Evaluation of dynamic simulation model for wheat genotypes under diverse environments in India

Performance of dynamic crop growth simulation model (CERES -Wheat v3.5) has been evaluated for various wheat genotypes in wheat growing regions of India. The genetic coefficients were developed and sensitivity analysis was carried out for the genotypes under study. The simulated phenology and yield were found in agreement with observed ones suggesting that calibrated model may be operationally used with routinely observed soil, crop and weather parameters.

Optimal Magnetic Graphite Heater Design for Impurity Control in Single-Crystal Si Grower Using Crystal Growth Simulation

In this paper, we report a successfully modified single-crystal Si growth furnace for impurity control. Four types of arbitrary magnetic heater (AMGH) systems with 3, 4, 5, and poly parts were designed in a coil shape and analyzed using crystal growth simulation. The concentration of oxygen impurities in single-crystal Si ingots was compared among the designed AMGHs and a normal graphite heater (NGH). The designed AMGHs were confirmed to be able to control turbulence and convection in a molten state, which created a vortex that influenced the oxygen direction near the melt–crystal interface. It was confirmed that replacing NGH with AMGHs resulted in a reduction in the average oxygen concentration at the Si melt–crystal interface by approximately 4.8%.

A Complete Environmental Intelligence System for LiDAR-Based Vegetation Management in Power-Line Corridors

This paper presents the first complete approach to achieving environmental intelligence support in the management of vegetation within electrical power transmission corridors. Contrary to the related studies that focused on the mapping of power lines, together with encroaching vegetation risk assessment, we realised predictive analytics with vegetation growth simulation. This was achieved by following the JDL/DFIG data fusion model for complementary feature extraction from Light Detection and Ranging (LiDAR) derived data products and auxiliary thematic maps that feed an ensemble regression model. The results indicate that improved vegetation growth prediction accuracy is obtained by segmenting training samples according to their contextual similarities that relate to their ecological niches. Furthermore, efficient situation assessment was then performed using a rasterised parametrically defined funnel-shaped volumetric filter. In this way, RMSE≈ 1 m was measured when considering tree growth simulation, while a 0.37 m error was estimated in encroaching vegetation detection, demonstrating significant improvements over the field observations.

Rice phenology and growth simulation using CERES-Rice model under the agro-climate of upper Brahmaputra valley of Assam

Crop growth simulation models, properly validated against experimental data have the potential for facilitating strategic decision making in agriculture. Such validated models can also make use of the information generated for site specific experiments and trials to other sites and for different time durations. For proper calibration and evaluation of crop simulation models, there is a need for collection of a comprehensive minimum set of data on soil, weather and crop management in all agronomic experiments. Keeping this in view, data from seven field experiments conducted at Jorhat (26° 47' N, 94°12' E; 87 m amsl) during 1998-2005 for long duration rice cultivar Ranjit grown under rainfed conditions were collected. Genetic coefficients required for running the CERES-Rice v4.5 model were derived and the performance of the model under the climate of upper Brahmaputra valley was evaluated. These results indicate that the CERES Rice v4.5 model is capable of estimating growth stages and grain yield of rice cultivar Ranjit in the climatic conditions of upper Brahmaputra valley with reasonable accuracy. Hence, the model have the potential for its use as a tool in making various strategic and tactical decisions related to agricultural planning in the state.