Details

Autor(en) / Beteiligte

• Ambrose, Ashabahebwa
• Kandpal, Lalit Mohan
• Kim, Moon S.
• Lee, Wang-Hee
• Cho, Byoung-Kwan

Titel

High speed measurement of corn seed viability using hyperspectral imaging

Ist Teil von

• Infrared physics & technology, 2016-03, Vol.75, p.173-179

Ort / Verlag

Elsevier B.V

Erscheinungsjahr

2016

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• •HSI technique was developed for investigation of microwave treated corn seeds.•PLSDA model classified treated and untreated corn seeds with high accuracy.•Image processing method was helpful for visualization and detection of untreated seeds form treated seeds.•HSI demonstrated a potential tool for detection of corn viability effected by heat treatment. Corn is one of the most cultivated crops all over world as food for humans as well as animals. Optimized agronomic practices and improved technological interventions during planting, harvesting and post-harvest handling are critical to improving the quantity and quality of corn production. Seed germination and vigor are the primary determinants of high yield notwithstanding any other factors that may play during the growth period. Seed viability may be lost during storage due to unfavorable conditions e.g. moisture content and temperatures, or physical damage during mechanical processing e.g. shelling, or over heating during drying. It is therefore vital for seed companies and farmers to test and ascertain seed viability to avoid losses of any kind. This study aimed at investigating the possibility of using hyperspectral imaging (HSI) technique to discriminate viable and nonviable corn seeds. A group of corn samples were heat treated by using microwave process while a group of seeds were kept as control group (untreated). The hyperspectral images of corn seeds of both groups were captured between 400 and 2500nm wave range. Partial least squares discriminant analysis (PLS-DA) was built for the classification of aged (heat treated) and normal (untreated) corn seeds. The model showed highest classification accuracy of 97.6% (calibration) and 95.6% (prediction) in the SWIR region of the HSI. Furthermore, the PLS-DA and binary images were capable to provide the visual information of treated and untreated corn seeds. The overall results suggest that HSI technique is accurate for classification of viable and non-viable seeds with non-destructive manner.