Back to Search Start Over

Thermal and hyperspectral imaging for Norway spruce (Picea abies) seeds screening

Authors :
Markku Keinänen
Sarita Keski-Saari
Markku Nygren
Laure Fauch
Tapani Hirvonen
Lars Granlund
Ilkka Porali
Katri Himanen
Elina Oksanen
Markku Hauta-Kasari
Jennifer Dumont
Jouni Hiltunen
Maxime Mistretta
Ville Heikkinen
Source :
Computers and Electronics in Agriculture. 116:118-124
Publication Year :
2015
Publisher :
Elsevier BV, 2015.

Abstract

Hyperspectral and thermal lifetime imaging were used to assess spruce seed quality.Viable, empty and infested seeds were resolved with high accuracy with both methods.400-1000nm data was not as informative as 1000-2500nm and thermal decay data.Classification of 93% accuracy was obtained using three wavelengths in SWIR range.The results suggest that high-throughput spruce seed quality testing is possible. The quality of seeds used in agriculture and forestry is tightly linked to the plant productivity. Thus, the development of high-throughput nondestructive methods to classify the seeds is of prime interest. Visible and near infrared (VNIR, 400-1000nm range) and short-wave infrared (SWIR, 1000-2500nm range) hyperspectral imaging techniques were compared to an infrared lifetime imaging technique to evaluate Norway spruce (Picea abies (L.) Karst.) seed quality. Hyperspectral image and thermal data from 1606 seeds were used to identify viable seeds, empty seeds and seeds infested by Megastigmus sp. larvae. The spectra of seeds obtained from hyperspectral imaging, especially in SWIR range and the thermal signal decay of seeds following an exposure to a short light pulse were characteristic of the seed status. Classification of the seeds to three classes was performed with a Support Vector Machine (nu-SVM) and sparse logistic regression based feature selection. Leave-One-Out classification resulted to 99% accuracy using either thermal or spectral measurements compared to radiography classification. In spectral imaging case, all important features were located in the SWIR range. Furthermore, the classification results showed that accurate (93.8%) seed sorting can be achieved with a simpler method based on information from only three hyperspectral bands at 1310nm, 1710nm and 1985nm locations, suggesting a possibility to build an inexpensive screening device. The results indicate that combined classification methods with hyperspectral imaging technique and infrared lifetime imaging technique constitute practically high performance fast and non-destructive techniques for high-throughput seed screening.

Details

ISSN :
01681699
Volume :
116
Database :
OpenAIRE
Journal :
Computers and Electronics in Agriculture
Accession number :
edsair.doi...........f5482ef04b67c51e4d9416f7968f912f