Non-destructive characterization of pulse flours from different milling methods
| dc.contributor.author | Sivakumar, Chitra | |
| dc.contributor.examiningcommittee | Ramachandran, Rani (Biosystems Engineering) Erkinbaev, Chyngyz (Biosystems Engineering) | en_US |
| dc.contributor.supervisor | Paliwal, Jitendra (Biosystems Engineering) | en_US |
| dc.date.accessioned | 2021-08-26T21:27:41Z | |
| dc.date.available | 2021-08-26T21:27:41Z | |
| dc.date.copyright | 2021-08-23 | |
| dc.date.issued | 2021-08 | en_US |
| dc.date.submitted | 2021-08-23T15:37:58Z | en_US |
| dc.degree.discipline | Biosystems Engineering | en_US |
| dc.degree.level | Master of Science (M.Sc.) | en_US |
| dc.description.abstract | With increasing consumer interest in pulse flour-based food formulations, characterization of pulse flours based on pulse-type and milling techniques has become crucial. The present research work is aimed at using non-destructive imaging techniques including visible near-infrared (Vis-NIR) and shortwave infrared (SWIR) hyperspectral imaging and scanning electron microscopy (SEM) for pulse flour characterization. Four different types of pulses namely, chickpea, yellow pea, navy bean, and green lentil milled using a single-stage Ferkar mill and a multistage roller mill were studied. Hyperspectral imaging was used for classifying these flours based on pulse-type and milling methods, through the development of unsupervised and supervised classification models and classification maps. In the case of supervised classification of pulse-type, the wavelength range of 530 to 700 nm contributed to the color attributes of the biological samples yielding 100% classification accuracy. For milling method based supervised classification, the wavelength regions, 1370 to 1500 nm, and 1700 to 2000 nm, that capture the protein content of the flour, yielded 95% classification accuracy. SEM was used to study the microstructural changes of the flours. Stream-based and pulse-type classifications were conducted to study the relationship between particle size distribution and protein content, and characteristics of starch-protein matrices. The findings from SEM images revealed that fine distribution of protein bodies was found in Ferkar milled and straight grade (SG) stream of roller milled flours with similar protein content. On the other hand, the reduction stream had higher protein content and starch damage than the break stream. The presence of pores was higher in chickpea starches for both roller and Ferkar milled flours. Navy bean flours possessed the highest starch-protein cluster count. Traces of bran particles were clearly visible in green lentil flours obtained from roller and Ferkar mills. Hence, from SEM results it can be inferred that the microstructure and protein content of the pulse flours is influenced by the pulse type and milling method. Overall, it can be concluded that non-destructive imaging techniques such as Vis-NIR and SWIR hyperspectral imaging and SEM can prove to be a useful tool for pulse flour characterization based on pulse-type and milling methods. | en_US |
| dc.description.note | October 2021 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1993/35842 | |
| dc.rights | open access | en_US |
| dc.subject | characterization | en_US |
| dc.subject | pulse flours | en_US |
| dc.subject | hyperspectral imaging | en_US |
| dc.subject | scanning electron microscopy | en_US |
| dc.subject | milling | en_US |
| dc.title | Non-destructive characterization of pulse flours from different milling methods | en_US |
| dc.type | master thesis | en_US |