CalviniRFocaGUlriciA.Chemometrics, imaging and spectroscopy laboratory – Department of Life Sciences, University of Modena and Reggio Emilia. NIR News2021;
32: 27–30.
2.
MalegoriCMustorgiE.Analytical chemistry and chemometrics group, Department of Pharmacy, University of Genova: an update.NIR news2020;
31: 30–33.
3.
MariniF.Analytical chemistry and chemometrics group, Department of Chemistry – University of Rome “La Sapienza.”NIR News2020;
31: 20–22.
4.
MasoeroGXiccatoGDalle ZotteA, et al.Analisi della carne di coniglio mediante Spettroscopia NIR. Zoot Nutr Anim1994;
20: 319–329.
5.
ServaLMarchesiniGChinelloM, et al.Use of near-infrared spectroscopy and multivariate approach for estimating silage fermentation quality from freshly harvested maize. Ital J Anim Sci2021;
20: 859–871.
6.
ServaLAndrighettoIMarchesiniG, et al.Prognostic capacity assessment of a multiparameter risk score for aerobic stability of maize silage undergoing heterofermentative inoculation (Lactobacillus buchneri) in variable ensiling conditions. Animal Feed Sci Technol2021;
281: 115116.
7.
MarchesiniGServaLChinelloM, et al.Effect of maturity stage at harvest on the ensilability of maize hybrids in the early and late FAO classes, grown in areas differing in yield potential. Grass Forage Sci2019;
74: 415–426.
8.
AndrighettoIServaLGazzieroM, et al.Proposal and validation of new indexes to evaluate maize silage fermentative quality in lab-scale ensiling conditions through the use of a receiver operating characteristic analysis. Anim Feed Sci Technol2018;
242: 31–40.
9.
MarchesiniGServaLGarbinE, et al.Near-infrared calibration transfer for undried whole maize plant between laboratory and on-site spectrometers. Ital J Anim Sci2017;
17: 66–72.
10.
BerzaghiPServaLPiombinoM, et al.Prediction performances of portable near infrared instruments for at farm forage analysis. Ital J Anim Sci2005;
4: 145–147.
11.
EvangelistaCBasiricòLBernabucciU.An overview on the use of near infrared spectroscopy (NIRS) on farms for the management of dairy cows. Agriculture2021;
11: 296.
12.
ServaLMarchesiniGGarbinE, et al. Uso di uno strumento NIR portatile per la valutazione dell’omogeneità dell’unifeed distribuito in mangiatoia. In: Proceedings of the 7 Simposio Italiano Di Spettroscopia NIR. Lodi: SISNIR, 2016, pp.138–142.
13.
ServaLBisonGMarchesiniG, et al. Use of a portable NIR instrument as a rapid tool for cattle feeding control. In: Book of Abstract, ASPA 24th Congress, Padova, 21–24 September 2021.
14.
BerzaghiPDalle ZotteAJanssonLM, et al.Near-infrared reflectance spectroscopy (NIRS) as a mean to predict chemical composition of breast meat and discriminating between different n-3 PUFA feeding sources. Poultry Sci2005;
84: 128–136.
15.
BoschettiLOttavianMFaccoP, et al.A correlative study on data from pork carcass and processed meat (Bauernspeck) for automatic estimation of chemical parameters by means of near-infrared spectroscopy. Meat Sci2013;
95: 621–628.
16.
ConcollatoADalle ZotteAServaL, et al. Impiego della Spettroscopia nel vicino infrarosso (NIRS) per predire la qualità del filetto di 5 ceppi genetici di trota iridea (Oncorhynchus mykiss) allevati in 3 diversi allevamenti del Trentino Alto Adige. In: Proc. 5° Simposio Italiano di Spettroscopia NIR, Agripolis, Legnaro, Padova, Italy, 26–28 settembre 2012.
17.
Dalle ZotteABerzaghiPJanssonLM, et al.The use of near-infrared reflectance spectroscopy (NIRS) in the prediction of chemical composition of freeze-dried egg yolk and discrimination between different n-3 PUFA feeding sources. Animal Feed Sci Technol2006;
128: 108–121.
18.
Dalle ZotteAMasoeroGSalaG, et al. Effects of housing system on the meat quality of fattening rabbits by NIRS using ethanol or freeze-dried specimens. In: Proc. 53rd ICOMST, Beijing, China, 5–10 August 2007. Beijing: Guanghong Zhou & Weili Zhang (China), pp.339–340.
19.
Dalle ZotteAPaciGMirisolaM, et al. Impiego della spettroscopia NIR per la stima della composizione chimica ed acidica della carne di coniglio e per discriminare l’allevamento outdoor da quello indoor. In: Proc. 3° Simposio Italiano di Spettroscopia NIR, Lazise, Verona, Italy, 22–23 maggio 2008.
20.
Dalle ZotteABerzaghiPMirisolaM, et al. Applicazione della spettroscopia NIR per la stima della composizione chimica ed acidica di tuorli d'uovo liofilizzati e per discriminare l'inclusione alimentare di Portulaca oleracea. In: Proc. 3° Simposio Italiano di Spettroscopia NIR, Lazise, Verona, Italy, 22–23 maggio 2008.
21.
Dalle ZotteAOttavianMConcollatoA, et al.Authentication of raw and cooked freeze-dried rainbow trout (Oncorhynchus mykiss) by means of near infrared spectroscopy and data fusion. Food Res Int2014;
60: 180–188.
22.
MoletteCBerzaghiPDalle ZotteA, et al.The use of near infrared reflectance spectroscopy in the prediction of the chemical composition of geese fatty liver.Poultry Sci2001;
80: 1625–1629.
23.
RiovantoRMirisolaMMaticsZS, et al.Near infrared spectroscopy (NIRS) as a tool to predict meat chemical composition and fatty acid profile in different rabbit genotypes. Ital J Animal Sci2009;
8: 799–801.
24.
TasonieroGCullereMServaL, et al. Use of Near Infrared Spectroscopy (NIRS) to discriminate meat cuts from rabbits divergently selected for total body fat content. In: Proc. 29th Hungarian conference on rabbit production, H-7400 Kaposvár, Guba Sándor u. 40, Hungary, 31 May 2017. pp.59–64.
25.
BisuttiVMerlantiRServaL, et al.Multivariate and machine learning approaches for honey botanical origin authentication using near infrared spectroscopy. J Near Infrared Spectrosc2019;
27: 65–74.
26.
De Jesus InacioLLanzaIMerlantiR, et al.Discriminant analysis of pyrrolizidine alkaloid contamination in bee pollen based on near-infrared data from lab-stationary and portable spectrometers. Eur Food Res. Technol2020;
246: 2471–2483.
27.
SegatoSMerlantiRBisuttiV, et al.Multivariate and machine learning models to assess the heat effects on honey physicochemical, colour and NIR data. Eur Food Res Technol2019;
245: 2269–2278.
28.
CozziGFerlitoJPasiniG, et al.Application of near-infrared spectroscopy as an alternative to chemical and color analysis to discriminate the production chains of Asiago d'Allevo cheese.J Agric Food Chem2009;
57: 11449–11454.
29.
LanzaIServaLContieroB, et al. Applicazione della spettroscopia NIR per la stima di varietà di Asiago DOP, NIR Italia online, 24–25 February 2021.
30.
VarràMOFasolatoLServaL, et al.Use of near infrared spectroscopy coupled with chemometrics for fast detection of irradiated dry fermented sausages. Food Control2020;
110: 107009.
31.
FasolatoLBalzanSRiovantoR, et al.Comparison of visible and near-infrared reflectance spectroscopy to authenticate fresh and frozen-thawed swordfish (Xiphias gladius L). J Aquat Food Prod Technol2012;
21: 493–507.
32.
OttavianMFasolatoLServaL, et al.Data fusion for food authentication: fresh/frozen-thawed discrimination in West African Goatfish (Pseudupeneus prayensis) fillets. Food Bioprocess Technol2014;
7: 1025–1036.
33.
SanniaMServaLBalzanS, et al.Application of near-infrared spectroscopy for frozen-thawed characterization of cuttlefish (Sepia officinalis).J Food Sci Technol2019;
56: 4437–4447.
34.
CurròSBalzanSServaL, et al.Fast and green method to control frauds of geographical origin in traded cuttlefish using a portable infrared reflective instrument. Foods2021;
10: 1678.
35.
FasolatoLAndreaniNADe NardiR, et al.Spectrophotometric techniques for the characterization of strains involved in the blue pigmentation of food: preliminary results. Ital J Food Saf2018;
7: 34–39.
36.
ServaLBalzanSBisuttiV, et al.Use of near infrared spectroscopy and chemometrics to evaluate the shelf-life of cloudy sonicated apple juice. J Near Infrared Spectrosc2019;
27: 75–85.
37.
LanzaIConficoniDBalzanS, et al.Assessment of chicken breast shelf life based on bench-top and portable near-infrared spectroscopy tools coupled with chemometrics. Food Qual Saf2021;
5: fyaa032.