The overall studies indicated the efficacy of NIR diffuse reflectance spectroscopy as a rapid and nondestructive method for on-line and simultaneous determination of moisture, starch, protein, and soluble sugars in the flue-curing process to assist in making decisions.

Honey as a component of marinade for semi-finished meat products

The specific features of the biochemical composition and properties of raw meat determine the necessity of finding new technologies for its processing to obtain new products with high consumer properties. The actual area of technology development is the enrichment of raw meat with useful components with functional and technological properties that have high biological value: api products and products of plant origin.The purpose of the work was to develop a marinade with the addition of honey and to explore its effect on the semi-finished meat product, depending on the duration of marinating. Selection of samples for investigations and their preparation for analysis was performed according to GOST 4288-76 “Culinary and semi-finished products of minced meat. Acceptance rules and test methods”, organoleptic examinations were performed according to DSTU 4426:2005, moisture content determination – GOST 9793-74 “Meat products. Methods for determination of moisture”, the amount of fat – for GOST 23042-86 “Meat and meat products, “Methods for determination of fat”, the amount of protein – GOST 25011-81 “Meat and meat products. Methods for determination of protein”, determination of ash content – GOST 31727-2012 “Meat and meat products. Determination of mass fraction of total ash”, determination of pH – GOST 26188-84 “Products of fruits and vegetables processing, canned meat and meat. Determination of pH”, and determination of fibre-forming and fibre-retaining properties were performed through sample preparation and determination of fibre content. According to the scheme of the experiment, the research technology was determined. The research results of the initial raw meat, honey and marinated semifinished product are presented in the study. It was established that the decrease in the pH of the marinated semi-finished product during the 24-hour exposure period ensures the stability of the meat to storage, as most bacteria develop at high pH values, while on acidic nutrient media below 6.2, their development is slowed down. Long marinating allows obtaining meat with increased moisture binding and moisture retention capacity and improved consistency and juiciness. The task of establishing new products requires new approaches and techniques of technology. Using apiproducts that have antioxidant properties will allow refraining from using preservatives and stabilisers of chemical origin. Thus, honey can be used in the composition of marinated meat products. The introduction of active components of honey into the marinade will extend the shelf life and adjust the organoleptic properties. In addition, during heat treatment, the meat marinated with honey marinade acquires new taste qualities, and the appearance becomes brighter due to the caramelisation of honey

Comparison of PLSR, MLR, SVM regression methods for determination of crude protein and carbohydrate content in stored wheat using near Infrared spectroscopy

Aim of the study was to predict quality parameters namely protein and carbohydrate content of wheat grain stored for one year at 4 °C and 21 °C using Near Infrared spectroscopy (NIRS) and Chemometrics. The spectra of grains were measured in reflectance mode using lab made filter based pre dispersive NIRS ranging from wavelength 750 nm to 2580 nm. NIR Wavelengths were divided into two sets for all the stored samples depending on its correlation with factors. The reference data and NIR data were analysed by principal component analysis (PCA) scores, partial last squared regression (PLSR) model, Multiple Regression Analysis (MLR) and Support Vector Machine Regression (SVMR). First four factors were sufficient to develop regression models for the above mentioned methods. Prediction performance was compared on the basis of the coefficient of correlation (R2) and Root Mean Square Error (RMSE) for the calibration and validation sets. R2 values for prediction of protein content from PLSR model were 0.955, 0.997 for 4 °C Wavelength Set I and II and 0.903, 0.989 for 21 °C Wavelength Set I and II. For the prediction of carbohydrate content 0.978, 0.951 and 0.946, 0.974 were the R2 values for the 4 °C and 21 °C wheat samples Set I and Set II respectively. MLR model also gave R2 values greater than 0.9 for all the samples. Wavelengths with high β correlation coefficients were defined. SVMR predicted the protein content and carbohydrate content with good accuracy. SVMR and PLS results. All the models developed showed good accuracy for successful prediction of protein and carbohydrate content of stored wheat grains with PLSR and SVMR giving the best results. This study showed that near infrared spectroscopy has potential to distinguish wheat grains stored under different conditions.

Protein quantification in ecological studies: A literature review and empirical comparisons of standard methodologies

Abstract Protein quantification is a routine procedure in ecological studies despite the inherent limitations of well‐acknowledged protein determination methods which have been largely overlooked by ecologists. Thus, we want to bridge this knowledge gap, in hopes of improving the way ecologists quantify proteins and interpret findings. We surveyed the ecological literature to determine how and why ecologists quantify proteins. To determine whether different quantification methods produce comparable results across taxa, and between populations of a single species, we estimated the protein content of eight phylogenetically diverse taxa, and of desert isopods fed different diets, using various derived protocols of the 'crude protein', Bradford and bicinchoninic acid approach (BCA) methods. We found that ecologists use many protein quantification procedures, often without reporting the crucial information needed to evaluate and repeat their methods. Our empirical work demonstrated that the three quantification methods examined, and their derived protocols, resulted in highly divergent protein estimations that were inconsistent in rank across taxa, preventing conversion between methods. We also found that different quantification methods yielded different answers to whether isopod protein content is affected by diet. We conclude that commonly used quantification techniques yield distinct protein estimations with varying precision, and no single method is likely to be more accurate than another across taxa which may lead to inconsistent results across taxa and between conspecifics. Inaccurate protein quantification may explain the observed mismatch between organismal N and protein that has plagued some recent studies and that contradicts the principles of ecological stoichiometry. We recommend using a single BCA protocol to reduce inconsistencies across studies, until the promising amino acid analysis becomes more affordable, accurate and accessible to ecologists. Until then, ecologists should consider the abovementioned drawbacks of protein quantification methods and interpret their results accordingly.