Zobrazeno 1 - 10
of 702
pro vyhledávání: '"Yield forecasting"'
Autor:
Eatidal Amin, Luca Pipia, Santiago Belda, Gregor Perich, Lukas Valentin Graf, Helge Aasen, Shari Van Wittenberghe, José Moreno, Jochem Verrelst
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 126, Iss , Pp 103636- (2024)
Precise knowledge of cropland productivity is relevant for farmers to enable optimizing managing practices; particularly with the perspective of anticipating crop yield ahead of harvest. The current availability of high spatiotemporal resolution Sent
Externí odkaz:
https://doaj.org/article/a8bb85440b7f41fb9a8aa795e47f6f54
Autor:
Matthew Beddows, Georgios Leontidis
Publikováno v:
Agriculture, Vol 14, Iss 6, p 883 (2024)
The importance of forecasting crop yields in agriculture cannot be overstated. The effects of yield forecasting are observed in all the aspects of the supply chain from staffing to supplier demand, food waste, and other business decisions. However, t
Externí odkaz:
https://doaj.org/article/b12221ccd111495990d3e078a5476d08
Publikováno v:
Horticulturae, Vol 10, Iss 6, p 584 (2024)
The olive tree is one of the most common type of cultivation in the Mediterranean area, having high economic and social importance. The Alentejo region, Portugal, is an area with a high presence of olive groves, which in 2022 accounted for 201,474 he
Externí odkaz:
https://doaj.org/article/a9b0664d690c4c44bcacfc9c5f2045e4
Publikováno v:
Remote Sensing, Vol 16, Iss 9, p 1573 (2024)
Crop yield forecasting during an ongoing season is crucial to ensure food security and commodity markets. For this reason, here, a scalable approach to forecast corn yields at the field-level using machine learning and satellite imagery from Sentinel
Externí odkaz:
https://doaj.org/article/ec3af4e11f5a4f139fceb9c88a66142e
Autor:
Anna I. Pavlova
Publikováno v:
Siberian Journal of Life Sciences and Agriculture, Vol 15, Iss 3, Pp 139-154 (2023)
Due to the sharp changes in climatic conditions in Western Siberia, the most pressing problem is food security associated with forecasting crop yields. There is a need to estimate the natural wetness of the area on the basis of agroclimatic indicator
Externí odkaz:
https://doaj.org/article/99a71e279d174b7da55b527fb1694fa1
Autor:
Karam Alsafadi, Shuoben Bi, Hazem Ghassan Abdo, Hussein Almohamad, Basma Alatrach, Amit Kumar Srivastava, Motrih Al-Mutiry, Santanu Kumar Bal, M. A. Sarath Chandran, Safwan Mohammed
Publikováno v:
Geoscience Letters, Vol 10, Iss 1, Pp 1-21 (2023)
Abstract Due to rapid population growth and the limitation of land resources, the sustainability of agricultural ecosystems has attracted more attention all over the world. Human activities will alter the components of the atmosphere and lead to clim
Externí odkaz:
https://doaj.org/article/aa875cedd8c5409183da7cad65cfbd63
Publikováno v:
Proceedings of the International Conference on Applied Innovations in IT, Vol 11, Iss 1, Pp 89-95 (2023)
Ukraine was one of the main exporters of plant products. However, as a result of the aggression, the country's agriculture has suffered greatly, export volumes are decreasing, which may provoke a shortage of agricultural products on world markets. It
Externí odkaz:
https://doaj.org/article/450da0f9c9384cff893fec2be14b5580
Publikováno v:
IEEE Access, Vol 11, Pp 42578-42594 (2023)
Achieving food security has become a major challenge for society. Crop yield estimation is essential for crop monitoring to ensure food security. Manual crop yield estimation is cumbersome and inaccurate and becomes infeasible when scaled up. Machine
Externí odkaz:
https://doaj.org/article/0766b021dcc048bd8f6af45fe8f7c697
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 122, Iss , Pp 103434- (2023)
This study presents a comprehensive evaluation of seasonal, locational, and varietal variations in canopy reflectance responses in 315 commercial citrus blocks from three major growing regions in Australia. The dataset includes three different citrus
Externí odkaz:
https://doaj.org/article/f53962dcb37b4abaa31845804a4f3174
Publikováno v:
Journal of Natural Fibers, Vol 19, Iss 16, Pp 13725-13735 (2022)
The aim of this study was to determine the usefulness of artificial neural networks (ANN) in the process of forecasting the yield of hemp seeds (Cannabis sativa L.) of the Henola variety. The field experiments (various doses of mineral fertilization,
Externí odkaz:
https://doaj.org/article/e2a618b4cee249ad93bc6bac6c717a2d