Identification of durum wheat grains by using hybrid convolution neural network and deep features
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s11760-021-02094-y.pdf
Reference38 articles.
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2. Philipp, N., Weichert, H., Bohra, U., Weschke, W., Schulthess, A.W., Weber, H.: Grain number and grain yield distribution along the spike remain stable despite breeding for high yield in winter wheat. PLoS ONE 13(10), e0205452 (2018). https://doi.org/10.1371/journal.pone.0205452
3. Feng, F., et al.: Contribution of proximal and distal grains within spikelets in relation to yield and yield components in the winter wheat production region of china from 1948 to 2012. Agronomy 9(12), 850 (2019). https://doi.org/10.3390/agronomy9120850
4. Panozzo, A., Huang, H., Bernazeau, B., Vamerali, T., Samson, M.F., Desclaux, D.: Morphology, phenology, yield, and quality of durum wheat cultivated within organic olive orchards of the Mediterranean area. Agronomy 10(11), 1789 (2020). https://doi.org/10.3390/agronomy10111789
5. Ferrante, A., Cartelle, J., Savin, R., Slafer, G.A.: Yield determination, interplay between major components and yield stability in a traditional and a contemporary wheat across a wide range of environments. F. Crop. Res. 203, 114–127 (2017). https://doi.org/10.1016/j.fcr.2016.12.028
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