Machine Learning-Based Rice Seed Quality Assessment: A Comprehensive Study
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-1488-9_40
Reference16 articles.
1. Ujoh F, Igbawua T, Ogidi Paul M (2019) Suitability mapping for rice cultivation in Benue State, Nigeria using satellite data. Geo-Spat Inf Sci 22(4):332–344. https://doi.org/10.1080/10095020.2019.1637075
2. Fukagawa NK, Ziska LH (2019) Rice: importance for global nutrition. J Nutr Sci Vitaminol 65(Supplement):S2–S3. https://doi.org/10.3177/jnsv.65.S2
3. Mohidem NA, Hashim N, Shamsudin R, Che Man H (2022) Rice for food security: revisiting its production, diversity, rice milling process and nutrient content. Agriculture 12(6):741. https://doi.org/10.3390/agriculture12060741
4. Vishwakarma C et al (2023) Bioengineering of canopy photosynthesis in rice for securing global food security: a critical review. Agronomy 13(2):489. https://doi.org/10.3390/agronomy13020489
5. Nabuuma D, Reimers C, Hoang KT, Stomph T, Swaans K, Raneri JE (2022) Impact of seed system interventions on food and nutrition security in low- and middle-income countries: a scoping review. Glob Food Secur 33:100638. https://doi.org/10.1016/j.gfs.2022.100638
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