Effect of genotype and pretreatment of field peas (Pisum sativum) on their dehulling and cooking quality

Field peas (Pisum sativum), an important pulse crop in Australia, are consumed as human food either as whole seeds or as splits after decortication. The yield of splits is an important economic factor for processors and the cooking quality is important for consumers. Effects of genotype, other physical characteristics and pretreatment in various solutions on both dehulling and cooking quality were studied for 23 known genotypes and are market sample of unknown genotype. Large variations were found for most characteristics. Seed size was positively correlated with yield of splits while husk content and broken seeds were negatively correlated with yield. Preconditioning seeds in salt solutions improved yield of splits. Variation in cooking quality among genotypes was reduced following splitting and cooking time was reduced by decortication and splitting and by presoaking in salt solutions (10 or 20 g kg⁻¹), particularly with sodium tripolyphosphate. Loss of seed material into cooking water was correlated with cooking time. No characteristic was found that could be used to predict cooking time. © 1998 SCI.     

Exocrine Pancreatic Secretions in Young Pigs Fed Diets Containing Faba Beans (Vicia faba) and Peas (Pisum sativum): Nitrogen,Protein and Enzyme Secretions

Two experiments were carried out to investigate the effect of feeding diets containing faba beans and peas on pancreatic secretions in young pigs fitted with a pancreatic pouch re-entrant cannula. In Experiment 1, eight barrows, with an average initial weight of 8·5 kg, were fed one of two maize starch-based diets formulated to contain 200 g crude protein (CP) kg⁻¹ according to a completely randomised design. In one of the diets, soya bean meal was the sole protein source; in the other diet, soya bean meal and faba beans (cv Fibro; dark-flowering) each supplied 50% of the dietary CP. In Experiment 2, five barrows, with an average initial weight of 18·1 kg, were fed one of two diets according to a two-period change-over design. The diets were formulated to contain 150 g CP kg⁻¹ with peas (cv Ascona or cv Radley) as the sole protein source. In both experiments, the experimental periods consisted of 8 days: 6 days adaptation followed by a 2 day collection of pancreatic juice. The soya bean meal diet and the faba bean diet contained 0.04 and 0.21% tannins (catechin equivalents), respectively. The trypsin inhibitor activities of the Ascona and Radley pea diets were 0·76 and 3·24 mg of trypsin inhibited per gram, respectively. In both experiments, diet did not affect ( P> 0·05) the pancreatic secretions of nitrogen, protein, amylase, lipase and chymotrypsin. In Experiment 1, specific trypsin activity was higher ( P< 0·05) in pancreatic juice from pigs fed the diet containing soya bean meal and faba beans (53700 units litre⁻¹) than for those fed the soya bean meal diet (41200 units litre⁻¹). However, there was no effect ( P> 0·05) when trypsin activity was expressed as total activity (units 24 h⁻¹). It is concluded that the inclu-sion of faba beans and peas in diets for young pigs has only minor effects on exocrine pancreatic secretions.     

Assessment of maximum cooking temperatures in previously heat treated beef. Part 1: Near infrared spectroscopy

Near infrared diffuse reflectance (NIR) and transmittance (NIT) spectroscopy were studied as potential methods for determination of the previous heat treatment of beef. Ninety-four samples of M longissimus dorsi from 33 bulls were heat treated at nine different temperatures between 50 and 85°C, and analysed by NIR and NIT spectroscopy. The samples were analysed by NIR and NIT in both ‘wet’ and freeze dried states. The NIR and NIT methods were able to determine the maximum temperature of previously heat treated beef with a prediction error of 2.0-2.1°C in the temperature range 50–85°C. Freeze drying of the samples prior to analysis reduced the prediction error to 1.4°C for the NIR method. NIR and NIT should be useful as fast screening methods to determine whether beef has been adequately heat treated.     

基于近红外光谱技术的大米品质分析与种类鉴别

应用近红外光谱(NIRS)技术建立了大米食味品质分析与种类快速鉴别的方法。提取了102份粉碎后大米样品的近红外光谱,采用偏最小二乘法(PLS)建立了大米水分、蛋白质和直链淀粉定量分析模型,对模型预测结果的准确性进行了评价。预测模型的内部交叉验证决定系数(R2)分别为:0.992、0.9792和0.9736;内部交叉验证标准差(RMSECV)分别为:0.141、0.201和0.209;模型外部验证决定系数(R2)分别为0.9861、0.912和0.9373;外部验证标准差(RMSEP)分别为0.179、0.206和0.243。通过计算样品的近红外光谱图之间的欧氏距离来反映不同样品间的差异,对不同属性和不同产地的大米进行了定性聚类分析,种类识别准确率达到100%。结果表明,NIRS分析技术可以用于对大米品质和种类的快速无损检测。     

Application of near infrared (NIR) spectroscopy coupled to chemometrics for dried egg-pasta characterization and egg content quantification

Dried egg pasta is an important and traditional food in the Italian cuisine, and the eggs in pasta improve its nutritional value and organoleptic properties. For this reason the percentage of eggs present in the products sold as “egg pasta” has to always be clearly reported in the label. In this respect, the present research addresses the possibility of developing a method which would allow fast, simple and economic determination of egg content in dried egg-pasta, using near-infrared spectroscopy and chemometric analysis. However, as it is very likely that the spectroscopic fingerprint can also be affected by the manufacturing process of this product, in particular by drying temperature and time, the effect of the manufacturing process on the spectral profile of egg-pasta samples was thoroughly investigated, using experimental design coupled to a multivariate exploratory data analytical technique called ANOVA–Simultaneous Component Analysis (ASCA). Moreover, once confirmed the significance of the drying effect on spectral shape, with the aim of building a calibration model to quantify the egg content in pasta samples irrespective of the manufacturing protocol adopted, a non-linear approach based on local regression, namely LWR-PLS, was investigated. This method allowed the determination of the egg content in external validation samples with low error (RMSEP = 1.25), resulting in predictions more accurate and precise than those obtained by a global PLS model.     

Predicting of intramuscular fat content in pork using near infrared spectroscopy and multivariate analysis

The potential of near infrared (NIR) spectroscopy combined with chemometrics methods was studied to rapidly detect intramuscular fat (IMF) content in pork. Near infrared diffuse reflectance spectra were recorded both with an FT-NIR and a USB4000 spectrometer. The data analysis was compared on different sample preparation, spectral range and spectra pretreatment. According to calibration statistics, best calibration for IMF showed R²_cal of 0.94, R²_val of 0.92, RMSEC of 0.233, RMSEP of 0.462 and RPD of 2.29. The prediction of IMF content for minced samples was more accurate than that for intact samples. The spectra obtained using FT-NIR contained much information correlating to the IMF content than the Vis-NIR spectra of USB4000. The results showed that NIR spectroscopy technique can be used to determine the IMF content in pork as a rapid, convenient, and feasible analysis tool.     

Direct determination of polymerised triacylglycerides in deep-frying vegetable oil by near infrared spectroscopy using Partial Least Squares regression

A green method for the determination of polymerised triacylglyceride (PTG) in deep-frying vegetable oils of different botanic origin has been developed employing near infrared (NIR) spectroscopy and Partial Least Squares (PLS) regression. Four different types of oil were heated during several hours, with and without the addition of foodstuff. NIR transmission spectra were obtained directly from sample aliquots stored in glass vials, thus avoiding the consumption of solvents and minimising waste generation. Variables employed for building the PLS models were selected applying interval PLS (iPLS) as well as Uninformative Variable Elimination-PLS (UVE-PLS). A global PLS model using spectra of all four types of oils was compared to PLS models established for each oil type. Due to the small differences observed in the NIR spectra that can be related to the different botanic origin and results obtained from the PLS model comparison, the use of a global PLS model is recommended leading to prediction errors of 2.28% (w/w) for the determination of PTG in oils employed for frying different kinds of foods.     

Effect of gamma irradiation and frozen storage on chemical and sensory characteristics of rainbow trout (Oncorhynchus mykiss) fillet

The present study was conducted to evaluate the combined effect of low‐dose gamma irradiation (1, 3 and 5 kGy) and frozen storage (5 months at ?20 °C) on chemical and sensory characteristics of rainbow trout (Oncorhynchus mykiss) fillet. Our statistical analysis showed that irradiation process and frozen storage time had a significant effect (P < 0.05) on total volatile nitrogen (TVN), peroxide value (PV), thiobarbituric acid (TBA) and pH. The level of all of these factors increased with increasing frozen storage time. At the end of the fifth month of frozen storage, the lowest and the highest level of TVN, PV and TBA were corresponding to the irradiated samples at 3 and 5 kGy, respectively. In terms of the overall acceptability of their texture, odour, colour and taste, irradiated samples at 3 kGy had the best quality and remained acceptable after 5 months frozen storage. The optimum dose of gamma radiation of rainbow trout fillets according to chemical and sensory analysis was obtained at 3 kGy.     

Nondestructive estimation of maturity and textural properties on tomato ‘Momotaro’ by near infrared spectroscopy

Near infrared spectroscopy offers the possibility to classify and predict the internal quality of fruits and vegetables. The objective of this study was to evaluate the ability of near infrared spectroscopy to classify the maturity level and to predict textural properties of tomatoes variety “Momotaro”. Principal component analysis (PCA) and Soft independent modeling of class analogy (SIMCA) were used to distinguish among different maturities (mature green, pink and red). Partial least squares (PLS) regression was used to estimate textural properties, alcohol insoluble solids and soluble solids content of the tomatoes. The PCA calibration model with mean normalization pretreatment spectra of mature green tomatoes, gave the highest distinguishability (96.85%). It could classify 100.00% of red and pink tomatoes. The SIMCA model could not give better accuracy in maturity classification than individual PCA models. Among the textural parameters measured, the bioyield force from the puncture test with the near infrared (NIR) spectra (between 1100 and 1800 nm) pretreated by multiplicative scatter correction (MSC) had the highest correlation coefficient between NIR predicted and reference values (r = 0.95) and lowest standard error of prediction (SEP = 0.35 N) and bias of 0.19 N. The ratio of standard deviation of reference data of prediction set to standard error of prediction (RPD) was 2.71. In the case of Momotaro tomato, NIR spectroscopy by using PLS regression could not predict alcohol insoluble solids in fresh weight accurately but could predict soluble solids content well with r of 0.80, SEP of 0.210 %Brix and bias of 0.022 %Brix.     

Characterization of marama bean (Tylosema esculentum) by comparative spectroscopy: NMR, FT-Raman, FT-IR and NIR

The marama bean from Southern Africa has proven to be a source for production of various healthy food products. In order to exploit its commercial potential, it is important to know its chemical composition in more detail. In this study, marama beans from different geographical sites and harvest years were analyzed by use of infrared, near infrared, Raman, and ¹H as well as ¹³C nuclear magnetic resonance spectroscopy. These techniques can measure single beans in a rapid and non-destructive manner. By comparative application, the qualitative composition of the marama bean was explored in detail, revealing large amounts of protein, dietary fiber and unsaturated fat. The carbohydrate fraction was largely present as pectins and a minor fraction of smaller water soluble carbohydrates were tentatively assigned to raffinose. It is characteristic that the beans do not contain starch or ??-glucans and that the water soluble part of the proteins/peptides have a high content of the aromatic amino acid tyrosine.