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Average trace of ten MOS sensor (I-X) measurements (Ω(G)/Ω(G0)) of the electronic nose lasting 30 sec (+y, upper) and standard deviation (-y, below).
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Near infrared (NIR) spectroscopy methods are now widely used in animal science to predict the chemical composition of forages and other foods, including silage. NIR is a convenient and rapid alternative to chemistry methods, which are expensive and time consuming. However, silage analysis using NIR has so far been limited to oven-dried samples, bec...
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... 1675 1781 1887 1993 2099 2205 2311 figure) vs. 5 (middle of figure) and difference between the two classes (bottom of figure). 1.4 Table 3. Optimum number of terms plus cross validation statistics range of parameters developed for two types of instrument. Electronic nose trace and chemometrics: The traces of the ten sensors for 30 sec reported in Fig. 6 show high variations in half of them, but when the causality of each variable was investigated the most sensitive sensor appeared to be Number VIII, which explained more than half of the causalities (at 0.35-0.50 r 2 values) in the studied variables; these were not exactly the same as those clustered by the PCA or CHA (Fig. 1). It ...
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The objective of this research was to examine three techniques for prediction of the chemical composition by NIR spectroscopy (1100 – 2500 nm) from semi-natural grassland: modified partial least squares (MPLS) regression; partial least square (PLS) regression and principal component regression (PCR). A spectral data for a total of 150 samples origi...
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... The utilization of high-quality forages in the formulation of diets for ruminants, thanks to the improvement of rumen fermentation characteristics [13][14][15][16], guarantees animal well-being [17,18] and high quality of animal-based food as well [19][20][21][22]. During the last few years, the use of Near Infrared Spectroscopy (NIRS) technology has been proposed in livestock farms and could be useful for forages, as well as for silages evaluation [23][24][25][26]. The benefits of NIRS use are rapidity, multiplicity of analyses, a low sample size and reduced cost. ...
In formulating balanced rations for ruminants, knowing the chemical composition of forage and feeds in general is crucial to create adequate nutritional plans that meet animals’ feed requirements. From July to December of 2020, a total of 175 samples of corn silage hybrid PR31Y43 grown (135 days of maturity class) in three sites (Piana del Sele, Vallo di Diano and Caserta) of the Campania region (South Italy) were collected and analysed by using a portable Near Infrared Spectroscopy (NIRS). The area of cultivation/storage of corn silage highly (p < 0.05) affected the nutritional characteristics of the analysed samples. The silages produced in the Vallo di Diano showed the significantly highest (p < 0.05) DM content compared to those from the other sites (349.3 vs. 323.4 and 328.1 g/kg as feed from Caserta and Piana del Sele, respectively). The structural carbohydrates were significantly higher (p < 0.05) in Piana del Sele feed than those in both Caserta and Vallo di Diano feeds (420.1 vs. 396.7 and 397.6 g/kg as feed), whereas the non-fibrous carbohydrates were significantly higher in Caserta and Vallo di Diano feeds (p < 0.05; 469.6 and 471.8 g/kg as feed); intermediate values were registered in the corn silages produced in Piana del Sele (446.6 g/kg as feed). No differences were detected for protein levels. The NIRS technology could be useful to obtain fast and accurate picture of silage quality. The knowledge of the nutritional characteristics of silages can improve the formulation of balanced rations, contributing to guarantee animal welfare and good productive performances.
... Apart from measuring the nutritional constituents and fibre fractions, silages can be evaluated for volatile organic compounds (VOCs) that result from fermentation reactions to assess fermentation quality based on the content of undesired degradation products [5] and VOCs resulting from the metabolism of undesirable microorganisms (bacteria and yeast) [6]. Masoero et al. [7] applied an electronic nose (EN) to analysis silage quality as a simple alternative method for evaluating gaseous components. The EN exhibited advantages over some other analytical methods, including near-infrared spectroscopy (NIR), for the evaluation of fermentation characteristics of silage and it is also superior at estimating total fatty acid and ammonia levels and buffering capacity [6]. ...
The objective of this study was to evaluate the aroma profile, microbial and chemical quality of winter cereals (triticale, oats, barley and wheat) and Italian ryegrass (Lolium multiflorum Lam., IRG) plus winter cereal mixture silages detected with an electronic nose. Four commercial mixtures (mixture A (40% of two cultivars of winter triticale + 30% of two cultivars of winter oats + 20% of winter barley + 10% of winter wheat), mixture B (50% of two cultivars of winter triticale + 40% of winter barley + 10% of winter wheat), mixture C (55% of three types of Italian ryegrass + 45% of two cultivars of winter oat), mixture D (40% of three types of Italian ryegrass + 30% of two cultivars of winter oat + 15% of two cultivars of winter triticale + 10% of winter barley + 5% of winter wheat)) were harvested, wilted and ensiled in laboratory-scale silos (n = 80) without additives. Both the principal component analysis (PCA) score plot for aroma profile and linear discriminant analysis (LDA) classification revealed that mixture D had different aroma profile than other mixture silages. The difference was caused by the presence of high ethanol and LA in mixture D. Ethyl esters such as ethyl 3-methyl pentanoate, 2-methylpropanal, ethyl acetate, isoamyl acetate and ethyl-3-methyl-thiopropanoate were found at different retention indices in mixture D silage. The low LA and higher mold and yeast count in mixture C silage caused off odour due to the presence of 3-methylbutanoic acid, a simple alcohol with unpleasant camphor-like odor. At the end of 90 days fermentation winter cereal mixture silages (mixture A and B) had similar aroma pattern, and mixture C was also similar to winter cereal silages. However, mixture D had different aromatic pattern than other ensiled mixtures. Mixture C had higher (p < 0.05) mold and yeast (Log10 CFU (colony forming unit)/g) counts compared to mixture B. Mixture B and C had higher acetic acid (AA) content than mixture A and D. The lactic acid (LA) content was higher for mixture B than mixture C. In general, the electronic nose (EN) results revealed that the Italian ryegrass and winter cereal mixtures (mixture D) had better aroma profile as compared to winter cereal mixtures (mixture A and B). However, the cereal mixtures (mixture A and B) had better aroma quality than mixture C silage. Otherwise, the EN technology is suitable in finding off odor compounds of ensiled forages.
... Apart from measuring the nutritional constituents and bre fractions, silages can be evaluated for volatile organic compounds (VOCs) that result from fermentation reactions to assess fermentation quality based on the content of undesired degradation products (Borreani et al., 2007) and VOCs resulting from the metabolism of undesirable microorganisms (bacteria and yeast) (Campagnoli and Dell'Orto, 2013). Masoero et al. (2007) applied an electronic nose (EN) to analysis silage quality as a simple alternative method for evaluating gaseous components. The EN exhibited advantages over some other analytical methods, including near-infrared spectroscopy (NIR), for the evaluation of fermentation characteristics of silage and it is also superior at estimating total fatty acid and ammonia levels and buffering capacity (Campagnoli and Dell'Orto, 2013). ...
During silage making microbial fermentation produces an array of end products which can influence the odour of the final silage and can also change many nutritive aspects of a forage. The objective of this study was to evaluate the fermentation quality and aroma profile of winter cereals and Italian ryegrass ( Lolium multiflorum Lam ., IRG) plus winter cereal mixture silages detected with an electronic nose. Four mixtures (mixture A: triticale, oats, barley and wheat; mixture B: triticale, barley and wheat; mixture C: IRG and oats; mixture D: IRG, oats, triticale, barley and wheat) were harvested, wilted and ensiled in laboratory-scale silos (n = 80) without additives. Mixture C had higher ( P < 0.05) mold and yeast (Log 10 CFU (colony forming unit)/g) counts compared to mixture B. Mixture B and C had higher acetic acid (AA) content than mixture A and D. The lactic acid (LA) content was higher for mixture B than mixture C. At the end of 90 days fermentation winter cereal mixture silages (mixture A and B) had similar aroma pattern, and mixture C was also similar to winter cereal silages. However, mixture D had different aromatic pattern than other ensiled mixtures. Both the principal component analysis (PCA) score plot for aroma profile and linear discriminant analysis (LDA) classification revealed that mixture D had different aroma profile than other mixture silages. The difference was caused by the presence of high ethanol and LA in mixture D. Ethyl esters such as ethyl 3-methyl pentanoate, 2-methylpropanal, ethyl acetate, isoamyl acetate and ethyl-3-methylthiopropanoate were found at different retention indices in mixture D silage. The low LA and higher mold and yeast count in mixture C silage caused off odour due to the presence of 3-methylbutanoic acid, a simple alcohol with unpleasant camphor-like odor. In general, the electronic nose (EN) results revealed that the ensiled mixtures were dominated by ethyl ester likely producing pleasant fruity odors which could increase the intake of ensiled mixtures. However, the technology is suitable in finding off odor compounds of ensiled forages that may likely reduce feed intake.
... The analysis of the nutritional composition of farm animal feeds is important for the decision-making process with the purpose to improve quantitative and qualitative productions. Near infrared spectroscopy was adopted already in 1970s for the analysis of forages [18], and since then there have been numerous studies on its applicability in support of animal husbandry [19][20][21][22][23][24]. The objectives of those studies were to develop calibration models for fodder and/or raw materials from different environments. ...
... In these specific feeds, there is the loss of volatile substances such organic acids, alcohols, esters, amines, and ammonia [25]. Alcohols and organic acids are important sources of energy for ruminants and are excellent indicators for the quality of silage fermentation [23]. ...
Dairy farming is increasingly affected by the digital revolution. To respond to current challenges—such as environmental, economic, and social sustainability—new technologies must be adopted, entering the perspective of precision livestock farming. This is made possible by the development of countless sensors to be adopted in the barn. The technology that is affecting various aspects of dairy cattle breeding is certainly near infrared spectroscopy (NIRS) which is versatile and can be used online/inline to evaluate and control the critical points of the production process by entering the PAT (process analytical technology). In the barn, NIRS currently can obtain information on the chemical-physical composition of raw materials, total mixed ration (TMR), feces and digestibility, chemical and technological analysis of milk. All this in a short time by eliminating the waiting times for analysis response and costs, allowing an improvement of livestock management. Many studies affirm the validity of NIRS as a reliable and predictive technology against multiple relevant parameters in matrices such as raw feed, TMR, feces, and milk. This review highlights the usefulness of NIRS technology in dairy farm with particular attention to portable instrumentation usable directly on the farm.
... Essential for future sustainable dairy farming and animal welfare is, therefore, the application of state-of-the-art ration formulation solutions, efficiently using the on-farm available digitized data and management information. Within the smart dairy nutrition concept (SDN) via interfaces, CNCPS can take advantage of the vast and readily available digitized farm data from sources like milking parlour, herd management systems, and feed laboratory analyses (Masoero et al. 2007;Kaloxylos et al. 2012). Using SDN in combination with the economic IOFC concept, both the economic and ecological sustainability of dairy farming can be evaluated simultaneously. ...
To satisfy increasing food and nutrient supply requirements for our growing future human population, farmers and staple food producers carry vital responsibilities. Especially farmers with ruminant livestock like dairy cows transform otherwise for human consumption unsuitable fibre into highly nutritious milk and meat. Nevertheless, dairy farmers are challenged increasingly by the consequences of global warming. Economic risks like feed supply and volatile commodity prices need to be balanced, also taking into account the increasing environmental awareness of end-customers. Focusing just on emissions, dairy production is contributing an essential part of the total carbon footprint emitted by the agricultural sector. Since rumen degradability of feed was identified by the Food and Agriculture Organization of the United Nations as one of the most influential parameters in reducing the carbon footprint of dairy farming, the desire to exploit leverage potential for efficiency increases can be considered exceptionally high. Although the positive effects of improved feed, in other words, neutral detergent fibre rumen degradability for
... The Near Infrared Reflectance Spectroscopy (NIRS) technique has been used extensively as a rapid and eco-friendly analysis system for the quality evaluation of agricultural products and forage crops (Cozzolino and Moron, 2004;Locher et al., 2005;Masoero et al., 2007;Montes et al., 2009) and for the prediction of animal intake and digestibility from the spectra of forage samples (Decruyenaere et al., 2009;Asekova et al., 2016). Even though NIRS fiber optics instruments have reached a satisfactory degree of portability, very few researchers have used NIRS as a tomoscopy instrument to predict in vitro digestibility and the crop maturity index of different forages (Tassone et al., 2014) or to determine other parameters in agricultural products (Masoero et al., 2018a(Masoero et al., , 2018b. ...
The aim of this study has been to investigate the efficiency of NIR scanning to detect differences related to the chemical composition, gross energy, in vitro apparent digestibility (DMD) and relative feed value (RFV) of leaves and green pruning residues (GPRs) of eleven red grapevine cultivars (Barbera, Cabernet Sauvignon, Cabernet Franc, Canaiolo Nero, Carignan Noir, Grenache, Lambrusco Salamino, Nebbiolo, Pinot Noir, Sangiovese and Syrah) and five white grapevine cultivars (Malvasia Bianca, Moscato Bianco, Sauvignon Blanc, Verdicchio and Vernaccia). Vibrational analyses were performed on lyophilized samples in reflectance mode using an NIR-SCÏO TM molecular sensor, that is, a miniaturized web-based device that operates over the 740-1070 nm NIR range. The present study demonstrates that the RFV of the considered grape leaves is 22.5% higher than that of the grape GPRs. This feed value may be predicted by means of NIR spectroscopy of the lyophilized samples; however, such information could also easily be approximated through a rapid NIR tomoscopy of adequate samples of intact leaves. Foliar moisture could be predicted by means of NIR tomoscopy of intact leaves, after the grape dataset has been enlarged appropriately. A concerted elaboration of the chemical and digestibility analyses leads to a significant compositional fingerprint of the sixteen cultivars studied here. NIR tomoscopy can be used to rapidly classify the phenotypes, since other P.G. Peiretti, G. Masoero and S. Tassone 2 physico-chemical information that is not revealed by means of the usual analyses are incorporated in the electromagnetic spectrum. Other key biological properties (polyphenols, antioxidants, stress reaction, etc.) that are prospected for precision agriculture purposes could be revealed by a rapid NIR scan and perhaps even through remote NIR sensing.
... The Near Infrared Reflectance Spectroscopy (NIRS) technique has been used extensively as a rapid and eco-friendly analysis system for the quality evaluation of agricultural products and forage crops (Cozzolino and Moron, 2004;Locher et al., 2005;Masoero et al., 2007;Montes et al., ...
Biogeography is the study of the distribution of species over space and time and aims to
understand where, why, and at what abundance organisms live. Revealing the diversity and
distribution pattern of populations and communities at multiple spatial scales is thus a central issue in ecology. Recent biogeographic studies based on genetic technologies revealed that microorganisms are not randomly distributed over space and time, showing that their distribution is systematically heterogeneous and structured, revealing specific patterns of microbial distribution. In this context, the study of microbial communities associated with vineyards points to the existence of patterns of microbial distribution across viticultural areas, suggesting a microbiological component of the terroir concept. In the light of this knowledge, the composition of the yeast flora present on grapes, besides representing a long-term known factor of wine quality tends to be presently seen as a potential factor of wine typicality. To assess grape yeast diversity and to understand the ecological and geographical factors shaping the yeast communities and populations composition is of great importance for modern oenology. In this chapter we present
on overview of the research developed in this scope.
... An EN was applied to silage analysis by Masoero et al. [38]. Researchers compared the use of near-infrared spectroscopy (NIR) and an EN including 10 metal oxide semiconductors (MOSs) to evaluate dry matter, pH, buffering capacity, and total nitrogen, soluble nitrogen, ammonia, alcohols, lactic acid, and volatile fatty acid content in fresh farm silages. ...
... Furthermore, routine silage analyses using VOCs as fermentation quality markers are considered quite expensive and are usually time-consuming and incompatible with farming needs, particularly with respect to the speed of mass front removal. Masoero et al. [38] used an EN as a simple alternative method for evaluating gaseous components. The portability of EN, combined with its lack of a requirement for sample pre-treatment, speed, and low operating cost, represents substantial in-field advantages. ...
Electronic Olfaction Systems (EOSs) based on a variety of gas-sensing technologies have been developed to simulate in a simplified manner animal olfactory sensing systems. EOSs have been successfully applied to many applications and fields, including food technology and agriculture. Less information is available for EOS applications in the feed technology and animal nutrition sectors. Volatile Organic Compounds (VOCs), which are derived from both forages and concentrate ingredients of farm animal rations, are considered and described in this review as olfactory markers for feedstock quality and safety evaluation. EOS applications to detect VOCs from feedstuffs (as analytical matrices) are described, and some future scenarios are hypothesised. Furthermore, some EOS applications in animal feeding behaviour and organoleptic feed assessment are also described.
... wheat with aflatoxins and DON, respectively (Campagnoli et al., 2009a,b; Cheli et al., 2009b; Tognon et al., 2005). A fast and straightforward analytical protocol was applied to the DON identification in naturally contaminated wheat samples based on E.U. limits (1750 g/kg) in unprocessed durum wheat for human consumption (Campagnoli et al., 2011). Masoero et al. (2007) compared NIR and a 10 Metal Oxide Semiconductors (MOSs) EN to evaluate dry matter, pH, buffering capacity, total N, soluble N, ammonia, alcohols, lactic acid and volatiles fatty acids in fresh farm silages. NIR provided better results than EN for pH prediction, while EN was better in estimation of total fatty acids levels, buffering cap ...
Silage making increased considerably from the 1960s and is the predominant method of forage preservation in temperate areas of the world. Silage is widely used in farms and has a substantial role in animal production systems. Currently, silage quality is evaluated by chemico-fermentative parameters. However, the presence of bacteria, moulds, and/or some of their metabolites, i.e., mycotoxins, must be considered because of their effects on animal production and health. The knowledge of mycotoxin occurrence in animal feed was concentrated primarily on commodities, such as grains and cereals. However, the contribution of silages to total mycotoxin intake could be significant and sometimes greater than that of compound feed in ruminant diet, as forages are the main dry matter component. The silage process is mainly under the control of the farmer. Therefore, large differences in preservation quality can be found, and different fungi found in forage may lead to a varied spectrum of toxins. The evidence regarding fungi and mycotoxins occurring in different silages from different geographical areas, and the fate of fungi and mycotoxins during ensiling, confirm the need to monitor the quality of silage that is fed to animals. Economical and straightforward silage testing is critical to reach a quick and sufficiently accurate diagnosis of silage quality, which allows for “in field” decision making with regard to the acceptability of a given forage for its use as animal feed.This review describes several topics of interest regarding fungi and mycotoxin contamination in silages, focusing on their occurrence as well as factors affecting their concentrations and distribution at harvest and during ensiling. The impact on sampling and analysis will also be discussed.
... Near infrared spectroscopy (NIRS) has been used for several years for the commercial testing of feeds; it is a rapid and convenient alternative to traditional chemical methods, which are time consuming, polluting and expensive. Electronic nose is a widespread emerging method that has recently been applied to the experimental analysis of milk and dairy products (Ampuero and Bosset, 2003) but also to the rapid appreciation of silage quality (Masoero et al., 2007 ). The purpose of this study was to evaluate four rapid methods that are suitable to characterize local milk products, in comparison , as a minimum, to the usual MIR-based analyses concerning milk Gross Composition and as a maximum to the Fatty Acids composition. ...
... The WinISI II software (Infrasoft International, Port Matilda, PA, USA) was chosen to perform the chemometrics, using a cross-validation system to assess the optimal number of latent, and allowing one passage for the elimination of any outliers (t>2; H>10). The olfactometric measurements of the ten MOS sensors registered for 30 sec were elaborated as contiguous arrays, in a set of 300 digits (Masoero et al. 2007). Six discriminant contrasts (Fearn, 1997) were directly fitted between the herd-breeds couples. ...
Four rapid methods, which are complementary to the usual MIR-based analyses, were compared in order to characterize local milk products. A set of 278 fresh samples from four separately reared Jersey, Piemontese and Valdostana cattle and Saanen goat herds was analyzed by: Fluorescence Spectroscopy, Electronic Nose, UV-Vis- NIRS and FT-NIRS (total 5851 digits by record). The Gross Composition and Fatty Acid composition were determined at the same time. Chemometric analysis of the digital measurements and of the milk composition was performed by discriminant PLS regression over the four herds. The average R2 cross-validated values of the six discriminant contrasts were lower for the Gross Composition (0.47), very high for the FT-NIRS scans (0.97), for the Fatty Acids (0.96), and also high for the Fluorescence (0.90) and the UV-Vis-NIRS evaluation (0.89), while the Electronic Nose gave lower distinction between the groups (0.64). The patterns based on the distance matrix showed a remarkable complementarity between the Gross Composition evaluation and the rapid methods, which were close to the Fatty Acids evaluation. The FT-NIRS and Fluorescence analyses converged together, clustering the Jersey & Piemontese, the Valdostana and then the Goat milk. The Jersey-Piemontese cluster was also confirmed by EN. The UV-Vis-NIRS appraisal, distinguished the Piemontese milk more clearly, while it paired the Jersey and Valdostana milk. These rapid methods could be of great interest in the milk research.
