Managing Wheat From Space: Linking MODIS NDVI and Crop Models for Predicting Australian Dryland Wheat Biomass

Winter Pea: Promising New Crop for Washington's Dryland Wheat-Fallow Region

A 2-year tillage-based winter wheat (Triticum aestivum L.)-summer fallow (WW-SF) rotation has been practiced by the vast majority of farmers in the low-precipitation (<300 mm annual) rainfed cropping region of east-central Washington and north-central Oregon for 140 years. Until recently, alternative crops (i.e., those other than WW) so far tested have not been as economically viable or stable ...

Winter wheat area estimation from MODIS-EVI time series data using the Crop Proportion Phenology Index

The Model of Wheat Yield Forecast Based on Modis-ndvi ——a Case Study of Xinxiang

The yield estimation models on a regional scale are generally constrained by the lack of spatially distributed information on major environmental. The utilization of remote sensing data with various spatial and temporal resolutions can settle this problem. The NDVI, which retrieved from satellite remote sensing, was adopted to forecast winter wheat yields in this paper. There are two key steps ...

Seasonal mycorrhizal colonization of winter wheat and its effect on wheat growth under dryland field conditions

A field experiment was conducted to determine the seasonal patterns of arbuscular mycorrhiza (AM) in a dryland winter wheat (Triticum aestivum L.) system and to determine wheat growth and P uptake responses to inoculation with mycorrhizal fungus. Broadcast-incorporated treatments included (1) no inoculation with mycorrhizal fungus, with and without P fertilizer, and (2) mycorrhizal fungal inocu...

Application of Synthetic NDVI Time Series Blended from Landsat and MODIS Data for Grassland Biomass Estimation

Accurate monitoring of grassland biomass at high spatial and temporal resolutions is important for the effective utilization of grasslands in ecological and agricultural applications. However, current remote sensing data cannot simultaneously provide accurate monitoring of vegetation changes with fine temporal and spatial resolutions. We used a data-fusion approach, namely the spatial and tempo...