Remote sensing in studies of the growing season: a bibliometric analysis

M Siłuch, P Bartmiński, W Zgłobicki - Remote Sensing, 2022 - mdpi.com
Analyses of climate change based on point observations indicate an extension of the plant
growing season, which may have an impact on plant production and functioning of natural …

Simple model based on artificial neural network for early prediction and simulation winter rapeseed yield

G Niedbała - Journal of integrative agriculture, 2019 - Elsevier
The aim of the research was to create a prediction model for winter rapeseed yield. The
constructed model enabled to perform simulation on 30 June, in the current year …

Application of artificial neural networks for multi-criteria yield prediction of winter rapeseed

G Niedbała - Sustainability, 2019 - mdpi.com
The aim of the work was to produce three independent, multi-criteria models for the
prediction of winter rapeseed yield. Each of the models was constructed in such a way that …

Application of artificial neural networks for yield modeling of winter rapeseed based on combined quantitative and qualitative data

G Niedbała, M Piekutowska, J Weres, R Korzeniewicz… - Agronomy, 2019 - mdpi.com
Rapeseed is considered as one of the most important oilseed crops in the world. Vegetable
oil obtained from rapeseed is a valuable raw material for the food and energy industry as …

[PDF][PDF] Winter oilseed rape and winter wheat growth prediction using remote sensing methods.

JA Domínguez, J Kumhálová, P Novák - 2015 - researchgate.net
Remote sensing is often used for yield prediction as well as for crop monitoring. This paper
describes how Landsat satellite data can be used to derive a growth model calculated from …

Using artificial neural network in determining postharvest LIFE of kiwifruit

A Mohammadi Torkashvand, A Ahmadi… - Journal of the …, 2019 - Wiley Online Library
BACKGROUND Artificial intelligence systems have been employed for the development of
predictive models that estimate many agricultural processes. RESULTS In present study, the …

Estimation of kiwifruit yield by leaf nutrients concentration and artificial neural network

AM Torkashvand, A Ahmadipour… - The Journal of …, 2020 - cambridge.org
There is a fundamental concern regarding the prediction of kiwifruit yield based on the
concentration of nutrients in the leaf (2–3 months before fruits harvesting). For this purpose …

[PDF][PDF] Remote estimation of crop canopy parameters by statistical regression algorithms for winter rapeseed using Sentinel-2 multispectral images

D Ganeva, E Roumenina - Aerosp. Res. Bulg, 2018 - researchgate.net
Еstimation of crop canopy parameters is important task for remote sensing monitoring of
agriculture and constructing strategies for within-field management. The main objective of …

Applicability of parametric and nonparametric regression models for retrieval of crop canopy parameters for winter rapeseed and wheat crops using Sentinel-2 …

D Ganeva, E Roumenina, G Jelev… - … on Remote Sensing …, 2019 - spiedigitallibrary.org
Parametric and nonparametric regression methods have been proven to successfully
retrieve crop canopy parameters. However, once those models are calibrated for certain …

Prediction of chamomile essential oil yield (Matricaria chamomilla L.) by physicochemical characteristics of soil.

N Khakipour, AM Torkashvand… - Advances in …, 2023 - search.ebscohost.com
The purpose of this study was to predict the percentage and yield of chamomile essential
oils using the artificial neural network system based on some soil physicochemical …