ABSTRACT
This study discusses carbon sequestration variability in different ecosystems of India. Four different biosphere regions, each over 0.5° × 0.5° area, have been selected considering the geospatial and climatic variability of these regions expanding from Central India (CI), the Northeast region (NER), the Western Ghats (WG), and the Western Himalayan region (WHNI). The climatic conditions of these four regions are different so are the biosphere constituents of these regions. We expect the Gross Primary Productivity (GPP) to enhance during the all India summer monsoon rainfall season but in varied magnitudes suggesting a role of climatic parameters and flora in these regions. The GPP from FLUXCOM for the duration of 2001 to 2019 (19 years) and satellite-derived vegetation indices like the Normalized Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Leaf Area Index (LAI) are used in this study to understand the response of regional vegetation to this variability. EVI seems to be better related to GPP in comparison to NDVI in the preliminary analysis. Further analysis suggests LAI correlates better to GPP than EVI and NDVI in different seasons in these four regions. Also, meteorological parameters like surface temperature, rainfall, soil water, and other derived parameters like Vapor Pressure Deficit (VPD) are studied. It is also observed that the year-to-year variability in the climatic conditions could also have a role to play in the observed features. It is proven that the climate around the world is experiencing changes. Vegetation is one of the potent markers to monitor the impact of climate change. These long-term data and trends were studied to understand if there is any significant impact of the changing climatic conditions on the vegetation in these regions. Our study shows that there is an increasing (positive) trend in GPP at these locations though at different rates. WG and WHNI have shown a significant high rate of increase (6.44 and 5.36 gCm-2 y-1, respectively) in GPP over the last two decades.
ABSTRACT
Crop geometry plays a vital role in ensuring proper plant growth and yield. Check row planting allows adequate space for weeding in both direction and allowing sunlight down to the bottom of the crop. Therefore, a light detection and ranging (LiDAR) navigated electronic seed metering system for check row planting of maize seeds was developed. The system is comprised of a LiDAR-based distance measurement unit, electronic seed metering mechanism and a wireless communication system. The electronic seed metering mechanism was evaluated in the laboratory for five different cell sizes (8.80, 9.73, 10.82, 11.90 and 12.83 mm) and linear cell speed (89.15, 99.46, 111.44, 123.41 and 133.72 mm·s-1). The research shows the optimised values for the cell size and linear speed of cell were found to be 11.90 mm and 99.46 mm·s-1 respectively. A light dependent resistor (LDR) and light emitting diode (LED)-based seed flow sensing system was developed to measure the lag time of seed flow from seed metering box to bottom of seed tube. The average lag time of seed fall was observed as 251.2 ± 5.39 ms at an optimised linear speed of cell of 99.46 mm·s-1 and forward speed of 2 km·h-1. This lag time was minimized by advancing the seed drop on the basis of forward speed of tractor, lag time and targeted position. A check row quality index (ICRQ) was developed to evaluate check row planter. While evaluating the developed system at different forward speeds (i.e., 2, 3 and 5 km·h-1), higher standard deviation (14.14%) of check row quality index was observed at forward speed of 5 km·h-1.
