Your browser doesn't support javascript.
loading
Innovative technology integration: E tongue, near infrared grain tester & machine vision approaches for amylose content & quality characterization.
Fayaz, Ufaq; Hussain, Syed Zameer; Naseer, Bazila; Bej, Gopinath; Pal, Abhra; Sarkar, Subrata; Wani, Nazrana Rafique; Mushtaq, Khalid; Yasmin, Salwee; Dhekale, B S; Richa, Rishi; Manzoor, Sobiya.
Afiliación
  • Fayaz U; Division of Food Science and Technology, Sher-e-Kashmir University of Agriculturual Sciences and Technology of Kashmir, Shalimar 190025, India.
  • Hussain SZ; Division of Food Science and Technology, Sher-e-Kashmir University of Agriculturual Sciences and Technology of Kashmir, Shalimar 190025, India.
  • Naseer B; Division of Food Science and Technology, Sher-e-Kashmir University of Agriculturual Sciences and Technology of Kashmir, Shalimar 190025, India.
  • Bej G; Centre for Development of Advanced Computing (C-DAC), Kolkata, India.
  • Pal A; Centre for Development of Advanced Computing (C-DAC), Kolkata, India.
  • Sarkar S; Centre for Development of Advanced Computing (C-DAC), Kolkata, India.
  • Wani NR; Division of Food Science and Technology, Sher-e-Kashmir University of Agriculturual Sciences and Technology of Kashmir, Shalimar 190025, India.
  • Mushtaq K; Division of Fruit Science, Sher-e-Kashmir University of Agricultural Sciences and Technology (SKUAST) Kashmir, Shalimar 190025, India.
  • Yasmin S; Central Institute of Temperate Horticulture, Kashmir, Rangreth, 190005, J&K, India.
  • Dhekale BS; Division of Agricultural Statistics, Sher-e-Kashmir University of Agricultural Sciences and Technology (SKUAST) Kashmir, Shalimar 190025, India.
  • Richa R; College of Agricultural Engineering and Technology, Sher-e-Kashmir University of Agriculture Sciences and Technology of Kashmir, Shalimar 190025, India.
  • Manzoor S; Division of Food Science and Technology, Sher-e-Kashmir University of Agriculturual Sciences and Technology of Kashmir, Shalimar 190025, India.
Food Chem X ; 24: 101805, 2024 Dec 30.
Article en En | MEDLINE | ID: mdl-39296480
ABSTRACT
E-tongue, machine vision and NIR systems were used to standardize the quality measurements in twenty rice genotypes grown in Highland Himalayan regions of Kashmir, in order to overcome the constraints of manual measurements. IRCTN-312 showed highest amylose content of 20.74 % and 20.70 % using iodometric method and NIR tester, which was validated by the highest norm value of 34.158 by E-tongue. From these results, genotypes such as GSR-43, GS-103, GSR-23B, GSR-60, SR-4, GSR-46, Koshihikari, GSR-64, GSR-32, GSR-49, GSR-4, GSR-42, GS-459, SKUA-494 and SKUA-540 were classified as low amylose and C-3, K-332, M4-22 and IRCTN-312 were classified as intermediate amylose in the present study. Lowest percentage of damaged grains and chalk ratio was found in GSR-23B. SKUA-494 recorded highest L/W ratio using both the systems. Highest head rice yield and elongation ratio was found in GSR-23B and SKUA-494 genotypes respectively. Highest lightness (L*) value was recorded for Koshihikari genotype.
Palabras clave
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Food Chem X Año: 2024 Tipo del documento: Article País de afiliación: India
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Food Chem X Año: 2024 Tipo del documento: Article País de afiliación: India