Novedades en biblioteca: libros
01 Abr 2024 La inteligencia artificial: la revolución que cambiará todo Bogotá: Planeta, 2024. 200 p. Tabla de contenido NTC 5800: 2020. Sistema de gestión de la innovación. Terminología y
01 Abr 2024 La inteligencia artificial: la revolución que cambiará todo Bogotá: Planeta, 2024. 200 p. Tabla de contenido NTC 5800: 2020. Sistema de gestión de la innovación. Terminología y
17 Julio 2024 Agronomy Journal Vol. 116, No. 4, Jul – Aug 2024 Crop Science Vol. 64, No. 3, May – Jun 2024 Soil Science Society American Journal Vol. 88,
Generative AI and Its Impact on Sugarcane Industry: An Insight into Modern Agricultural Practices Ray, P.P. Sugar Tech |January 2024 Mobile Application Implementation as Agriculture 4.0 Strategy for Sugarcane Yield
A Mathematical Model to Minimize the Total Cultivation Cost of Sugarcane Kumar, S. & Pant, M. In: Soft Computing for Problem Solving| 2023 Operational cycle analysis of Colombian sugarcane harvest,
A Soil Physical Assessment Over Three Successive Burned and Unburned Sugarcane Annual Harvests Ortiz, P.F.S., et al Sugar Tech |25| 2023 Combined Chemical Fertilizers with Molasses Increase Soil Stable Organic
30 Sep 23 12 avo Congreso Latinoamericano ATALAC y El Caribe 18 al 20 Septiembre de 2023. San José, Costa Rica Tabla de contenido XXII ATACA – XV ATAGUA 2023
Chapter 6. Smart Irrigation and Cultivation Recommendation System for Precision Agriculture Driven by IoT Kumari, N.M.J., Thirupathi Rao, N. & Bhattacharyya, D. In: Machine Intelligence, Big Data Analytics, and IoT
Sugarcane (Saccharum officinarum L.) under saline stress: Growth, productivity, technological quality, and industrial yield Florentino de Morais, J.E., et al Industrial crops and products |188| November 2022 Detection of White
A review of UAV platforms, sensors, and applications for monitoring of sugarcane crops Amarasingam, N., et al Environment |26| April 2022 Improving sugarcane production in saline soils with Machine Learning
Improving sugarcane growth simulation by integrating multi-source observation into a crop model Yu, D., Zha, Y., Shi, L., Ye, H. & Zhang, Y. European Journal of Agronomy |132|January 2022 Machine
El uso de este sitio está sujeto a condiciones de uso expresas. Al utilizar este sitio, usted acepta las Cláusulas de confidencialidad y nuestra política de tratamiento de datos personales.