173
Views
8
CrossRef citations to date
0
Altmetric
Original Articles

Predicting Eggplant Individual Fruit Weight Using an Artificial Neural Network

, &

References

  • Chen, H. and A.S. Kim. 2006. Prediction of permeate flux decline in cross-flow membrane filtration of colloidal suspension: a radial basis function neural network approach. Desalination 192:415–428.
  • Ekanayake, I., S. De Datta, and P. Steponkus. 1993. Effect of water deficit stress on diffusive resistance, transpiration, and spikelet desiccation of rice. Ann. Bot. 72:73–80.
  • Emamgholizadeh, S., M. Parsaeian, and M. Baradaran. 2015. Seed yield prediction of sesame using artificial neural network. Eur. J. Agron. 68:89–96.
  • Haykin, S. 2008. Neural computing. 2nd ed. Prentice Hall, Princeton, N.J.
  • Higgins, A., S.D. Prestwidge Di Tirling, and J. Yost. 2010. Forecasting maturity of green peas: an application of neural networks. Computers and Electronics in Agriculture 70:151–156.
  • Kumar, S.R. and T. Arumugam. 2013. Correlation and path coefficient analysis for some yield-related traits in F2 segregating population of eggplant. Intl. J. Veg. Sci. 19:334–341.
  • Nabavi-Pelesaraei, A., A. Sadeghzadeh, P. Mir Hossein, and H. Ghasemi Mobtaker. 2013. Energy flow modeling, economic and sensitivity analysis of eggplant production in Guilan Province of Iran. Intl. J. Agr. Crop Sci. 5:3006–3015.
  • Naroui Rad, M., M. Allahdoo, and H. Fanaei. 2010. Study of some yield traits relationship in melon germplasm gene bank of Iran by correlation and factor analysis. Iran. J. Hort. 8:27–32.
  • Naroui Rad, M.R., S. Koohkan, H.R. Fanaei, and M.R. Pahlavan Rad. 2015. Application of artificial neural networks to predict the final fruit weight and random forest to select important variables in native population of Melon (Cucumis melo L.). Sci. Hort. 181:108–112.
  • Nayak, B. and P.K. Nagre. 2013. Genetic variability and correlation studies in Brinjal (Solanum melongena L.). Intl. J. Appl. Biol. Pharm. Technol. 4:211–215.
  • Phonglosa, A., K. Bhattacharyya, K. Ray, J. Mandal, A. Pari, H. Banerjee, and A. Chattopadhyay. 2015. Integrated nutrient management for okra in an inceptisol of eastern India and yield modeling through artificial neural network. Sci. Hort. 187:1–9.
  • Shearer, S.A., J.A. Thomasson, T.G. Mueller, J.P. Fulton, S.F. Higgins, and S. Samson. 2000. Yield prediction using a neural network classifier trained using soil landscape features and soil fertility data. Proc. Annu. Intl. Mtg. Soft Computing Applications Group, 14 May 1999, Milwaukee, Wis.
  • Shinde, K.G., U.M. Birajdar, M.N. Bhalekar, and B.T. Patil. 2012. Correlation and path analysis in Eggplant (Solanum melongena L.). Veg. Sci. 39:108–110.
  • Snehal, D. and V. Sandeep. 2014. Agricultural crop yield prediction using artificial neural network approach. Intl. J. Innov. Res. Eng. 2:683–686.
  • Soares, J.D.R., M. Pasqual, W.S. Lacerda, S.O. Silva, and S.L.R. Donato. 2013. Utilization of artificial neural networks in the prediction of the bunches’ weight in banana plants. Sci. Hort. 155:24–29.
  • Solaimany-Aminabad, M., A. Maleki, and H. Mahdi. 2013. Application of artificial neural network (ANN) for the prediction of water treatment plant influent characteristics. J. Adv. Environ. Health Res. 1:1–12.
  • Vazquez-Cruz, M.A., S.N. Jimenez-Garcia, R. Luna-Rubio, L.M. Contreras-Medina, E. Vazquez-Barrios, E. Mercado-Silva, I. Torres-Pacheco, and R.G. Guevara-Gonzalez. 2013. Application of neural networks to estimate carotenoid content during ripening in tomato fruits (Solanum lycopersicum). Sci. Hort. 162:165–171.
  • Zaefizadeh, M., M. Khayatnezhad, and R. Gholamin. 2011. Comparison of multiplelinear regressions (MLR) and artificial neural network (ANN) in predicting theyield using its components in the hulless barley. Amer. Eur. J. Agr. Environ. Sci. 10:60–64.
  • Zhang, H., T. Song, K. Wang, G. Wang, H. Hu, and F. Zeng. 2012. Prediction of crude protein content in rice grain with canopy spectral reflectance. Plant Soil. Environ. 58:514–520.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.