Corrigendum to: Optimisation of dry matter and nutrients in feed rations through use of a near-infrared spectroscopy system mounted on a self-propelled feed mixer

2021 ◽  
Vol 61 (5) ◽  
pp. 540
Author(s):  
Ehab Mostafa ◽  
Philipp Twickler ◽  
Alexander Schmithausen ◽  
Christian Maack ◽  
Abdelkader Ghaly ◽  
...  

Context Knowledge of the nutrient requirements of dairy cows, and the nutritional composition and physical form of the feed resources used to prepare the total mixed ration (TMR) of basic and concentrated feeds, is essential to achieving high milk yields, health and welfare in modern commercial herds. Grass and maize silage components can vary widely in composition depending on harvesting intervals and weather; thus, the distribution of dry matter (DM) and nutrients in silos may vary greatly, resulting in serious errors during sampling and analysis. In addition, the flow of information from the stored silage stops once the forages are stored in the silo. Aims The objective of this study was to develop a practical approach for measuring variations in DM and silage quality parameters (crude protein, fibre, ash and fat) during the feed-extraction process from a bunker silo by a self-propelled feed mixer, which would ultimately help farmers to optimise the TMR. Methods Near-infrared spectroscopy (NIRS) technology was used to estimate fodder DM and nutrient contents in the material flow. Wet chemical analyses were used for preliminary evaluation of grass and maize silage samples. A portable NIRS was developed to record the spectra of various silage samples. Key results The spans of calibration of sample DM content were 21.3–59.2% for grass and 26–46.7% for maize. Crude protein content had span values of 11.4–18.3% for the grass silage and 5.4–10.8% for the maize silage models. Conclusions NIRS technology was used successfully to estimate the DM and nutrient contents of the fodder. The location for the functional unit on the self-propelled feed mixer may need to be modified for series production because it is not fully accessible. Implications NIRS is a suitable method for measuring DM and nutrient contents continuously during feed extraction from the bunker silo and can be used to help farmers to optimise the TMR.

1998 ◽  
Vol 6 (1) ◽  
pp. 145-151 ◽  
Author(s):  
Begoña De la Roza ◽  
Adela Martínez ◽  
Begoña Santos ◽  
Javier González ◽  
Guillermo Gómez

A total of 130 silages samples (53 of maize silages and 77 of grass silages), which were ensiled with or without silage additives, with different soil contamination levels, with different weed percentages and with or without wilting, were used to evaluate the dry matter (DM) and crude protein (CP) ruminal degradability. The ruminal degradability of the samples was calculated from the corresponding in situ degradation parameters and from the measured passage rates of the silages fed to each experimental animal. The DM and CP degradation parameters were obtained using the logistic model of Van Milgen and Baumont. The fitting of the models to the kinetics of degradation and particle passage was carried out by non-linear regression. The value of the effective degradability, considering in the rumen simultaneously an outflow compartment and a mixing–reduction compartment, were calculated in both cases from an adaptation of the general procedure proposed by Ørskov and McDonald. A NIRSystems 6500 spectrometer was used for the prediction of the DM and the CP degradation characteristics of the samples. Calibration equations were obtained by modified partial least squares regression, using reflectance spectra transformed into the second derivative. The results showed that near infrared spectroscopy is a good method for predicting the DM and CP degradation characteristics. The calibrations for effective degradability of maize and grass silages indicated a high consistency.


2016 ◽  
Vol 56 (9) ◽  
pp. 1504 ◽  
Author(s):  
J. P. Keim ◽  
H. Charles ◽  
D. Alomar

An important constraint of in situ degradability studies is the need to analyse a high number of samples and often with insufficient amount of residue, especially after the longer incubations of high-quality forages, that impede the study of more than one nutritional component. Near-infrared spectroscopy (NIRS) has been established as a reliable method for predicting composition of many entities, including forages and other animal feedstuffs. The objective of this work was to evaluate the potential of NIRS for predicting the crude protein (CP) and neutral detergent fibre (NDF) concentration in rumen incubation residues of permanent and sown temperate pastures in a vegetative stage. In situ residues (n = 236) from four swards were scanned for their visible-NIR spectra and analysed for CP and NDF. Selected equations developed by partial least-squares multivariate regression presented high coefficients of determination (CP = 0.99, NDF = 0.95) and low standard errors (CP = 4.17 g/kg, NDF = 7.91 g/kg) in cross-validation. These errors compare favourably to the average concentrations of CP and NDF (146.5 and 711.2 g/kg, respectively) and represent a low fraction of their standard deviation (CP = 38.2 g/kg, NDF = 34.4 g/kg). An external validation was not as successful, with R2 of 0.83 and 0.82 and a standard error of prediction of 14.8 and 15.2 g/kg, for CP and NDF, respectively. It is concluded that NIRS has the potential to predict CP and NDF of in situ incubation residues of leafy pastures typical of humid temperate zones, but more robust calibrations should be developed.


Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8222
Author(s):  
Olga Escuredo ◽  
Laura Meno ◽  
María Shantal Rodríguez-Flores ◽  
Maria Carmen Seijo

The aim of the present work was to determine the main quality parameters on tuber potato using a portable near-infrared spectroscopy device (MicroNIR). Potato tubers protected by the Protected Geographical Indication (PGI “Patata de Galicia”, Spain) were analyzed both using chemical methods of reference and also using the NIR methodology for the determination of important parameters for tuber commercialization, such as dry matter and reducing sugars. MicroNIR technology allows for the attainment/estimation of dry matter and reducing sugars in the warehouses by directly measuring the tubers without a chemical treatment and destruction of samples. The principal component analysis and modified partial least squares regression method were used to develop the NIR calibration model. The best determination coefficients obtained for dry matter and reducing sugars were of 0.72 and 0.55, respectively, and with acceptable standard errors of cross-validation. Near-infrared spectroscopy was established as an effective tool to obtain prediction equations of these potato quality parameters. At the same time, the efficiency of portable devices for taking instantaneous measurements of crucial quality parameters is useful for potato processors.


2006 ◽  
Vol 125 (6) ◽  
pp. 591-595 ◽  
Author(s):  
J. M. Montes ◽  
H. F. Utz ◽  
W. Schipprack ◽  
B. Kusterer ◽  
J. Muminovic ◽  
...  

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