[HTML][HTML] Using NDVI for the assessment of canopy cover in agricultural crops within modelling research
The fraction of green canopy cover (CC) is an important feature commonly used to
characterize crop growth and for calibration of crop and hydrological models. It is well …
characterize crop growth and for calibration of crop and hydrological models. It is well …
Using NDVI to differentiate wheat genotypes productivity under dryland and irrigated conditions
Crop breeders are looking for tools to facilitate the screening of genotypes in field trials.
Remote sensing-based indices such as normalized difference vegetative index (NDVI) are …
Remote sensing-based indices such as normalized difference vegetative index (NDVI) are …
[HTML][HTML] In silico curation of QTL-rich clusters and candidate gene identification for plant height of bread wheat
C Jia, X Lyu, T Yang, H Qin, Y Wang, Q Hao, W Liu… - The Crop Journal, 2023 - Elsevier
Many genetic loci for wheat plant height (PH) have been reported, and 26 dwarfing genes
have been catalogued. To identify major and stable genetic loci for PH, here we thoroughly …
have been catalogued. To identify major and stable genetic loci for PH, here we thoroughly …
Develo** and testing remote-sensing indices to represent within-field variation of wheat yields: Assessment of the variation explained by simple models
One important issue faced by wheat producers is temporal and spatial yield variation
management at a within-field scale. Vegetation indices derived from remote-sensing …
management at a within-field scale. Vegetation indices derived from remote-sensing …
GSP-AI: An AI-Powered Platform for Identifying Key Growth Stages and the Vegetative-to-Reproductive Transition in Wheat Using Trilateral Drone Imagery and …
Wheat (Triticum aestivum) is one of the most important staple crops worldwide. To ensure its
global supply, the timing and duration of its growth cycle needs to be closely monitored in …
global supply, the timing and duration of its growth cycle needs to be closely monitored in …
The study on the relationship between normalized difference vegetation index and fractional green canopy cover in five selected crops
Crop models are of great use and importance in modern agriculture. Most models imply
spatial vegetation indices, such as NDVI, or canopy cover characteristics, such as FGCC, to …
spatial vegetation indices, such as NDVI, or canopy cover characteristics, such as FGCC, to …
Using canopy measurements to predict soybean seed yield
PK Schmitz, HJ Kandel - Remote Sensing, 2021 - mdpi.com
Predicting soybean [Glycine max (L.) Merr.] seed yield is of interest for crop producers to
make important agronomic and economic decisions. Evaluating the soybean canopy across …
make important agronomic and economic decisions. Evaluating the soybean canopy across …
Development and validation of a model to combine NDVI and plant height for high-throughput phenoty** of herbage yield in a perennial ryegrass breeding program
Sensor-based phenoty** technologies may offer a non-destructive, high-throughput and
efficient assessment of herbage yield (HY) to replace current inefficient phenoty** …
efficient assessment of herbage yield (HY) to replace current inefficient phenoty** …
Improving in-season wheat yield prediction using remote sensing and additional agronomic traits as predictors
The development of accurate grain yield (GY) multivariate models using normalized
difference vegetation index (NDVI) assessments obtained from aerial vehicles and …
difference vegetation index (NDVI) assessments obtained from aerial vehicles and …
Are climate-dependent impacts of soil constraints on crop growth evident in remote-sensing data?
Soil constraints limit plant growth and grain yield in Australia's grain-crop** regions, with
the nature of the impact dependent on climate. In seasons with low in-crop (short for “during …
the nature of the impact dependent on climate. In seasons with low in-crop (short for “during …