Prediction of Fermentation Parameters in Grass and Corn Silage by Near Infrared Spectroscopy

Abstract

Prediction models were developed for determination of lactic acid (Lac), acetic acid (HAc), pH, NH 3 N, and ethanol (EtOH) in grass and corn silages by near infrared (NIR) spectroscopy. Generally, Lac, pH, and NH 3 N concentrations in original sample material could be determined with a better accuracy when NIR measurements were performed on dried material rather than on wet material. The difference could only partly be explained by the repeatability error of NIR measurements for compounds stable with respect to drying. The HAc concentration was determined slightly more accurately when measurements were performed on wet material. The respective ratios between analytical concentration range expressed as standard deviation and the root mean square error of cross validation (RMSECV) were 4.9, 2.0, 3.7, and 3.1 for Lac, HAc, pH, and NH 3 N measured on dried grass silage, and 3.3 for EtOH measured on wet grass silage. The corresponding standard deviation:RMSECV for corn silage were 4.7, 1.9, 2.4, 2.9, and 4.0. The content of Lac was affected only slightly by drying at 80°C, whereas the effects on NH 3 N and HAc were more pronounced, depending on silage type.

Propanol in maize silage at Danish dairy farms

“…However, due to the absence of a test for propanol content in the routine analyses on maize silage for feed value and fermentation quality data, recordings of propanol levels and prevalence of propanol occurrence in maize silage under field conditions are generally not available (Sørensen, 2004). In order to address the fundamental concern about the impact of propanol containing silage on dairy cows, we initially aimed to establish fundamental knowledge on the prevalence of propanol containing maize silage at randomly selected dairy farms.…”

La spectrométrie dans le proche infrarouge pour la caractérisation des ressources alimentaires

“…La prédiction des paramètres fermentaires des ensilages peut également être obtenue par analyse SPIR (Sinneave et al, 1994 ;Sørensen, 2004). Certains composés étant volatils ou fortement affectés par le séchage (NH 3 , acide acétique, acides gras volatils), il est nécessaire de prendre les spectres sur le produit frais, ce qui diminue la précision de la prédiction car les échantillons soumis à l'analyse SPIR sont alors plus hétérogènes.…”

“…Certains composés étant volatils ou fortement affectés par le séchage (NH 3 , acide acétique, acides gras volatils), il est nécessaire de prendre les spectres sur le produit frais, ce qui diminue la précision de la prédiction car les échantillons soumis à l'analyse SPIR sont alors plus hétérogènes. Pour d'autres paramètres moins sensibles au séchage (par exemple l'acide lactique) la prédiction peut être faite sur les échantillons séchés (Sørensen, 2004). La SPIR, lorsqu' elle est utilisée comme un outil d'analyse est une méthode indirecte, nécessitant le développement d' étalonnages (ou « calibrations » selon un anglicisme fréquent).…”

Retrieving the Bioenergy Potential from Maize Crops Using Hyperspectral Remote Sensing

“…NIRS is widely used in feed and food quality monitoring [19][20][21][22][23][24][25][26] and is accepted since many years as routine method for determining forage quality parameters of various crops. In the bioenergy sector NIRS has been applied to estimate sulphur content in biodiesel [27], for predicting digestibility of maize silage [28][29][30] and fermentation parameters of silages [31], and for the assessment of in situ degradability parameters of crude protein and dry matter characteristics [32,33].…”