Comparison of the predictive ability of NIR calibration models developed to predict nutritional parameters in total mixed rations by using reference data expressed “as dry matter” or “as is basis”

2021 ◽  
Author(s):  
Dolores C. Pérez-Marín ◽  
Begoña De la Roza ◽  
José A. Entrenas ◽  
María del Mar Garrido-Cuevas ◽  
Ana Garrido
Keyword(s):  
Dry Matter ◽  
Reference Data ◽  
Predictive Ability ◽  
Nutritional Parameters ◽  
Calibration Models

Determination of Dry Matter Content and Basic Density of Norway Spruce by near Infrared Reflectance and Transmittance Spectroscopy

1994 ◽  
Vol 2 (3) ◽  
pp. 127-135 ◽  
Author(s):  
Lisbeth G. Thygesen
Keyword(s):  
Norway Spruce ◽  
Relative Error ◽  
Dry Matter ◽  
Near Infrared ◽  
Basic Density ◽  
Predictive Ability ◽  
Matter Content ◽  
Dry Matter Content ◽  
Calibration Models

The purpose of the study was to investigate the feasibility of using near infrared (NTR) spectroscopy in reflectance and transmittance modes for the determination of dry matter content and basic density of Norway spruce ( Picea abies (L.) Karst). The 169 samples varied in moisture content (below fibre saturation, green and fully saturated) and in form (solid wood and shavings). Calibration models were produced using partial least squares regression and the resulting models were validated using test sets. The calibration models for dry matter content showed good predictive ability. The root mean square error of prediction (RMSEP) was 1–2% for dry matter contents ranging between 35 and 95%, corresponding to a relative error between 1 and 6%. Calibration models for basic density were less precise, having RMSEP values between 15 and 26 kg m−3 for basic density values ranging from 313 to 495 kg m−3 (relative error 3–8%). The reason for the limited predictive ability of the basic density models is probably that the part of each sample scanned with NIR spectroscopy was not representative of the whole sample of which the basic density had been determined by the reference method. No marked differences in the predictive ability of calibration models were found between reflectance and transmittance.

scholarly journals Rapid Determination of Aesculin, Aesculetin and Fraxetin inCortex FraxiniExtract Solutions Based on Ultraviolet Spectroscopy

2011 ◽  
Vol 8 (s1) ◽  
pp. S225-S236 ◽  
Author(s):  
Ming Yang ◽  
Jia-Lei Chen ◽  
Xiu-Feng Shi ◽  
Hui-Jue Niu
Keyword(s):  
Root Mean Square Error ◽  
Reference Data ◽  
Rapid Determination ◽  
Ultraviolet Spectroscopy ◽  
Mean Square ◽  
Chemical Parameters ◽  
Ultraviolet Spectra ◽  
Calibration Models ◽  
The Relationship

To evaluate the application of ultraviolet spectroscopy for the rapid determination of aesculin, aesculetin and fraxetin inCortex fraxiniextract solutions, ultraviolet spectra ofCortex fraxiniextract solutions from different batches were collected in the spectral range from 200 nm to 400 nm. The relationship between ultraviolet spectra and chemical parameters displayed some non-linear characteristics. Thus, K-OPLS was proposed to establish the calibration models for the determination ofCortex fraxiniextract solutions between the reference data and ultraviolet spectra. The calibration results were achieved for the determination ofCortex fraxiniextract solutions. The coefficients of determination in calibration (R2) for aesculin, aesculetin and fraxetin were 0.989, 0.957 and 0.939, while in prediction (R2) were 0.982, 0.979 and 0.962, respectively. And the root-mean-square error of prediction (RMSEP) for aesculin, aesculet and fraxetin were 11.99, 3.02 and 1.59 μg/mL. The results demonstrated that ultraviolet spectroscopy could be used for the rapid determination of these three components inCortex fraxiniextract solutions.

scholarly journals Rapid Determination of Nutritional Parameters of Pasta/Sauce Blends by Handheld Near-Infrared Spectroscopy

Molecules ◽  
2019 ◽  
Vol 24 (11) ◽  
pp. 2029 ◽  
Author(s):  
Marina D. G. Neves ◽  
Ronei J. Poppi ◽  
Heinz W. Siesler
Keyword(s):  
Near Infrared ◽  
Rapid Determination ◽  
Analytical Data ◽  
Nir Spectroscopy ◽  
Nutritional Parameters ◽  
Direct To Consumer ◽  
Calibration Models ◽  
Food And Beverage ◽  
The Individual ◽  
Near Future

Nowadays, near infrared (NIR) spectroscopy has experienced a rapid progress in miniaturization (instruments < 100 g are presently available), and the price for handheld systems has reached the < $500 level for high lot sizes. Thus, the stage is set for NIR spectroscopy to become the technique of choice for food and beverage testing, not only in industry but also as a consumer application. However, contrary to the (in our opinion) exaggerated claims of some direct-to-consumer companies regarding the performance of their “food scanners” with “cloud evaluation of big data”, the present publication will demonstrate realistic analytical data derived from the development of partial least squares (PLS) calibration models for six different nutritional parameters (energy, protein, fat, carbohydrates, sugar, and fiber) based on the NIR spectra of a broad range of different pasta/sauce blends recorded with a handheld instrument. The prediction performance of the PLS calibration models for the individual parameters was double-checked by cross-validation (CV) and test-set validation. The results obtained suggest that in the near future consumers will be able to predict the nutritional parameters of their meals by using handheld NIR spectroscopy under every-day life conditions.

scholarly journals Optimizing setup of scan number in FTIR spectroscopy using the moment distance index and PLS regression: application to soil spectroscopy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Issam Barra ◽  
Lotfi Khiari ◽  
Stephan M. Haefele ◽  
Ruben Sakrabani ◽  
Fassil Kebede
Keyword(s):  
Low Cost ◽  
Predictive Ability ◽  
Exchange Capacity ◽  
General Tendency ◽  
Least Squares Regression ◽  
Minimal Sample ◽  
Predictive Quality ◽  
Calibration Models ◽  
Cross Validation Error ◽  
The Moment

AbstractVibrational spectroscopy such as Fourier-transform infrared (FTIR), has been used successfully for soil diagnosis owing to its low cost, minimal sample preparation, non-destructive nature, and reliable results. This study aimed at optimizing one of the essential settings during the acquisition of FTIR spectra (viz. Scans number) using the standardized moment distance index (SMDI) as a metric that could trap the fine points of the curve and extract optimal spectral fingerprints of the sample. Furthermore, it can be used successfully to assess the spectra resemblance. The study revealed that beyond 50 scans the similarity of the acquisitions has been remarkably improved. Subsequently, the effect of the number of scans on the predictive ability of partial least squares regression models for the estimation of five selected soil properties (i.e., soil pH in water, soil organic carbon, total nitrogen, cation exchange capacity and Olsen phosphorus) was assessed, and the results showed a general tendency in improving the correlation coefficient (R2) as the number of scans increased from 10 to 80. In contrast, the cross-validation error RMSECV decreased with increasing scan number, reflecting an improvement of the predictive quality of the calibration models with an increasing number of scans.

scholarly journals Assessment of cactus (Opuntia ficus-indica L. Mill) accessions for growth, yield and nutritional parameters under pot culture

2019 ◽  
Vol 6 (49) ◽  
Author(s):  
V. K. Kauthale ◽  
K. K. Punde ◽  
S. D. Kodre
Keyword(s):  
Crude Protein ◽  
Dry Matter ◽  
Biomass Yield ◽  
Growth Yield ◽  
Production Performance ◽  
Growth And Yield ◽  
Development Research ◽  
Fresh Weight ◽  
Nutritional Evaluation ◽  
Nutritional Parameters

A pot experiment was conducted at BAIF Development Research Foundation, Urulikanchan, Pune, India during 2014-2016 to study the biomass production performance of four cactus accessions as a source of fodder for livestock. Single matured cladodes of individual accessions were planted in plastic pots during August 2014 and were harvested 18 months after planting. The growth and yield observations were recorded during harvesting and fresh cladodes were analyzed for nutritional parameters in the laboratory. The study revealed that the highest green biomass yield per plant was recorded in accession 1270 (1.74 kg) followed by 1271 (1.45 kg), 1280 (1.39 kg) and the lowest was in accession 1308 (1.36 kg). The maximum fresh weight per cladode was observed in accession 1280 (448.84 g) followed by 1270 (436.75 g), 1271 (394.73 g) and the minimum was in accession 1308 (150.69 g). The more number of cladodes (9.0) were found in accession 1308 followed by 1270 (4.0), 1271 (3.69) and the least (3.10) was in accession 1280. The maximum cladodes area of 333.14 cm2 was recorded in accession 1270 followed by 1280 (310.84 cm2) and the lowest was in accession 1308 (95.61 cm2). The nutritional evaluation of fresh cladodes revealed dry matter in the range of 8.24 to 11.15 %, crude protein 4.00 to 6.03% and crude fiber 7.06 to 8.15%.

scholarly journals Application of FT NIR Spectroscopy in the Determination of Basic Physical and Chemical Properties of Sausages

2010 ◽  
Vol 79 (9) ◽  
pp. S101-S106 ◽  
Author(s):  
Zuzana Procházková ◽  
Michaela Dračková ◽  
Alena Saláková ◽  
Leo Gallas ◽  
Matěj Pospiech ◽  
...  
Keyword(s):  
Water Activity ◽  
Dry Matter ◽  
Muscle Protein ◽  
Chemical Properties ◽  
Dry Matter Content ◽  
Physical And Chemical Properties ◽  
Calibration Models ◽  
Physical And Chemical ◽  
And Chemical Properties

The objectives of this study were to develop calibration models for determination of water activity and the content of fat, dry matter, salt, non collagen muscle protein and pH in dry cooked sausages. Samples (n = 42) were scanned in FT-NIR Analyzer and simultaneously analyzed by standard methods. The spectra were measured in the reflectance mode with a compressive cell between 10 000 and 4 000 cm-1, averaging 100 scans. Calibration models were developed using the partial least squares (PLS) method. These calibration models were checked later by crossvalidation. The following statistical values were obtained: R (correlation coefficient) = 0.997 and SEC (standard error of calibration) = 0.002 for water activity, R = 0.966 and SEC = 0.023 for pH, R = 0.995 and SEC = 0.970 for dry matter content, R = 0.995 and SEC = 0.045 for salt content, R = 0.965 and SEC = 0.652 for non collagen muscle protein, R = 0.996 and SEC = 0.559 for fat content. The results of the study showed that FT-NIR is a suitable method for rapid analysis of physical and chemical properties of sausages.

Assessment of contamination of wool by dark and medullated fibres using near infrared spectroscopy

2006 ◽  
Vol 46 (5) ◽  
pp. 605
Author(s):  
M. R. Fleet ◽  
L. Li ◽  
Y. Ru
Keyword(s):  
Infrared Spectroscopy ◽  
Sample Preparation ◽  
Near Infrared Spectroscopy ◽  
Reference Values ◽  
Near Infrared ◽  
Reference Data ◽  
Wool Fibre ◽  
Reflectance Measurement ◽  
Calibration Models ◽  
Calibration Equations

Increased crossbreeding of Merino sheep in Australia, involving coloured or highly medullated sire breeds, has increased the risk of dark and highly medullated fibres in wool lots. Commercial implementation of the Dark and Medullated Fibre Risk Scheme, based on producer information, is identifying to buyers some of these risks and technology is sought to provide an inexpensive method for routine presale testing of greasy wool lots. One measurement concept assessed the ability of near infrared spectroscopy (NIRS) to predict variation in levels of pigmented fibres or highly medullated fibres in wool. The project used either ‘seeded’ wool samples or naturally contaminated samples with measured reference values as well as different methods of sample preparation of wool fibre (in air or immersed in benzyl alcohol) or the solutions from alkali hydrolysis of wool fibre and NIRS measurement (reflectance v. transmission). NIRS can predict variation in trace levels of pigmented fibre or highly medullated white fibres (kemp) in wool and, among the methods assessed, reflectance analysis of wool fibre in air was generally better than the other options considered. Calibration models for NIRS reflectance measurement of 5 g wool samples ‘seeded’ with 1–50 black-pigmented, tan-pigmented or white kemp fibres gave coefficients of determination (R2) of 0.96, 0.88 and 0.82 with standard errors of cross-validation (SECV) of 4.34, 6.97 and 7.17 fibres per 5 g sample, respectively. However, these calibration equations generally did not predict variations in the reference values for 3 other sets of naturally contaminated samples. New calibration equations determined for each of the sets of naturally contaminated samples also predicted variation in the pigmented fibre reference values, with the extent of agreement depending on the accuracy of the reference data as well as sample preparation and method of measurement. Calibration models for NIRS reflectance measurement of wool fibre from the 3 sets of naturally contaminated samples produced R2 = 0.99, 0.71 and 0.92 with SECV = 0.923, 6.43 and 4.54 pigmented fibres per 5 g sample, respectively. However, these calibrations and those obtained from various combinations of the wool sets also had limited ability to predict variation in pigmented fibre reference values in other independent or excluded samples. Refinement of the technique and development of calibrations with extensive and reliable reference data, representing all of the wool variation likely to be encountered, may allow this NIRS potential to become relevant in the presale testing of wool as an inexpensive measurement procedure for estimating dark and medullated fibre content.

scholarly journals Effect of Hybrid Type on Fermentation and Nutritional Parameters of Whole Plant Corn Silage

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1587
Author(s):  
Yue Liu ◽  
Guogen Wang ◽  
Hao Wu ◽  
Qingxiang Meng ◽  
Muhammad Zahoor Khan ◽  
...  
Keyword(s):  
Acetic Acid ◽  
Dry Matter ◽  
Nutritive Value ◽  
Corn Silage ◽  
Neutral Detergent Fiber ◽  
Soluble Fiber ◽  
Dual Purpose ◽  
Nutritional Parameters ◽  
Hybrid Type ◽  
Whole Plant

This study was designed to evaluate the effect of hybrid type on the fermentation and nutritional parameters of whole-plant corn silage (dual-purpose and silage-specific corn). For this purpose, the two corn hybrid types were harvested at the one-half to three-fourths milk line and ensiled in fermentation bags (50 × 80 cm) for 60 day. Our results demonstrated that the ratio of lactic acid to acetic acid (p = 0.004), propionic acid (p < 0.001), Flieg point (p < 0.001), ether extract (p = 0.039), starch (p < 0.001), milk-per-ton index (p < 0.005), net energy for lactation (p = 0.003), total digestible nutrients (p < 0.001), neutral detergent soluble fiber (p =0.04), and in situ dry matter digestibility (TDMDis) (p < 0.001) were higher in dual-purpose corn silage, while the pH (p = 0.014), acetic acid (p = 0.007), the ratio of ammonia nitrogen to total nitrogen (p = 0.045), neutral detergent fiber (p < 0.001), acid detergent fiber (p < 0.001), acid detergent lignin (p < 0.001), dry matter yield per ha (p < 0.001), milk-per-acre index (p = 0.003), available neutral detergent fiber (p < 0.001), and unavailable neutral detergent fiber (p < 0.001) were higher in silage-specific corn silage. Based on our analysis, we concluded that under favourable production conditions for whole-plant corn silage, the nutritive value per unit was higher in dual-purpose corn while biomass yield and nutrient value per ha were higher in silage-specific corn.

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