Nondestructive Quantification of Foliar Chlorophyll in an Apple Orchard by Visible/Near-Infrared Reflectance Spectroscopy and Partial Least Squares

2014 ◽  
Vol 47 (6) ◽  
pp. 481-487 ◽  
Author(s):  
Zhiming Guo ◽  
Chunjiang Zhao ◽  
Wenqian Huang ◽  
Yan'an Wang ◽  
Jianhua Guo
2016 ◽  
Vol 1 (1) ◽  
pp. 1059-1068
Author(s):  
Masdar Masdar ◽  
Agus Arip Munawar ◽  
Zulfahrizal Zulfahrizal

Rendahnya pengawasan mutu kakao menyebabkan harga jual di pasar dunia menurun akibat kurangnya pengawasan kadar air. Salah satu metode yang tepat dan cepat dalam penentuan kadar air adalah menggunakan atau Near Infrared Reflectance Spectroscopy (NIRS). Tujuan penelitian adalah melihat kemampuan NIRS dalam memprediksi kadar air bubuk biji kakao dengan menggunakan metode Partial Least Squares (PLS) serta membandingkan dua metode pretreatment De-trending dan Derivatif ke-2.Alat yang digunakan FT-IR IPTEK T-1516, dan pengolahan data dengan unscrambler software® X version 10. Hasil penelitian menunjukkan NIRS mampu menduga kadar air dalam jumlah 10 gram dengan selang kadar air 7.42 – 11.09 % menggunakan PLS secara non pretreatment maupun pretreatment. Panjang gelombang relevan dalam menduga kadar air bubuk biji kakao adalah  1400-1450 nm dan 1800-1950 nm. Peningkatkan kinerja PLS yang paling bagus menggunakan pretreatment derivative ke-2.Abstract The lowest quality of cocoa supervision cause the selling price descrease due to the lack of supervision on the water content. One of the exact method in determining the water content is Near Infrared Reflectance Spectroscopy (NIRS). The purpose of this study is to know the capability of NIRS in order to predict the water content of cocoa by using Partial Least Squares (PLS) method then compared the two pretreatment methods namely De-trending and second Derivative. The instrument used was FT-IR IPTEK T-1516, and the spectra data were analyzed by using unscrambler software® X version 10. The results showed that NIRS can be used to predict the water content in amount 10 grams in a range of water content 7:42 to 11:09% by using PLS non pretreatment and vice versa. The relevantwavelengthsused to predict water content of cocoa powder ware1400-1450 nm and 1800-1950 nm. The optimum best pretreatment method was found to be second Derivative.


2021 ◽  
pp. 096703352110075
Author(s):  
Adou Emmanuel Ehounou ◽  
Denis Cornet ◽  
Lucienne Desfontaines ◽  
Carine Marie-Magdeleine ◽  
Erick Maledon ◽  
...  

Despite the importance of yam ( Dioscorea spp.) tuber quality traits, and more precisely texture attributes, high-throughput screening methods for varietal selection are still lacking. This study sets out to define the profile of good quality pounded yam and provide screening tools based on predictive models using near infrared reflectance spectroscopy. Seventy-four out of 216 studied samples proved to be moldable, i.e. suitable for pounded yam. While samples with low dry matter (<25%), high sugar (>4%) and high protein (>6%) contents, low hardness (<5 N), high springiness (>0.5) and high cohesiveness (>0.5) grouped mostly non-moldable genotypes, the opposite was not true. This outline definition of a desirable chemotype may allow breeders to choose screening thresholds to support their choice. Moreover, traditional near infrared reflectance spectroscopy quantitative prediction models provided good prediction for chemical aspects (R2 > 0.85 for dry matter, starch, protein and sugar content), but not for texture attributes (R2 < 0.58). Conversely, convolutional neural network classification models enabled good qualitative prediction for all texture parameters but hardness (i.e. an accuracy of 80, 95, 100 and 55%, respectively, for moldability, cohesiveness, springiness and hardness). This study demonstrated the usefulness of near infrared reflectance spectroscopy as a high-throughput way of phenotyping pounded yam quality. Altogether, these results allow for an efficient screening toolbox for quality traits in yams.


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