Sorghum yield modelling based on crop growth parameters determined from visible and near-IR channel NOAA AVHRR data

1993 ◽  
Vol 14 (5) ◽  
pp. 895-905 ◽  
Author(s):  
M. B. POTDAR
Agriculture ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 658
Author(s):  
Subin Mattara Chalill ◽  
Snehaunshu Chowdhury ◽  
Ramanujam Karthikeyan

Controlled crop growth parameters, such as average air velocity, air temperature, and relative humidity (RH), inside the greenhouse are necessary prerequisites for commercial greenhouse operation. Frequent overshoots of such parameters are noticed in the Middle East. Traditional heating ventilation and air-conditioning (HVAC) systems in such greenhouses use axial fans and evaporative cooling pads to control the temperature. Such systems fail to respond to the extreme heat load variations during the day. In this study, we present the design and implementation of a single span, commercial greenhouse using box type evaporative coolers (BTEC) as the backbone of the HVAC system. The HVAC system is run by a fully-automated real time feedback-based climate management system (CMS). A full-scale, steady state computational fluid dynamics (CFD) simulation of the greenhouse is carried out assuming peak summer outdoor conditions. A pilot study is conducted to experimentally monitor the environmental parameters in the greenhouse over a 20-h period. The recorded data confirm that the crop growth parameters lie within their required ranges, indicating a successful design and implementation phase of the commercial greenhouse on a pilot scale.


2006 ◽  
Vol 72 (2) ◽  
pp. 139-150 ◽  
Author(s):  
Peng Gong ◽  
Ruiliang Pu ◽  
Zhanqing Li ◽  
James Scarborough ◽  
Nicolas Clinton ◽  
...  

2000 ◽  
Author(s):  
Changyao Wang ◽  
Qingyuan Zhang ◽  
Zheng Niu ◽  
Xiuwang Cheng
Keyword(s):  

2021 ◽  
Author(s):  
Bingyu Zhao ◽  
Meiling Liu ◽  
Jiianjun Wu ◽  
Xiangnan Liu ◽  
Mengxue Liu ◽  
...  

<p>It is very important to obtain regional crop growth conditions efficiently and accurately in the agricultural field. The data assimilation between crop growth model and remote sensing data is a widely used method for obtaining vegetation growth information. This study aims to present a parallel method based on graphic processing unit (GPU) to improve the efficiency of the assimilation between RS data and crop growth model to estimate rice growth parameters. Remote sensing data, Landsat and HJ-1 images were collected and the World Food Studies (WOFOST) crop growth model which has a strong flexibility was employed. To acquire continuous regional crop parameters in temporal-spatial scale, particle swarm optimization (PSO) data assimilation method was used to combine remote sensing images and WOFOST and this process is accompanied by a parallel method based on the Compute Unified Device Architecture (CUDA) platform of NVIDIA GPU. With these methods, we obtained daily rice growth parameters of Zhuzhou City, Hunan, China and compared the efficiency and precision of parallel method and non-parallel method. Results showed that the parallel program has a remarkable speedup (reaching 240 times) compared with the non-parallel program with a similar accuracy. This study indicated that the parallel implementation based on GPU was successful in improving the efficiency of the assimilation between RS data and the WOFOST model and was conducive to obtaining regional crop growth conditions efficiently and accurately.</p>


2000 ◽  
Vol 26 (7) ◽  
pp. 1177-1185 ◽  
Author(s):  
R.A. Seiler ◽  
F. Kogan ◽  
Guo Wei

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