Kaba Yem Kalitesinin Near Infrared Reflectance (NIR) Spektroskopisi ve Kemometrik Teknikler ile Tahmin Edilmesi

Abstract

Yakın Kızılötesi Spektroskopisi yem kalite değerlendirmelerinde yaygın olarak kullanılmaya başlanmıştır. Yapılan çalışmaların büyük kısmı lifli bileşenlerin NIR ile tespitine yönelik olarak yürütülmüştür. Kaba yem kalitesinin değerlendirilmesinde kullanılan Nisbi yem değeri (Relative Forage Value, RFV), Nisbi yem Kalitesi (Relative Forage Quality, RFQ) ve Net Enerji Laktasyon (Net Energy Lactation, NEL) gibi farklı kalite özelliklerine yönelik ise model geliştirme çalışmaları henüz yaygınlaşmamıştır. Bu çalışmada farklı kaba yem örneklerinde NFV, RFQ ve NEL değerlerinin NIR spektroskopisi ile tespiti ve dalgaboyu seçiminin model başarısı üzerine etkisinin araştırılması amaçlanmıştır. Araştırmada silaj, yonca kuru otu, yulaf kuru otu ve buğday samanı örneklerinde alınan spektral veriler ve laboratuvar analiz sonuçları kullanılarak kısmı en küçük kareler regresyon (PLSR) yöntemine göre tahmin modelleri geliştirilmiştir. Dalga boyu seçim yöntemi olarak variable importance projection (VIP) metodundan yararlanılmıştır. Araştırma bulgularına göre geliştirilen tahmin modellerinin RFV için VIP-PLS model kombinasyonundan (RMSE=12.7, Bias=0,000, R2=0,804, RPD=2,28) elde edilmiştir. VIP yöntemi bütün değişkenler için tahmin başarısını yükseltmiştir. Araştırma bulgularına dayanarak, kaba yem kalite değerlendirme parametrelerinde kullanılan hesaplamaların NIR ile tespitinin mümkün olduğu anlaşılmıştır.

Keywords

• Yakın Kızılötesi Yansıma
• Kaba yem kalitesi
• Dalga boyu seçimi
• kemometri

Estimating Roughage Quality with Near Infrared Reflectance (NIR) Spectroscopy and Chemometric Techniques

Abstract

Near-Infrared Spectroscopy has been commonly adopted in feed quality evaluations. The majority of studies have been performed on the detection of fibrous components with the help of NIR. Model development studies are not yet common for different roughage quality characteristics such as Relative Forage Value (RFV), Relative Forage Quality (RFQ), and Net Energy Lactation (NEL), which are used in the evaluation of roughage quality. The purpose of this study is the detection of RFV, RFQ, and NEL values with NIR spectroscopy in different roughage samples, and to investigate the effect of wavelength selection on the model's success. In this study, spectral data belonging to silage, dry alfalfa, dry oat, and wheat straw samples and laboratory analysis results were used to develop estimation models according to the partial least square regression (PLSR) method. A variable importance projection (VIP) method was used as the wavelength selection method. Estimation models, which were developed according to study results, were obtained from the VIP-PLS model combination (RMSE=12.7, Bias=0.000, R2=0.804, RPD=2.28) for RFV. VIP method has increased the estimation of success for all variables. Based on the study results, it was recognized that it is possible to use NIR in the calculations used in roughages quality evaluation parameters.

Keywords

• Near-İnfrared Reflectance (NIR)
• Wavelength Selection
• Roughage quality
• Chemometrics

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