Results 221 to 230 of about 6,379,441 (300)

Agronomic performance of the first ratoon of sugarcane under phosphorus supply from a mineral and an organic source. [PDF]

Sci Rep
Dos Santos EA, Soares FAL, Teixeira MB, da Silva EC, Morais WA, Pires WM, Vitorino LC, Bessa LA, Sousa AEC, Vale LSR.   +9 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Machine learning in the prediction of sugarcane production environments

Computers and Electronics in Agriculture, 2021
Sugarcane is one of the most important crops in the Brazilian agricultural market. Techniques that aim to increase the productivity and quality of raw materials, such as localized management, have been applied manually for many years by farmers and have ...
Gabriela Mourão Almeida, G. T. Pereira, Angélica Santos Rabelo de Souza Bahia, Kathleen Fernandes, J. M. Júnior   +4 more
semanticscholar   +1 more source

Energy-economic and life cycle assessment of sugarcane production in different tillage systems

, 2021
Sugarcane cultivation areas in the world are mostly done in light and medium texture as well as wet conditions. This study investigated energy, environmental and economic indicators for conventional and conservation tillage methods in sugarcane ...
Hakim Naseri, M. G. Parashkoohi, I. Ranjbar, D. M. Zamani   +3 more
semanticscholar   +1 more source

Sugarcane wastes as microbial feedstocks: A review of the biorefinery framework from resource recovery to production of value-added products.

Bioresource Technology, 2023
Sugarcane industry is a major agricultural sector capable of producing sugars with byproducts including straw, bagasse, and molasses. Sugarcane byproducts are no longer wastes since they can be converted into carbon-rich resources for biorefinery if ...
H. Lee, Yu Jung Sohn, Subeen Jeon, Hyoju Yang, J. Son., Yu Jin Kim, Si Jae Park   +6 more
semanticscholar   +1 more source

Combined life cycle assessment and artificial intelligence for prediction of output energy and environmental impacts of sugarcane production.

Science of the Total Environment, 2019
This study aims to employ two artificial intelligence (AI) methods, namely, artificial neural networks (ANNs) and adaptive neuro fuzzy inference system (ANFIS) model, for predicting life cycle environmental impacts and output energy of sugarcane ...
A. Kaab, Mohammad Sharifi, H. Mobli, Ashkan Nabavi‐Pelesaraei, K. Chau   +4 more
semanticscholar   +1 more source

Sugarcane production in the subtropics: Seasonal changes in soil properties and crop yield in no-tillage, inverting and minimum tillage

, 2020
Sugarcane is one of the important energy crops grown globally. Despite the increased sugarcane productivity, the mechanization of sugarcane production has caused the modification of soil structure in different scales.
G. O. Awe, J. M. Reichert, E. Fontanela
semanticscholar   +1 more source