Year 2019, Volume 29, Issue 1, Pages 43 - 51 2019-03-29

Prediction of Protein Content of Winter Wheat by Canopy of Near Infrared Spectroscopy (NIRS), Using Partial Least Squares Regression (PLSR) and Artificial Neural Network (ANN) Models
Kısmi En Küçük Kareler Regresyonu (KEKKR) ve Yapay Sinir Ağı (YSA) Modelleri Kullanarak, Kanopi Kızılötesi Spektroskopisi (KS) ile Kış Buğdayında Protein İçeriğinin Tahmini

Vali Rasooli SHARABIANI [1] , Araz Soltani NAZARLOO [2] , Ebrahim TAGHINEZHAD [3]

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In this study to predict amount of protein in wheat, near infrared spectroscopy technique (NIRS) was used that is a non-destructive and fast observing method. Partial Least Squares Regression (PLSR) and Artificial Neural Network (ANN) methods were used to choose the spectral bands and the best models, respectively. To compare the efficiency of models Root-mean-square error (RMSE) and R2 were applied. The finest consequence by cascade forward back propagation (CFBP) was related to network structure of 8-8-1 with Levenberg-Marquardt (LM), and function of TANSIG-TANSIG-PURELIN (TANSIG-TANSIG-PURELIN (R𝑀𝑆𝐸=0.0289 and 𝑅2=0.9881 at 14 epochs). The consequences of estimation for ANN model (𝑅2=0.9881) was better than the PLSR model (𝑅2=0.9783). Therefore, according to the results, it can be said that NIRS has a high potential for predicting the amount of protein in wheat. 

Bu çalışmada, buğdaydaki protein miktarını tahmin etmek için, tahribatsız ve hızlı bir gözlem yöntemi olan yakın kızılötesi spektroskopi (KS) tekniği kullanılmıştır. Sırasıyla spektral bantları ve en iyi modelleri seçmek için Kısmi En Küçük Kareler Regresyonu (KEKKR) ve Yapay Sinir Ağı (YSA) yöntemleri kullanılmıştır. Modellerin verimliliğini karşılaştırmak için Kök-ortalama-kare hata (KOKH) ve R2 uygulanmıştır. Cascade ileri geri yayılımının (CİGY) en iyi sonucu, Levenberg-Marquardt (LM) ile 8-8-1 ağ yapısı ve TANSIG-TANSIG-PURELIN (TANSIG-TANSIG-PURELIN (R𝑀𝑆𝐸 = 0.0289 ve 𝑅2) 'nin işlevi ile ilgilidir. YSA modeli için tahmin sonuçları (𝑅2 = 0.9881), KEKKR modelinden (𝑅2 = 0.9783) daha iyi bulunmuştur. Bu nedenle, sonuçlara göre, buğdaydaki protein miktarının belirlenmesinde KS'nin tahmin etme potansiyeli yüksek olduğu söylenebilir. 

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Primary Language en
Subjects Engineering
Published Date 2019
Journal Section Articles
Authors

Orcid: 0000-0001-5981-5229
Author: Vali Rasooli SHARABIANI (Primary Author)
Institution: Department of Biosystem Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil
Country: Iran


Author: Araz Soltani NAZARLOO
Institution: Department of Biosystem Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil
Country: Iran


Author: Ebrahim TAGHINEZHAD
Institution: Moghan College of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil
Country: Iran


Bibtex @research article { yyutbd447926, journal = {Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi}, issn = {1308-7576}, eissn = {1308-7584}, address = {Yuzuncu Yil University}, year = {2019}, volume = {29}, pages = {43 - 51}, doi = {10.29133/yyutbd.447926}, title = {Prediction of Protein Content of Winter Wheat by Canopy of Near Infrared Spectroscopy (NIRS), Using Partial Least Squares Regression (PLSR) and Artificial Neural Network (ANN) Models}, key = {cite}, author = {SHARABIANI, Vali Rasooli and NAZARLOO, Araz Soltani and TAGHINEZHAD, Ebrahim} }
APA SHARABIANI, V , NAZARLOO, A , TAGHINEZHAD, E . (2019). Prediction of Protein Content of Winter Wheat by Canopy of Near Infrared Spectroscopy (NIRS), Using Partial Least Squares Regression (PLSR) and Artificial Neural Network (ANN) Models. Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi, 29 (1), 43-51. DOI: 10.29133/yyutbd.447926
MLA SHARABIANI, V , NAZARLOO, A , TAGHINEZHAD, E . "Prediction of Protein Content of Winter Wheat by Canopy of Near Infrared Spectroscopy (NIRS), Using Partial Least Squares Regression (PLSR) and Artificial Neural Network (ANN) Models". Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi 29 (2019): 43-51 <http://dergipark.org.tr/yyutbd/issue/44253/447926>
Chicago SHARABIANI, V , NAZARLOO, A , TAGHINEZHAD, E . "Prediction of Protein Content of Winter Wheat by Canopy of Near Infrared Spectroscopy (NIRS), Using Partial Least Squares Regression (PLSR) and Artificial Neural Network (ANN) Models". Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi 29 (2019): 43-51
RIS TY - JOUR T1 - Prediction of Protein Content of Winter Wheat by Canopy of Near Infrared Spectroscopy (NIRS), Using Partial Least Squares Regression (PLSR) and Artificial Neural Network (ANN) Models AU - Vali Rasooli SHARABIANI , Araz Soltani NAZARLOO , Ebrahim TAGHINEZHAD Y1 - 2019 PY - 2019 N1 - doi: 10.29133/yyutbd.447926 DO - 10.29133/yyutbd.447926 T2 - Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi JF - Journal JO - JOR SP - 43 EP - 51 VL - 29 IS - 1 SN - 1308-7576-1308-7584 M3 - doi: 10.29133/yyutbd.447926 UR - https://doi.org/10.29133/yyutbd.447926 Y2 - 2019 ER -
EndNote %0 Yuzuncu Yıl University Journal of Agricultural Sciences Prediction of Protein Content of Winter Wheat by Canopy of Near Infrared Spectroscopy (NIRS), Using Partial Least Squares Regression (PLSR) and Artificial Neural Network (ANN) Models %A Vali Rasooli SHARABIANI , Araz Soltani NAZARLOO , Ebrahim TAGHINEZHAD %T Prediction of Protein Content of Winter Wheat by Canopy of Near Infrared Spectroscopy (NIRS), Using Partial Least Squares Regression (PLSR) and Artificial Neural Network (ANN) Models %D 2019 %J Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi %P 1308-7576-1308-7584 %V 29 %N 1 %R doi: 10.29133/yyutbd.447926 %U 10.29133/yyutbd.447926
ISNAD SHARABIANI, Vali Rasooli , NAZARLOO, Araz Soltani , TAGHINEZHAD, Ebrahim . "Prediction of Protein Content of Winter Wheat by Canopy of Near Infrared Spectroscopy (NIRS), Using Partial Least Squares Regression (PLSR) and Artificial Neural Network (ANN) Models". Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi 29 / 1 (March 2019): 43-51. https://doi.org/10.29133/yyutbd.447926