Determination of fat, protein and moisture in ricotta cheese by near infrared spectroscopy and multivariate calibration

Madalozzo, Elisângela Serenato; Sauer, Elenise; Nagata, Noemi

doi:10.1007/s13197-013-1147-z

Cited by 36 publications

(21 citation statements)

References 29 publications

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“…Among them, we included some fruits that typically grow in the Sicilian area and demonstrated important health benefits, such as red oranges (Grosso et al 2013), prickly pears (Feugang et al 2006), pomegranates (Sreekumar et al 2014), artichoke (Rondanelli et al 2013) and some characteristic foods that may have peculiar nutritional profile [i.e. ''ricotta'' whey cheese have less fats than more common cheeses (Madalozzo et al 2015)]. We also included several varieties of fisheries and nuts, which may be highly characterized in the Sicilian area and have been demonstrated to exert peculiar effects on health (Gil & Gil 2015;Grosso & Estruch 2016), and distinguished between extra virgin olive oil and other oils (Sacchi et al 2014).…”

Section: Food Frequency Questionnairementioning

confidence: 99%

Reliability and relative validity of a food frequency questionnaire for Italian adults living in Sicily, Southern Italy

Marventano

Mistretta

Platania³

et al. 2016

International Journal of Food Sciences and Nutrition

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The aim of this study was to develop and test the reliability and relative validity of a food frequency questionnaire (FFQ) specifically developed for individuals living in Sicily, southern Italy. This study was conducted on a convenient sample of 178 adult volunteers aged 18-80 years recruited in the urban population of Catania. Dietary intake estimated by 2 FFQs was compared with six 24-h recalls covering a period of 10 months. A total of 110 food items were included in the FFQ. Person's coefficients between the first FFQ and mean of the six 24-h recalls showed high correlations for coffee, tea, pasta and dairy products, alcohol, total fats and carbohydrates (in women). The test-retest analysis showed high reproducibility of the FFQ. We showed that our FFQ provided a useful estimate of both food and nutrient intake in a healthy adult population.

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Section: Food Frequency Questionnairementioning

confidence: 99%

Reliability and relative validity of a food frequency questionnaire for Italian adults living in Sicily, Southern Italy

Marventano

Mistretta

Platania³

et al. 2016

International Journal of Food Sciences and Nutrition

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“…For construction of the model for moisture analysis by NIRS, the R 2 values for calibration and validation were considered low in all treatments. Madalozzo, Sauer & Nagata (2015), in their study on the physicochemical characterization of ricotta cheese also using NIRS methodology, verified a correlation coefficient of 0.851% for calibration and a coefficient of 0.757% for validation. They also stated that there was a lower capacity prediction model for moisture determination as verified in the present study.…”

Section: Discussionmentioning

confidence: 79%

Proximate composition determination in goat cheese whey by near infrared spectroscopy (NIRS)

Galdino

Salles

Santos

et al. 2020

PeerJ

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Background In Brazil, over the last few years there has been an increase in the production and consumption of goat cheeses. In addition, there was also a demand to create options to use the whey extracted during the production of cheeses. Whey can be used as an ingredient in the development of many products. Therefore, knowing its composition is a matter of utmost importance, considering that the reference methods of food analysis require time, trained labor and expensive reagents for its execution. Methods Goat whey samples produced in winter and summer were submitted to proximate composition analysis (moisture, total solids, ashes, proteins, fat and carbohydrates by difference) using reference methods and near infrared spectroscopy (NIRS). The spectral data was preprocessed by baseline correction and the Savitzky–Golay derivative. The models were built using Partial Least Square Regression (PLSR) with raw and preprocessed data for each dependent variable (proximate composition parameter). Results The average whey composition values obtained using the referenced methods were in accordance with the consulted literature. The composition did not differ significantly (p > 0.05) between the summer and winter whey samples. The PLSR models were made available using the following figures of merit: coefficients of determination of the calibration and prediction models (R2cal and R2pred, respectively) and the Root Mean Squared Error Calibration and Prediction (RMSEC and RMSEP, respectively). The best models used raw data for fat and protein determinations and the values obtained by NIRS for both parameters were consistent with their referenced methods. Consequently, NIRS can be used to determine fat and protein in goat whey.

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“…Examining artisanal and industrial Ricotta samples Mattera et al (35) noticed that industrial Ricotta showed a greater homogeneity in view of their chemical composition. Lack of uniformity with greater coefficients of variation found for fat (48.35%) and protein (23.61%) was determined in a research done by Madalozzo et al (36). Casti et al (30) indicated the role of raw material quality and contrary to our results they obtained higher values for total solids (42.12%), fat (19.55%), protein (14.84%) and salt (3.42%) for Ricotta produced from whey from sheep milk cheeses.…”

Section: Discussionmentioning

confidence: 91%

Comparison of the Chemical Composition of Whey Cheeses: Urda And Ricotta

Paskaš

Miočinović

Savić

et al. 2019

Macedonian Veterinary Review

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This study was conducted to evaluate the nutritional quality of two types of cheese prepared from bovine whey: Urda and Ricotta. Cheeses were examined for chemical parameters and their amino acids profile was determined. The results revealed that the chemical composition of the observed whey cheeses was highly significantly different (p<0.01) from each other. The amounts of dry matter, fat, protein, lactose, ash and salt were higher in Ricotta compared with Urda cheese samples. On the other hand, Urda contained more moisture, fat on a dry matter basis and moisture on a fat-free basis (79.59%, 27.50%, 84.27% versus 69.82%, 21.02%, 74.56%, respectively). Especially higher yield, salt in moisture content and energy values were observed in Ricotta cheese (5.93%, 3.12%, 145.99Kcal/100g versus 4.39%, 2.40%, 108.97Kcal/100g; Ricotta and Urda, respectively). Whey cheeses are a particularly good source of amino acids containing approximately - Ricotta: leucine (1.60g/100g), lysine (1.17g/100g), phenylalanine (0.78g/100g) and followed by threonine (0.77g/100g), while Urda contained leucine (0.80g/100g), lysine (0.45g/100g), threonine (0.68g/100g) and phenylalanine (0.31g/100g). Both cheese varieties contained glutamic and aspartic acid as the predominant non-essential amino acids (Ricotta: 3.91g/100g and 1.68g/100g versus Urda: 1.65g/100g and 0.80g/100g, respectively). Generally, from a nutritional point of view, the investigated whey cheeses could be considered as cheeses with low salt and fat content, as well as cheeses particularly abundant in branched chain amino acids (leucine, isoleucine and valine). These results also emphasize their advantages as products that present a cost-effective way of dealing with whey as waste material.

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Determination of fat, protein and moisture in ricotta cheese by near infrared spectroscopy and multivariate calibration

Cited by 36 publications

References 29 publications

Reliability and relative validity of a food frequency questionnaire for Italian adults living in Sicily, Southern Italy

Reliability and relative validity of a food frequency questionnaire for Italian adults living in Sicily, Southern Italy

Proximate composition determination in goat cheese whey by near infrared spectroscopy (NIRS)

Comparison of the Chemical Composition of Whey Cheeses: Urda And Ricotta

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