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This study aimed to evaluate the feasibility of mid-infrared (MIR; 5000–900 cm−1) and visible/near-infrared (Vis/NIR; 400–2500 nm) spectroscopy to discriminate organic (ORG) from conventional (CONV) bulk milk. Samples (n = 225) from 24 farms (ORG, n = 12; CONV, n = 12) located in the same area, mainly rearing Holstein-Friesian cows, under similar management conditions, except for ORG livestock spending a period of time on pasture, were collected from September 2019 to August 2020. Chemical composition of the lactation ration was similar between groups. Mid-infrared and Vis/NIR spectrum of each sample were collected. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were done using R software. For the PLS-DA, records were divided in a train set (8 farms/group) and a test set (4 farms/group), and only wavelengths with VIP >1 were retained. The PCA was not able to discriminate both groups. The PLS-DA revealed an accuracy of the model in the test set of 54.1% and 62.9%, for MIR and Vis/NIR, respectively. In conclusion, both infrared regions performed similarly, and the moderate accuracy of the PLS-DA could be related to the similarity of the selected farms between both categories.Highlights Infrared spectra from bulk milk samples of organic and conventional farms were similar. Low accuracy using partial least squares-discriminant analysis. Both MIR and Vis/NIR infrared regions performed similarly.

espanolEntre noviembre 2018 y febrero 2019 se envio por e-mail, a 1.055 ganaderos ecologicos espanoles un cuestionario sobre ganaderia ecologica para obtener informacion sobre las preocupaciones y uso de insumos “polemicos” del sector. Un total de 116 respuestas fueron retenidas para el analisis. El perfil de los/as participantes (68 % hombres) y las caracteristicas de las explotaciones participantes (67 % con una sola especie animal) son representativos del sector ganadero ecologico espanol. En relacion a los insumos polemicos, los ganaderos encuestados indicaron dificultad para encontrar informacion sobre el uso de alternativas a antibioticos, antiparasitarios y vitaminas sinteticas. Sin embargo, encontraron poca dificultad en conseguir informacion sobre las camas de los animales, aunque la mayoria declararon utilizar la paja. Manifestaron que sus principales preocupaciones son la alimentacion/nutricion, el bienestar animal y la salud animal. No obstante, en la transicion a ecologico las mayores preocupaciones fueron la salud animal y los costes de produccion. El 65 % de los encuestados no administraron antibioticos a sus animales en el ultimo ano y el uso de terapias alternativas dependio del problema de salud a tratar, aunque indicaron confiar mayoritariamente en tratamientos de uso convencional. En base a una pregunta con multiples respuestas, la mayoria de los participantes declararon informarse sobre tratamientos alternativos mayoritariamente a traves de veterinarios e internet. En conclusion, si bien los costes de produccion fueron importantes en la conversion a ecologico, las principales preocupaciones como ganaderos ecologicos estan relacionadas con la salud y el bienestar animal. Ademas, los tratamientos alternativos como la fitoterapia, la homeopatia e incluso aditivos como los probioticos aun presentan un uso minoritario EnglishAn on-line questionnaire was emailed to 1,055 organic farmers from November 2018 to February 2019 to gather information about issues and use of contentious inputs in organic production. A total of 116 responses were retained for the analysis. Characteristics of the participants (68 % men) and participating farms (67 % only had one species) were representatives of the Spanish organic livestock sector. In relation to the use of contentious inputs, participants indicated more difficult to find information about the use of alternatives on antibiotics, antiparasitics, and synthetic vitamins than to find information for animals’ bedding; although, they mostly use straw as bedding material. They indicated feeding/nutrition, welfare, and animal health as main concerns nowadays in their farms, and animal health and production cost when moving to organic farming. In the last year, 65 % of the farmers did not administer antibiotics to their animals and the use of alternative therapies depended on the health issue they were facing, although they still relied more on conventional treatments. Based on a multiple- check response, most farmers declared to mainly obtain information about the use of alternatives treatments trough veterinarians and the internet. In conclusion, despite production costs were relevant when deciding becoming an organic farmer, their main concerns as organic producers were related to animal health and welfare. Moreover, there is still a scarce use of alternatives treatments such as phytoterapy, homeopathy, as well as additives such as the probiotics

Studies on goat milk have mainly focused on cosmopolitan breeds and very limited information is available on local breeds, which is important for biodiversity preservation and local cheese production. The aim of this study was to evaluate the breed effect on milk yield, composition and somatic cell score (SCS) of five local Italian goat breeds (Garganica, Girgentana, Jonica, Maltese and Mediterranean Red) compared with a cosmopolitan specialized dairy breed (Saanen). A total of 60 goats (10 per breed) from an experimental farm were enrolled in the study. Milk yield, composition and SCS were recorded and analyzed every 2 weeks during the entire lactation. Data were analyzed using a mixed model with repeated measures. Saanen yielded between 0.27 and 0.62 kg day−1 more milk than the local breeds. Among local breeds, Maltese and Jonica were the most productive, with an average of 1.28 and 1.25 kg day−1, respectively, while Mediterranean Red, Garganica and Girgentana produced ≤1 kg day−1. Saanen had the highest SCS (6.81) and the lowest fat content (3.26 %). In relation to protein, Garganica showed the greatest content (3.71 %), and Saanen had a similar content to other local breeds (3.42 %) except for Maltese, which was lower (3.11 %). Saanen and Garganica had the lowest lactose percentage (4.28 % and 4.26 %, respectively). All breeds followed a similar pattern across lactation: SCS and fat and protein content peaked at the end of the lactation, whereas lactose percentage was highest at the beginning of the lactation. Differences between Saanen and the local breeds for milk yield, composition and SCS were consistent across lactation. In conclusion, local breeds produced less milk but with lower SCS and greater fat and lactose content than the Saanen cosmopolitan breed, suggesting a better milk quality.

The interest for safe and natural foods of animal origin is currently increasing the use of plant feed additives (PFA) as antioxidants in animal nutrition. However, studies with livestock animals dealing with PFA as antioxidants are scarce. The aim of the present review was to evaluate the antioxidant impact of PFA compared with synthetic vitamins on animal food product yield and quality. For this purpose, peer-reviewed studies published between 2000 and 2020 were collected. Most papers were carried out on ruminants (n = 13), but PFA were also tested in swine (n = 6) and rabbits (n = 2). The inclusion of PFA in the diets of pigs, rabbits, and ruminants improved the products’ quality (including organoleptic characteristics and fatty acids profile), oxidative stability, and shelf life, with some impacts also on their yields. The effects of PFA are diverse but often comparable to those of the synthetic antioxidant vitamin E, suggesting their potential as an alternative to this vitamin within the diet.

Scientific evidence demonstrates that plant feed additives (PFA) can be a viable alternative to synthetic antioxidant vitamins in poultry nutrition. PFA are represented by plants, essential oils, plant extracts, and by-products from herbal or crop processing. The use of PFA in the feed industry has increased in recent years as their biologically active compounds (polyphenols) have demonstrated antimicrobial and antioxidant effects in food-producing animals. However, few trials have directly compared the effects of PFA with synthetic vitamins. After a systematic literature review of studies comparing the effects of PFA and synthetic vitamins on poultry products in the last 20 years (2000– 2020), a total of 44 peer-reviewed articles were included in the present work. A positive effect of PFA on poultry products’ oxidative stability during storage, organoleptic characteristics, and fatty acids profile has been observed without a specific impact on their performances. The effects of PFA are variable but often similar to those of vitamin E, suggesting the opportunity for a partial substitution of the latter in poultry diets.

Barley grains contain a variable amount of biologically active compounds such as non-starch polysaccharides and phenol compounds. These compounds are important in nutrition due to their significant health benefits and technological role in food. We developed predictive models for β-glucans (BG), arabinoxylans (AX), bound phenols (BP), free phenols (FP), and anthocyanins (AN) based on near-infrared spectroscopy (NIRS) using two different NIRS instruments with different spectral range and spectral steps. Regressions of modified partial least squares (MPLS) and several combinations of scattering correction and derivative treatments were tested. The optimal calibration models generated high coefficients of determination for BG and BP, but not for AN content. The instrument with the highest resolution only gave better results for BG prediction models, and the addition of the visible range did not prove to be ostensibly advantageous to the determination of any of the active compounds of study, not even in the case of AN analysis. This research was funded by MINECO/FEDER (AGL2015–69435-C3–3-R) project (Spain). Vis-NIR spectrometer DS2500 was funded by Progetto di Eccellenza "Centro per l'Agricoltura, la Sostenibilità e gli Alimenti" (CASA), CUP C26C18000190001, MIUR (Italy).

Plant feed additives (PFA) such as essential oils, extracts, and by-products from plant processing can be included in poultry diets. A total of 39 peer-reviewed articles were selected from the literature published in the last 20 years (2000–2020) comparing PFA antioxidant effects with synthetic antioxidant vitamins (mainly vitamin E) in poultry nutrition. The PFA can be used as an effective nutritional strategy to face poultry’s oxidative stress with positive impact also on their productivity and efficiency. They can partially or completely replace antioxidant synthetic vitamins (the latter administered at doses between 150 and 500 mg/kg) in animal diets, sometimes affecting important physiological functions or expressing synergistic effect with the synthetic antioxidants. It is crucial to take into consideration the issues related to the absorption and the metabolism of these additives and their interaction with gut microbiota. However, some form- and dose-dependent negative effects on growth performances are observed.

Flexitarians have reduced their meat consumption showing a rising interest in plant-based meat alternatives with ‘meaty’ characteristics, and we are witnessing an unprecedented growth of meat substitutes in the Western market. However, to our knowledge, no information regarding the ‘simulated beef burgers’ nutritional profile compared to similar meat products has been published yet. Here we show that, whilst both plant-based and meat-based burgers have similar protein profile and saturated fat content, the former are richer in minerals and polyunsaturated fatty acids. We found that the most abundant minerals in both categories were Na, K, P, S, Ca, and Mg; being Na and S content similar between groups. Only six amino acids differed between categories, being hydroxyproline exclusively in meat-based burgers. Plant-based burgers revealed fourfold greater content of n-6 than meat-based burgers, and greater short-chain fatty acids proportion. Our results demonstrate how ‘simulated beef’ products may be authenticated based on some specific nutrients and are a good source of minerals. We believe that there is a need to provide complete and unbiased nutritional information on these ‘new’ vegan products so that consumers can adjust their diet to nutritional needs.

This study aimed to assess the feasibility of visible/near-infrared reflectance (Vis-NIR) and near-infrared transmittance (NIT) spectroscopy to predict total and gelatinized starch and fiber fractions in extruded dry dog food. Reference laboratory analyses were performed on 81 samples, and the spectrum of each ground sample was obtained through Vis-NIR and NIT spectrometers. Prediction equations for each instrument were developed by modified partial least squares regressions and validated by cross- (CrV) and external validation (ExV) procedures. All studied traits were better predicted by Vis-NIR than NIT spectroscopy. With Vis-NIR, excellent prediction models were obtained for total starch (residual predictive deviation, RPDCrV = 6.33, RPDExV = 4.43), gelatinized starch (RPDCrV = 4.62, RPDExV = 4.36), neutral detergent fiber (NDF, RPDCrV = 3.93, RPDExV = 4.31), and acid detergent fiber (ADF, RPDCrV = 5.80, RPDExV = 5.67). With NIT, RPDCrV ranged from 1.75 (ADF) to 2.61 (acid detergent lignin, ADL) and RPDExV from 1.71 (ADL) to 2.16 (total starch). In conclusion, results of the present study demonstrated the feasibility of at-line Vis-NIR spectroscopy in predicting total and gelatinized starch, NDF, and ADF, with lower accuracy for ADL, whereas results do not support the applicability of NIT spectroscopy to predict those traits.

This study aimed to describe metabolic, oxidative, and mineral blood profiles of Saanen does through lactation compared with Mediterranean breed clusters (Maltese and Rossa Mediterranea, and Jonica, Garganica, and Girgentana). Milk and blood samples of 57 dairy goats (9&ndash, 10 goats per breed) were collected from the 2nd to the 30th week of lactation every 2&ndash, 3 weeks. Saanen showed greater milk yield and somatic cell score, and lower fat and protein percentage through lactation (p &lt, 0.05) than the Mediterranean breed clusters. Blood analysis revealed that stage of lactation had a greater impact than breed cluster, except for uric acid, alkaline phosphatase, and aspartate aminotransferase. Plasmatic non-esterified fatty acids indicated a greater negative energy balance in Saanen than the other breed clusters during early and medium lactation stages (p &lt, 0.05). Serum Cl, Mg, and Ca increased in all the breed clusters from early to the following stages of lactation (p &lt, 0.05). No significant prooxidant/antioxidant imbalances were detected in any of the three clusters during the entire lactation. In conclusion, Mediterranean breeds tended to recover earlier from negative energy balance than Saanen, but effects of breed or stage of lactation on long-term oxidative stress indicators were not evident.

Serum metabolic profile is a common method to monitor health and nutritional status of dairy cows, but blood sampling and analysis are invasive, time-consuming, and expensive. Milk mid-infrared spectra have recently been used to develop prediction models for blood metabolites. The current study aimed to investigate factors affecting blood &beta, hydroxybutyrate (BHB), non-esterified fatty acids (NEFA), and urea nitrogen (BUN) predicted from a large milk mid-infrared spectra database. Data consisted of the first test-day record of early-lactation cows in multi-breed herds. Holstein-Friesian cows had the greatest concentration of blood BHB and NEFA, followed by Simmental and Brown Swiss. The greatest and the lowest concentrations of BUN were detected for Brown Swiss and Holstein-Friesian, respectively. The greatest BHB concentration was observed in the first two weeks of lactation for Brown Swiss and Holstein-Friesian. Across the first month of lactation, NEFA decreased and BUN increased for all considered breeds. The greatest concentrations of blood BHB and NEFA were recorded in spring and early summer, whereas BUN peaked in December. Environmental effects identified in the present study can be included as adjusting factors in within-breed estimation of genetic parameters for major blood metabolites.

High milk somatic cell count (SCC) influences milk production and quality; however, very little is known about the effect of low SCC on milk quality, especially in terms of mineral content and coagulation properties. Thus, the present study aimed to investigate the effects of somatic cell score (SCS), calculated as log2(SCC/100) + 3, on milk yield, composition (fat, crude protein, casein, lactose, milk urea nitrogen, protein fractions, and mineral contents), and coagulation properties of Brown Swiss, Holstein Friesian, and Simmental cows from multibreed herds. Milk composition and coagulation traits were predicted using mid-infrared spectroscopy. The data set comprised 95,591 observations of 6,940 cows in 313 multibreed herds, collected from January 2011 to December 2017. Observations were divided into 8 classes based on SCS. Statistical analysis was performed using a linear mixed model, which included breed, parity, stage of lactation, SCS class, and their interactions as fixed effects, and herd test day, cow, and residual as random effects. The probability that cows experienced SCS > 4.00 at 30 ± 5, 60 ± 5, or 90 ± 5 d after the observation test day was calculated for each SCS class, and odds ratios to the reference class (-1.00 4.00). Moreover, cows with SCS lower than -1.00 on a test day were about 7 times more likely to present high SCS within the following 90 ± 5 d than cows with SCS between -1.00 and 0.00. Breeds responded similarly to the increase of SCS, but the overall loss of fat and crude protein yields, and several minerals among Holstein Friesian were lower with increasing SCS. The best milk yield and quality were observed between SCS 0.00 and 1.00, but milk quality of Holstein Friesians started to decrease at lower SCS compared with milk quality of Brown Swiss and Simmental cows. Results suggest a breed-dependent optimum of SCS, and highlighted that very low SCS can be an indicator of udder health problems and, thus, may be used for early detection of mastitis.

Given consumer interest in Mozzarella di latte di Bufala and other cheeses, and the growing interest of the cheese industry in offering products adequate for lactovegetarian consumers, this study aimed to compare clotting capacity of vegetal and animal rennet in buffalo milk. Milk coagulation properties of 1,261 buffalo bulk milk samples collected during milk quality testing were assessed by lactodynamography using commercial animal (75% chymosin and 25% bovine pepsin) and vegetal (Cynara cardunculus) rennets. Chemical composition of milk samples was predicted by MilkoScan (Foss Analytics, Hillerod, Denmark) calibrated with specific buffalo standards. Rennet effect (animal versus vegetal) was statistically analyzed with a paired t-test. Fat, protein, and lactose contents of milk samples were 7.94%, 4.52%, and 4.80%, respectively. A similar variability of milk coagulation properties was observed with both rennets, with the exception of greater variability of curd firmness at 30 min after the addition of vegetal rennet compared with animal rennet (73 and 26%, respectively). On average, when using plant rennet, milk started to coagulate and reached the 20-mm coagulum 12 ± 0.22 min and 1.9 ± 0.20 min, respectively, later than with animal rennet. Thirty minutes after rennet addition, curds were almost twice as firm in animal as in vegetal rennet (difference of 23.92 ± 0.66 mm). However, curd firmness at 60 min was only 1.21 ± 0.39 mm thicker with vegetal than with animal rennet. Moreover, when using animal rennet, 99.52% of samples started coagulating within the first 30 min of analysis, whereas only 70.42% did so when using vegetal rennet. We conclude that vegetal rennet has the capacity to coagulate buffalo milk, achieving a similar curd firmness to that of animal rennet at 60 min. Further studies are needed to evaluate the sensory characteristics and consumer acceptability of Mozzarella di latte di Bufala processed with vegetal rennet.

Native goat breeds play an important role both in the safeguarding of biodiversity and the development of local economy. This study aimed to evaluate milk coagulation properties (MCP) of local (Garganica, Girgentana, Maltese, Mediterranean Red) and cosmopolitan (Saanen) goat breeds. From May to August 2018, 46 goats were sampled monthly in an experimental farm; milk samples were analysed for fat, protein and lactose percentages, pH, SCC and MCP. Data were evaluated through a mixed linear model with repeated measures, including breed, month of lactation and parity as fixed effects. Month of lactation affected all studied traits, and breed affected MCP, protein percentage, lactose percentage and pH. Milk composition and coagulation properties were better in local breeds than Saanen. In particular, milk of local breeds was richer in protein percentage, and coagulated and reached 20 mm of curd firmness on average 3.14 and 2.56 min earlier than Saanen, respectively. Moreover, the firmest curd was observed in Girgentana (31.44 mm) and the weakest in Garganica (21.72 mm). Rennet coagulation time and curd firmness decreased towards the end of lactation, differing significantly between May (10.62 min and 31.69 mm, respectively) and August (8.33 min and 20.69 mm, respectively), whereas curd-firming time only differed between May and June–July. In conclusion, milk of local breeds showed better milk coagulation ability than the cosmopolitan breed.Highlights Breed and month of lactation were important sources of variation of goat MCP. Local goat breeds showed better MCP than Saanen. Valorisation of the milk from the local breeds might be a tool to preserve native genetic resources.

Milk filtration procedures are gaining relevance in the dairy industry because milk ultra- and nanofiltrates are used to increase milk processing efficiency, and as additives for products with improved nutraceutical properties. This study aimed to develop Fourier-transformed mid-infrared spectroscopy calibrations for ultra- and nanopermeate and retentate fractions of defatted and delactosated milk. A total of 154 samples from different milk fractions were collected and analyzed using reference methods to determine protein, solids-not-fat, glucose, and galactose content. The obtained values were matched with their respective Fourier-transformed mid-infrared spectroscopy spectra to develop new prediction models. Calibrations for each trait were built following 3 different approaches to get the best prediction models: (1) using the entire data set, (2) using 3 subsets based on component concentrations (level approach), and (3) using hierarchical clusters calculated with pairwise Mahalanobis distance among spectra (cluster approach). Calibrations were developed using partial least squares regression, after removing low signal-to-noise ratio wavelengths, and validated through a leave-one-out cross-validation procedure. In addition, the accuracy of the predicted values within each fraction was checked for each approach. Dividing the data set into subsets improved prediction models for each trait and for the samples in each milk fraction. Without considering milk fraction, the best improvement was observed for glucose and galactose. Glucose ratio performance deviation in cross-validation (RPD) increased from 7.42 to 11.31 and 11.06, for cluster and level approaches, respectively, whereas galactose RPD increased from 8.86 to 11.69 and 11.27 for cluster and level approaches, respectively. Considering milk fractions, the best improvement was observed for protein content, where RPD ranged from 0.08 to 6.06 for the whole data set calibration, whereas it ranged from 0.43 to 40.34 for the subset calibration approaches. Cluster and level approaches to build calibration models were comparable for samples from different fractions, suggesting that the 2 subsetting protocols should be both investigated to get the best prediction performances.

This paper investigated sources of variation of milk fatty acid (FA, g/100 g total FA) profile routinely predicted by mid-infrared spectroscopy in Pinzgauer dual-purpose cattle breed. A total of 19,578 individual milk samples collected from 1232 cows and 77 herds between 2011 and 2014 were available for phenotypic characterisation. Data were analysed using a linear mixed model which included stage of lactation, parity and their interaction as fixed effects, and cow and herd-test-day as random effects. Milk yield averaged 20.87 kg/d, and means for fat, protein and casein were 4.01, 3.44 and 2.72%, respectively. Saturated FA (SFA), monounsaturated FA (MUFA) and polyunsaturated FA (PUFA) averaged 69.20, 25.43 and 3.19 g/100 g total FA, respectively. About half of the SFA were provided by C16:0 (31.24 g/100 g total FA), and almost all MUFA by C18:1 (22.18 g/100 g total FA). Fixed effects were significant in explaining the variation of the studied traits. Milk of first-parity cows had the lowest percentage of SFA, medium-chain FA and C14:0, and the greatest percentage of MUFA, PUFA, trans FA, short- and long-chain FA, and C18:1. Saturated FA, C14:0 and C16:0 increased from calving until 120 days in milk, whereas unsaturated FA, MUFA, PUFA, long-chain FA, C18:0 and C18:1 decreased. Although both parity and stage of lactation affected milk FA, greater variation was observed during lactation than among parities.

The aim of the present study was to investigate sources of variation of milk composition and technological characteristics routinely collected in field conditions in the Italian dairy industry. A total of 40,896 bulk milk records from 620 herds and 10 regions across Italy were analyzed. Composition traits were fat, protein, and casein percentages, urea content, and somatic cell score; and technological characteristics were rennet coagulation time, curd firming time, curd firmness 30 min after rennet addition to milk, and titratable acidity. Data of herd bulk milks were analyzed using a model that included fixed effects of region, herd nested within region, and season of milk analysis. An average good milk quality was reported in the dairy industry (especially concerning fat, protein, and casein percentages), and moderate to high correlations between composition and technological traits were observed. All factors included in the statistical model were significant in explaining the variation of the studied traits except for region effect in the analysis of casein and somatic cell score. Northeast and central-southern Italian regions showed the best performance for composition and technological features, respectively. Traits varied greatly across regions, which could reflect differences in herd management and strategies. Overall, less suitable milk for dairy processing was observed in summer. Results of the present study suggested that a constant monitoring of technological traits in the dairy industry is necessary to improve production quality at herd level and it may be a way to segregate milk according to its processing characteristics.

The aim of the study was to evaluate the feasibility of near infrared (NIR) transmittance spectroscopy to predict cheese ripeness using the ratio of water-soluble nitrogen (WSN) to total nitrogen (TN) as an index of cheese maturity (WSN/TN). Fifty-two Protected Designation of Origin cow milk cheeses of 5 varieties (Asiago, Grana Padano, Montasio, Parmigiano Reggiano, and Piave) and different ripening times were available for laboratory and chemometric analyses. Reference measures of WSN and TN were matched with cheese spectral information obtained from ground samples by a NIR instrument that operated in transmittance mode for wavelengths from 850 to 1,050 nm. Prediction equations for WSN and TN were developed using (1) cross-validation on the whole data set and (2) external validation on a subset of the entire data. The WSN/TN was calculated as ratio of predicted WSN to predicted TN in cross-validation. The coefficients of determination for WSN and TN were >0.85 both in cross- and external validation. The high accuracy of the prediction equations for WSN and TN could facilitate implementation of NIR transmittance spectroscopy in the dairy industry to objectively, rapidly, and accurately monitor the ripeness of cheese through WSN/TN.

Milk coagulation and acidity traits are important factors to inform the cheesemaking process. Those traits have been deeply studied in bovine milk, whereas scarce information is available for buffalo milk. However, the dairy industry is interested in a method to determine milk coagulation and acidity features quickly and in a cost-effective manner, which could be provided by Fourier-transform mid-infrared (FT-MIR) spectroscopy. The aim of this study was to evaluate the potential of FT-MIR to predict coagulation and acidity traits of Mediterranean buffalo milk. A total of 654 records from 36 herds located in central Italy with information on milk yield, somatic cell score, milk chemical composition, milk acidity [pH, titratable acidity (TA)], and milk coagulation properties (rennet coagulation time, curd firming time, and curd firmness) were available for statistical analysis. Reference measures of milk acidity and coagulation properties were matched with milk spectral information, and FT-MIR prediction models were built using partial least squares regression. The data set was divided into a calibration set (75%) and a validation set (25%). The capacity of FT-MIR spectroscopy to correctly classify milk samples based on their renneting ability was evaluated by a canonical discriminant analysis. Average values for milk coagulation traits were 13.32 min, 3.24 min, and 39.27 mm for rennet coagulation time, curd firming time, and curd firmness, respectively. Milk acidity traits averaged 6.66 (pH) and 7.22 Soxhlet-Henkel degrees/100 mL (TA). All milk coagulation and acidity traits, except for pH, had high variability (17 to 46%). Prediction models of coagulation traits were moderately to scarcely accurate, whereas the coefficients of determination of external validation were 0.76 and 0.66 for pH and TA, respectively. Canonical discriminant analysis indicated that information on milk coagulating ability is present in the MIR spectra, and the model correctly classified as noncoagulating the 91.57 and 67.86% of milk samples in the calibration and validation sets, respectively. In conclusion, our results can be relevant to the dairy industry to classify buffalo milk samples before processing.

Background: The new European Regulation 1169/2011 concerning nutrition declaration of food products compels the addition of saturated fatty acids, whereas the declaration of monounsaturated and polyunsaturated fatty acids remains voluntary. Therefore, the industry is interested in a more rapid, easy and less cost-effective analysis method for accomplishing this labelling regulation. The present study aimed to evaluate the ability of near infrared transmittance spectroscopy (wavelengths between 850 and 1050 nm) to predict the fatty acid (FA) composition of commercial processed meat samples (n = 310).; Results: Good predictions were achieved for the absolute content of saturated, unsaturated, monounsaturated and polyunsaturated FA, as well as ω-6 groups, and also for a few individual FA (C16:0, C18:0, C18:1n9, C18:2n6 and 18:1n7), with the coefficient of determination in cross-validation being > 0.90 and the residual prediction deviation being > 3.15. Unsatisfactory models were obtained for the relative content of FA.; Conclusion: Near infrared transmittance spectroscopy can be considered as a reliable method for predicting the main groups of FA in processed meat products, whereas predictions of individual FA are less reliable. © 2017 Society of Chemical Industry.; © 2017 Society of Chemical Industry.

The present study evaluated the ability of near infrared transmittance (NIT) spectroscopy (FoodScan, 850-1050nm) to predict sodium (Na) content in commercial processed meat products (n=310) as intact and ground samples. Prediction models were built with all samples spectra and with spectra divided in 5 categories according to the manufacturing meat process. Sodium content (%) was determined using inductively coupled plasma optical emission spectrometry. Modified partial least squares regression for the overall samples showed satisfactory predictive ability for intact (coefficient of determination in cross-validation, R2CV=0.93) and ground samples (R2CV=0.95). Despite the low number of samples, good specific prediction models were developed for each commercial meat category. In conclusion, NIT is really promising for at-line application to predict Na in processed meat products which could help industry to accomplish the new labelling regulation.

Fatty acid (FA) profile plays an important role on human health and on sensory quality of dairy products. There is few information about breed influence on milk FA profile of local goat breeds. This study aimed to characterize and compare the milk FA profile of 5 local endangered goat breeds (Garganica, Girgentana, Jonica, Maltese, and Mediterranean Red) and a cosmopolitan breed (Saanen) reared in the same farm during a complete lactation. A total of 252 milk samples were collected monthly from 42 goats (7 goats per breed) and analyzed for gross composition and FA profile. Individual FA was determined using gas-chromatography. Data were analyzed using a mixed model with repeated measures with breed and week of lactation as fixed effects. Results showed that the FA profile was significantly affected by week of lactation and only few FA by breed effect (p &lt, 0.05). Overall, the main differences were found between Saanen and local breeds. This study contributed to the characterization of goat milk FA profile, and it may be of interest for the valorization of milk from local goat breeds which seem to have a healthier profile than milk of the cosmopolitan breed.

The pet food industry is interested in performing fast analyses to control the nutritional quality of their products. This study assessed the feasibility of near-infrared spectroscopy to predict mineral content in extruded dry dog food. Mineral content in commercial dry dog food samples (n = 119) was quantified by inductively coupled plasma optical emission spectrometry and reflectance spectra (850&ndash, 2500 nm) captured with FOSS NIRS DS2500 spectrometer. Calibration models were built using modified partial least square regression and leave-one-out cross-validation. The best prediction models were obtained for S (coefficient of determination, R2 = 0.89), K (R2 = 0.85), and Li (R2 = 0.74), followed by P, B, and Sr (R2 = 0.72 each). Only prediction models for S and K were adequate for screening purposes. This study supports that minerals are difficult to determine with NIRS if they are not associated with organic molecules.

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