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Improper sample preparation negatively affects near infrared reflectance spectroscopy (NIRS) nutrient analysis of ground corn. Anim Feed Sci Technol 2022. [DOI: 10.1016/j.anifeedsci.2022.115472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Pérez-Marín D, de la Roza-Delgado B, Entrenas JA, Garrido-Cuevas M, Garrido-Varo A. Transferring a large data library of fresh total mixed rations from a benchtop to 2 portable near-infrared spectrometers for on-farm real-time decisions. J Dairy Sci 2022; 105:2380-2392. [PMID: 35033340 DOI: 10.3168/jds.2021-21032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 11/22/2021] [Indexed: 11/19/2022]
Abstract
This study was carried out using a spectral database consisting of 394 samples of fresh total mixed ration (TMR) from dairy farms located at Northern Spain. Cloning sets of different size and structure were evaluated for the transfer of the large TMR spectral database obtained on a Foss NIRSystems monochromator to 2 different portable near-infrared devices: one diode array instrument and another based on linear variable filters. The cloning matrix that produced the best matching between instruments was then used to transfer the TMR spectral library to the 2 portable instruments. Once the database had been transferred, calibration equations were developed to compare the predictive ability of the equations obtained in the benchtop and portable instruments. In comparison with the monochromator predictive ability, the calibration equations developed with the near-infrared portable instruments displayed a high and similar accuracy for most of the studied parameters related to TMR composition, enabling their use for predicting TMR quality at the farm level.
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Affiliation(s)
- Dolores Pérez-Marín
- Faculty of Agriculture and Forestry Engineering (ETSIAM), Universidad de Cordoba, Campus de Rabanales, Carretera de Madrid km. 396, 14071 Cordoba, Spain
| | - Begoña de la Roza-Delgado
- Nutrition Research Programme, Regional Institute for Research and Agri-Food Development (SERIDA), PO Box 13, 33300 Villaviciosa, Spain
| | - J Antonio Entrenas
- Faculty of Agriculture and Forestry Engineering (ETSIAM), Universidad de Cordoba, Campus de Rabanales, Carretera de Madrid km. 396, 14071 Cordoba, Spain.
| | - Mar Garrido-Cuevas
- Faculty of Agriculture and Forestry Engineering (ETSIAM), Universidad de Cordoba, Campus de Rabanales, Carretera de Madrid km. 396, 14071 Cordoba, Spain
| | - Ana Garrido-Varo
- Faculty of Agriculture and Forestry Engineering (ETSIAM), Universidad de Cordoba, Campus de Rabanales, Carretera de Madrid km. 396, 14071 Cordoba, Spain
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Zaefarian F, Cowieson AJ, Pontoppidan K, Abdollahi MR, Ravindran V. Trends in feed evaluation for poultry with emphasis on in vitro techniques. ACTA ACUST UNITED AC 2021; 7:268-281. [PMID: 34258415 PMCID: PMC8245842 DOI: 10.1016/j.aninu.2020.08.006] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 07/29/2020] [Accepted: 08/02/2020] [Indexed: 01/10/2023]
Abstract
Accurate knowledge of the actual nutritional value of individual feed ingredients and complete diets is critical for efficient and sustainable animal production. For this reason, feed evaluation has always been in the forefront of nutritional research. Feed evaluation for poultry involves several approaches that include chemical analysis, table values, prediction equations, near-infrared reflectance spectroscopy, in vivo data and in vitro digestion techniques. Among these, the use of animals (in vivo) is the most valuable to gain information on nutrient utilization and is more predictive of bird performance. However, in vivo methods are expensive, laborious and time-consuming. It is therefore important to establish in vitro methods that are reliable, rapid and practical to assess the nutritional quality of feed ingredients or complete diets. Accuracy of the technique is crucial, as poor prediction will have a negative impact on bird performance and, increase feed cost and environmental issues. In this review, the relevance and importance of feed evaluation in poultry nutrition will be highlighted and the various approaches to evaluate the feed value of feed ingredients or complete diets will be discussed. Trends in and practical limitations encountered in feed evaluation science, with emphasis on in vitro digestion techniques, will be discussed.
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Affiliation(s)
- Faegheh Zaefarian
- Monogastric Research Centre, School of Agriculture and Environment, Massey University, Palmerston North 4442, New Zealand
- Corresponding author.
| | | | | | - M. Reza Abdollahi
- Monogastric Research Centre, School of Agriculture and Environment, Massey University, Palmerston North 4442, New Zealand
| | - Velmurugu Ravindran
- Monogastric Research Centre, School of Agriculture and Environment, Massey University, Palmerston North 4442, New Zealand
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Dangal SRS, Sanderman J. Is Standardization Necessary for Sharing of a Large Mid-Infrared Soil Spectral Library? SENSORS 2020; 20:s20236729. [PMID: 33255566 PMCID: PMC7728050 DOI: 10.3390/s20236729] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Revised: 11/19/2020] [Accepted: 11/21/2020] [Indexed: 11/16/2022]
Abstract
Recent developments in diffuse reflectance soil spectroscopy have increasingly focused on building and using large soil spectral libraries with the purpose of supporting many activities relevant to monitoring, mapping and managing soil resources. A potential limitation of using a mid-infrared (MIR) spectral library developed by another laboratory is the need to account for inherent differences in the signal strength at each wavelength associated with different instrumental and environmental conditions. Here we apply predictive models built using the USDA National Soil Survey Center-Kellogg Soil Survey Laboratory (NSSC-KSSL) MIR spectral library (n = 56,155) to samples sets of European and US origin scanned on a secondary spectrometer to assess the need for calibration transfer using a piecewise direct standardization (PDS) approach in transforming spectra before predicting carbon cycle relevant soil properties (bulk density, CaCO3, organic carbon, clay and pH). The European soil samples were from the land use/cover area frame statistical survey (LUCAS) database available through the European Soil Data Center (ESDAC), while the US soil samples were from the National Ecological Observatory Network (NEON). Additionally, the performance of the predictive models on PDS transfer spectra was tested against the direct calibration models built using samples scanned on the secondary spectrometer. On independent test sets of European and US origin, PDS improved predictions for most but not all soil properties with memory based learning (MBL) models generally outperforming partial least squares regression and Cubist models. Our study suggests that while good-to-excellent results can be obtained without calibration transfer, for most of the cases presented in this study, PDS was necessary for unbiased predictions. The MBL models also outperformed the direct calibration models for most of the soil properties. For laboratories building new spectroscopy capacity utilizing existing spectral libraries, it appears necessary to develop calibration transfer using PDS or other calibration transfer techniques to obtain the least biased and most precise predictions of different soil properties.
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Evaluation of diesel exhaust fluid (DEF) using near-infrared spectroscopy and multivariate calibration. Microchem J 2019. [DOI: 10.1016/j.microc.2019.104155] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Yang J, Lou X, Yang H, Yang H, Liu C, Wu J, Bin J. Improved calibration transfer between near-Infrared (NIR) spectrometers using canonical correlation analysis. ANAL LETT 2019. [DOI: 10.1080/00032719.2019.1604725] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Affiliation(s)
- Junxing Yang
- College of Agriculture, Hunan Agricultural University, Changsha, China
| | - Xiaoping Lou
- China Tobacco Zhejiang Industry Co., Ltd, Hangzhou, China
| | - Hongqi Yang
- College of Agriculture, Hunan Agricultural University, Changsha, China
| | - Huibing Yang
- College of Agriculture, Hunan Agricultural University, Changsha, China
| | - Chaoying Liu
- China Tobacco Zhejiang Industry Co., Ltd, Hangzhou, China
| | - Jingjing Wu
- China Tobacco Zhejiang Industry Co., Ltd, Hangzhou, China
| | - Jun Bin
- College of Agriculture, Hunan Agricultural University, Changsha, China
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Li J, Yu XN, Ge WZ, An D. Qualitative Analysis of Maize Haploid Kernels Based on Calibration Transfer by Near-Infrared Spectroscopy. ANAL LETT 2018. [DOI: 10.1080/00032719.2018.1459656] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
Affiliation(s)
- Jia Li
- College of Information and Electrical Engineering, China Agricultural University, Beijing, China
| | - Xiao-Ning Yu
- College of Information and Electrical Engineering, China Agricultural University, Beijing, China
| | - Wen-Zhang Ge
- College of Information and Electrical Engineering, China Agricultural University, Beijing, China
| | - Dong An
- College of Information and Electrical Engineering, China Agricultural University, Beijing, China
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da Silva NC, Cavalcanti CJ, Honorato FA, Amigo JM, Pimentel MF. Standardization from a benchtop to a handheld NIR spectrometer using mathematically mixed NIR spectra to determine fuel quality parameters. Anal Chim Acta 2017; 954:32-42. [DOI: 10.1016/j.aca.2016.12.018] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2016] [Revised: 11/24/2016] [Accepted: 12/05/2016] [Indexed: 11/13/2022]
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Berzaghi P, Riovanto R. Near infrared spectroscopy in animal science production: principles and applications. ITALIAN JOURNAL OF ANIMAL SCIENCE 2016. [DOI: 10.4081/ijas.2009.s3.39] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Affiliation(s)
- Paolo Berzaghi
- Dipartimento di Scienze AnimaliUniversità di Padova, Italy
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Origin authentication of distillers' dried grains and solubles (DDGS)--application and comparison of different analytical strategies. Anal Bioanal Chem 2015; 407:6447-61. [PMID: 26123435 DOI: 10.1007/s00216-015-8807-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2015] [Revised: 05/22/2015] [Accepted: 05/26/2015] [Indexed: 10/23/2022]
Abstract
In the context of products from certain regions or countries being banned because of an identified or non-identified hazard, proof of geographical origin is essential with regard to feed and food safety issues. Usually, the product labeling of an affected feed lot shows origin, and the paper documentation shows traceability. Incorrect product labeling is common in embargo situations, however, and alternative analytical strategies for controlling feed authenticity are therefore needed. In this study, distillers' dried grains and solubles (DDGS) were chosen as the product on which to base a comparison of analytical strategies aimed at identifying the most appropriate one. Various analytical techniques were investigated for their ability to authenticate DDGS, including spectroscopic and spectrometric techniques combined with multivariate data analysis, as well as proven techniques for authenticating food, such as DNA analysis and stable isotope ratio analysis. An external validation procedure (called the system challenge) was used to analyze sample sets blind and to compare analytical techniques. All the techniques were adapted so as to be applicable to the DDGS matrix. They produced positive results in determining the botanical origin of DDGS (corn vs. wheat), and several of them were able to determine the geographical origin of the DDGS in the sample set. The maintenance and extension of the databanks generated in this study through the analysis of new authentic samples from a single location are essential in order to monitor developments and processing that could affect authentication.
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Soldado A, Fearn T, Martínez-Fernández A, de la Roza-Delgado B. The transfer of NIR calibrations for undried grass silage from the laboratory to on-site instruments: Comparison of two approaches. Talanta 2013; 105:8-14. [DOI: 10.1016/j.talanta.2012.11.028] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2012] [Revised: 11/06/2012] [Accepted: 11/11/2012] [Indexed: 11/25/2022]
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Development of a Quantitative Visualization Technique for Gluten in Dough Using Fluorescence Fingerprint Imaging. FOOD BIOPROCESS TECH 2012. [DOI: 10.1007/s11947-012-0982-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Zamora-Rojas E, Garrido-Varo A, De Pedro-Sanz E, Guerrero-Ginel JE, Pérez-Marín D. Monitoring NIRS calibrations for use in routine meat analysis as part of Iberian pig-breeding programs. Food Chem 2011. [DOI: 10.1016/j.foodchem.2011.05.139] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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