Table 3.

Distinct approaches for hyperspectral imaging-based food grains evaluation.

Authors	HSI	Range (nm)	Food Grain	Approach	Accuracy (%)
Archibald et al. [43]	NIR	632–1098	Wheat	Histogram	–
Mahesh et al. [44]	NIR	960–1700	Wheat	ANN	100
Singh et al. [45]	NIR	700–1000	Wheat	BPNN	96.40
Singh et al. [46]	NIR	700–1000	Wheat	Quadratic	99.30
McGoverin et al. [53]	NIR	1920–1940	Wheat	PLS DA	–
Weinstock et al. [54]	NIR	950–1700	Corn	PLSA	–
William et al. [47]	NIR	960–1662	Maize	PLS DA	86.00
William et al. [55]	NIR	1000–2498	Maize	PLS RM	–
Shahinet et al. [56]	NIR	400–1000	Wheat	PLS	90.60
Caporaso et al. [57]	NIR	–	Cereal	–	–
Valenzuela et al. [48]	NIR	500–1000	Blueberries	–	87.00
Huang et al. [49]	NIR	600–1000	Apple	SVM	82.50
Huang et al. [50]	NIR	1193–1217	Salmon	GLCM	–
Ivorra et al. [51]	NIR	–	Salmon	PLS DA	82.70
Serranti et al. [52]	NIR	1006–1650	Oat & Grout	PLS DA	100