Precision Farming (PF) management strategies are commonly based on estimations of within-field yield potential, often derived from remotely-sensed products, e.g., Vegetation Index (VI) maps. These well-established means, however, lack important information, like crop height. Combinations of VI-maps and detailed 3D Crop Surface Models (CSMs) enable advanced methods for crop yield prediction. Thi...

A pronounced residual effect of organic and inorganic fertilizers, applied in maize crop was observed on yields of maize-gobhi sarson cropping system. The experiment was conducted with 10 treatments of N, P, K, FYM, crop residue and zinc sulphate nutrients. The highest growth, yield and yield components of maize crop were recorded with 100% recommended fertilizer dose-RFD + ZnSO4 20 kg/ha and t...

Dynamic process-based crop simulation models are useful tool in predicting crop growth and yield in response to environmental and cultural factors but are constrained by lack of availability of the required large number of inputs when applied for regional studies. In this study we report (a) development of a prototype Crop Growth Monitoring System (CGMS) for wheat using WTGROWS simulation model...

Information on maximum grain yield and its attributes are limited for double-season rice crop grown under the subtropical environment. This study was conducted to examine key characteristics associated with high yielding double-season rice crop through a comparison between an integrated crop management (ICM) and farmers' practice (FP). Field experiments were conducted in the early and late seas...

Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) s...

Knowledge of spatial and temporal variations in crop growth is important for crop management and stable crop production for the food security of a country. A combination of crop growth models and remote sensing data is a useful method for monitoring crop growth status and estimating crop yield. The objective of this study was to use spectral-based biomass values generated from spectral indices ...

Official crop progress, condition and production estimates for the United States are responsibilities of the U.S. Department of Agriculture’s, National Agricultural Statistics Service (NASS). In addition to weekly and monthly survey-based data, biweekly composite maps of the normalized difference vegetation index (NDVI) from the NOAA AVHRR sensor (1 km resolution) are produced by NASS’s Researc...

Information on the outlook of yield and production of crops over large regions is essential for government services dealing with import and export of food crops, for agencies playing a role in food relief, for international organisations with a mandate in monitoring the world food production and trade, as well as for commodity traders. In Europe, such information is provided by the MARS (Monito...

A number of plant features and traits, such as overall plant architecture, leaf structure and morphological features, vascular architecture and flowering time are important determinants of photosynthetic efficiency and hence the overall performance of crop plants. The optimization of such developmental traits thus has great potential to increase biomass and crop yield. Here, we provide a compre...