Journal of Food Processing & Technology

Bhole V, Kumar A. Mango Quality Grading using Deep Learning Technique: Perspectives from Agriculture and Food Industry. InProceedings of the 21st Annual Conference on Information Technology Education 2020 Oct 7 (pp. 180-186).

Torres JP, Ávila M, Caro A, Pérez-Palacios T, Caballero D. Non-destructively Prediction of Quality Parameters of Dry-Cured Iberian Ham by Applying Computer Vision and Low-Field MRI. InIberian Conference on Pattern Recognition and Image Analysis 2019 Jul 1 (pp. 498-507). Springer, Cham.

Dewi T, Risma P, Oktarina Y. Fruit sorting robot based on color and size for an agricultural product packaging system. Bulletin of Electrical Engineering and Informatics. 2020 Aug 1;9(4):1438-45.

Rajin SM, Abdul S, Anuar S, Muad M. Evaluation of the quality of grapes using machine vision. Recent Advance Intelligent Control Modelling Simulation. 2013:176-80.

Pande A, Munot M, Sreeemathy R, Bakare RV. An Efficient Approach to Fruit Classification and Grading using Deep Convolutional Neural Network. In2019 IEEE 5th International Conference for Convergence in Technology (I2CT) 2019 Mar 29 (pp. 1-7). IEEE.

Bandyopadhyaya I, Babu D, Bhattacharjee S, Roychowdhury J. Vegetable grading using tactile sensing and machine learning. InAdvanced Computing, Networking and Informatics-Volume 1 2014 (pp. 77-85). Springer, Cham.

Kaur G, Verma B. Measurement standards based grading of rice kernels by separating touching kernels for embedded imaging applications. International Journal of Electronics, Communication & Instrumentation Engineering Research and Development (IJECIERD). 2013 Mar;3(1):127-34.

Babaki A, Askari G, Emam-Djomeh Z. Drying behavior, diffusion modeling, and energy consumption optimization of Cuminum cyminum L. undergoing microwave-assisted fluidized bed drying. Drying Technology. 2020 Jan 2;38(1-2):224-34.

Ávila MM, Caballero D, Durán ML, Caro A, Pérez-Palacios T, Antequera T. Including 3D-textures in a computer vision system to analyze quality traits of loin. InInternational Conference on Computer Vision Systems 2015 Jul 6 (pp. 456-465). Springer, Cham.

Cimini A, Pallottino F, Menesatti P, Moresi M. A low-cost image analysis system to upgrade the rudin beer foam head retention meter. Food and bioprocess technology. 2016 Sep;9(9):1587-97.

Tan JY, Ker PJ, Lau KY, Hannan MA, Tang SG. Applications of photonics in agriculture sector: a review. Molecules. 2019 Jan;24(10):2025.

Satpute MR, Jagdale SM. Automatic fruit quality inspection system. In2016 International Conference on Inventive Computation Technologies (ICICT) 2016 Aug 26 (Vol. 1, pp. 1-4). IEEE.

Tripathi MK, Maktedar DD. A role of computer vision in fruits and vegetables among various horticulture products of agriculture fields: A survey. Information Processing in Agriculture. 2020 Jun 1;7(2):183-203.

Tripathi MK, Maktedar DD. A role of computer vision in fruits and vegetables among various horticulture products of agriculture fields: A survey. Information Processing in Agriculture. 2020 Jun 1;7(2):183-203.

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El-Mesery HS, Mao H, Abomohra AE. Applications of non-destructive technologies for agricultural and food products quality inspection. Sensors. 2019 Jan;19(4):846.

Momin MA, Rahman MT, Sultana MS, Igathinathane C, Ziauddin AT, Grift TE. Geometry-based mass grading of mango fruits using image processing. Information processing in agriculture. 2017 Jun 1;4(2):150-60.

Deshpande T, Sengupta S, Raghuvanshi KS. Grading & identification of disease in pomegranate leaf and fruit. International Journal of Computer Science and Information Technologies. 2014 Aug;5(3):4638-45.

Rady AM, Guyer DE. Rapid and/or nondestructive quality evaluation methods for potatoes: a review. Computers and Electronics in Agriculture. 2015 Sep 1;117:31-48.