TY - JOUR
T1 - Animal feed formulation
T2 - Rapid and non-destructive measurement of components from waste by-products
AU - Uyeh, Daniel Dooyum
AU - Ha, Yushin
AU - Park, Tusan
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/4
Y1 - 2021/4
N2 - The major cost (60–80%) of animal production is attributed to feed but most growers are yet to accept and adopt alternative materials like by-products due to their vast variations in nutrient components. Feed and animal production methods are currently considered as unsustainable -with environmental issues related to by-products disposal. Rapid and non-destructive models for quantifying sugars, organic acids, amino acids and other nutrients in alternative materials and a model for precision animal feed production were developed. Consequently, we investigated the nutrient components of by-products using line-scan hyperspectral imaging (HSI) technique. Hyperspectral images of by-products were acquired in the spectral range of 1000–2500 nm. The spectral data were extracted and preprocessed to develop a prediction model using partial least square regression (PLSR) analysis. The PLSR models developed resulted in the following acceptable prediction accuracies (R2p); sugars (0.76–0.94), organic acids (0.72–0.75), amino acids (0.55–0.84), and other nutrients content (0.69–0.96). The root means square error of predictions (RMSEP) obtained were sugars (0.076–0.524 mg/mL), organic acids (0.360–0.626 mg/mL), amino acids (0.007–0.052 mg/mL), and other nutrients content (0.403–1.035 %). The results obtained from the PLSR models showed reliable performance for quantifying chemical components of different by-products. Further, the generated PLSR-based chemical-mapped images facilitated the visual assessment of the chemical concentration and distribution in by-products. Thus, based on the results, the application of HSI in combination with multivariate analysis method of PLSR in a commercial setting may be feasible. This can ultimately enable cost-saving in breeding by curtailing overfeeding and post-production losses and significantly mitigate environmental issues related to by-products disposal.
AB - The major cost (60–80%) of animal production is attributed to feed but most growers are yet to accept and adopt alternative materials like by-products due to their vast variations in nutrient components. Feed and animal production methods are currently considered as unsustainable -with environmental issues related to by-products disposal. Rapid and non-destructive models for quantifying sugars, organic acids, amino acids and other nutrients in alternative materials and a model for precision animal feed production were developed. Consequently, we investigated the nutrient components of by-products using line-scan hyperspectral imaging (HSI) technique. Hyperspectral images of by-products were acquired in the spectral range of 1000–2500 nm. The spectral data were extracted and preprocessed to develop a prediction model using partial least square regression (PLSR) analysis. The PLSR models developed resulted in the following acceptable prediction accuracies (R2p); sugars (0.76–0.94), organic acids (0.72–0.75), amino acids (0.55–0.84), and other nutrients content (0.69–0.96). The root means square error of predictions (RMSEP) obtained were sugars (0.076–0.524 mg/mL), organic acids (0.360–0.626 mg/mL), amino acids (0.007–0.052 mg/mL), and other nutrients content (0.403–1.035 %). The results obtained from the PLSR models showed reliable performance for quantifying chemical components of different by-products. Further, the generated PLSR-based chemical-mapped images facilitated the visual assessment of the chemical concentration and distribution in by-products. Thus, based on the results, the application of HSI in combination with multivariate analysis method of PLSR in a commercial setting may be feasible. This can ultimately enable cost-saving in breeding by curtailing overfeeding and post-production losses and significantly mitigate environmental issues related to by-products disposal.
KW - Agricultural and industrial by-products
KW - Animal nutrition
KW - Hyperspectral imaging
KW - Partial least square regression
KW - Precision animal feed production
UR - http://www.scopus.com/inward/record.url?scp=85100421156&partnerID=8YFLogxK
U2 - 10.1016/j.anifeedsci.2021.114848
DO - 10.1016/j.anifeedsci.2021.114848
M3 - Article
AN - SCOPUS:85100421156
SN - 0377-8401
VL - 274
JO - Animal Feed Science and Technology
JF - Animal Feed Science and Technology
M1 - 114848
ER -