Handheld NIRS sensors for routine compound feed quality control: Real time analysis and field monitoring.

Significant advances achieved in different sensor technologies and computer processing data have made possible to respond the needs of livestock sector, providing precise and rapid information on feed composition, being an alternative to real time quality control on compound feed the use of handheld NIRS sensors. This work aimed to evaluate two hand-held portable NIR spectrophotometers for on-site and real time analysis of nutritive parameters in raw compound feed: Phazir 1624 Polychromix Inc (PhIR) and MicroNIRTM 1700 by JDSU (MICRO). For computing data, different combinations of pre-treatments and multivariate statistical methods have been assayed to extract the valuable information of spectra data and to develop appropriate calibrations. The calibration models displayed greatest predictive capacity for Crude Protein (CP), Crude Fiber (CF) and Starch (STCH) and the determination coefficients of cross validation were 0.90-0.88 for CP, 0.85-0.91 for CF, 0.89-0.88 and 0.89-0.91 for STCH using PhIR and MICRO instruments respectively. Dry Matter showed the lowest determination coefficients of cross validation 0.67-0.73. Accuracy achieved 99-101% for both NIRS instruments and no differences were found when applying tstudent-test comparing reference and predicted data. Results obtained with both instruments were compared by using standard deviation and not significant differences were observed at the 5% level. Results so far have demonstrated the potential of these handheld NIRS instruments proposed here to estimate the individual compound feeds composition changes at farms level instantly, time avoiding the disadvantage of moving the samples to the lab.

[1]  Dolores Pérez-Marín,et al.  Miniature handheld NIR sensor for the on-site non-destructive assessment of post-harvest quality and refrigerated storage behavior in plums , 2010 .

[2]  Heinz W. Siesler,et al.  Miniature near-infrared (NIR) spectrometer engine for handheld applications , 2012, Defense, Security, and Sensing.

[3]  Wolfgang Lehner,et al.  Data modeling for Precision Dairy Farming within the competitive field of operational and analytical tasks , 2007 .

[4]  Ana Soldado,et al.  On-Site NIR Spectroscopy to Control the Shelf Life of Pork Meat , 2011 .

[5]  Dolores Pérez-Marín,et al.  Handheld NIRS analysis for routine meat quality control: Database transfer from at-line instruments , 2012 .

[6]  Ana Soldado,et al.  Assessing the Value of a Portable Near Infrared Spectroscopy Sensor for Predicting Pork Meat Quality Traits of “Asturcelta Autochthonous Swine Breed” , 2013, Food Analytical Methods.

[7]  J. Shenk,et al.  Application of NIR Spectroscopy to Agricultural Products , 1992 .

[8]  L. E. Chase Precision Feed Management – What Have We Learned? , 2018 .

[9]  Vincent Baeten,et al.  Calibration Transfer from Dispersive Instruments to Handheld Spectrometers , 2010, Applied spectroscopy.

[10]  R. Barnes,et al.  Standard Normal Variate Transformation and De-Trending of Near-Infrared Diffuse Reflectance Spectra , 1989 .

[11]  J. Rodgers,et al.  Cotton Micronaire Measurements Using Small Portable Near-Infrared (NIR) Analyzers , 2016, Applied spectroscopy.

[12]  Tom Fearn,et al.  Comparing Standard Deviations , 1996 .

[13]  D. Cavalli,et al.  Evaluation of four NIR spectrometers in the analysis of cattle slurry , 2015 .

[14]  Jerome J. Workman,et al.  Application of NIR spectroscopy to agricultural products. In 'Handbook of Near-infrared Analysis'.(E , 1992 .

[15]  A. Garrido-Varo,et al.  On-Site Quality Control of Processed Land Animal Proteins Using a Portable Micro-Electro-Mechanical-Systems near Infrared Spectrometer , 2016 .

[16]  Elaine Duterte Delvo-Favre,et al.  Implementation of Near-Infrared Technology (AccuVein AV-400®) to Facilitate Successful PIV Cannulation , 2017 .

[17]  T. Fearn,et al.  Near infrared spectroscopy in food analysis , 1986 .