Various researchers, agronomists, scientists, and engineers utilize a variety of technologies every year to boost agricultural productivity at a low cost, but this has a negative influence on the environment. Precision agriculture is the study of the use of technology to enhance agricultural operations in comparison to conventional agricultural methods and lessen negative environmental impacts. Precision agriculture depends heavily on remote sensing technology, and this technology's use in precision agriculture opens up new possibilities for raising agricultural standards. The global positioning system (GPS) enables the geographic Latitude and Longitude data of field data (slope, aspect, nutrients, and yield). Since it has the ability to continuously determine and record the right position, it can build a bigger database for the user. A geographic information system (GIS) that can handle and store these data is needed for further investigation. Despite agroforestry's limited spatial extent, isolation, and higher functional and structural complexity, recent advancements in geospatial technologies, as well as the free accessibility of spatial information and software, can provide additional insight into assessing tools, making the decisions, and developing policies. This review has covered the current uses of geospatial technology, along with their restrictions and limits, as well as prospective future uses for agroforestry. This review discusses GPS, GIS, and remote sensing technology and explains how they might be used in precision agriculture and agroforestry.
Remote sensing has played a vital role in advancement of agriculture and is effective technical method for agriculture crop management. It is a technology which acquisite information regarding objects on earth surface as well as atmosphere from a distance without being in contact with the object. Researchers have proved its high potential with accuracy in the field of agriculture. After various experiments, the qualitative and quantitative assessment of soil, crop and atmosphere demonstrated the better understanding between the crop and its management practices. The collected spatial and temporal data via various passive and active sensors has been utilized not only for morphological study but also for monitoring the vegetation moisture content. The paper reviews about the potential studies carried out to investigate the water content in plant to make use in irrigation management. Diverse spectral reflectance indices have been mentioned from which special emphasis on NDWI has been given. It is an index which is used in remote sensing to assess the crop water status and can be utilized in efficient operation of irrigation to improve water use efficiency (WUE) in agriculture. In order to make irrigation practices more efficient by making the lab restricted irrigation scheduling methods like IW:CPE method applicable in regular practice by using remote sensing. This paper firstly identifies areas where researches and techniques have real-world application. Next, it identifies actual issues that remote sensing could address and solve with further research and its related development. All opportunities for managing agricultural water resources effectively to be explored and made successful through precision agriculture. Using the fast, impartial and reliable information offered by remote sensing is a significant difficulty in the field of water resource management.
In recent years air pollution is one of the biggest problems in the world. Owing to the transboundary dispersion of contaminants around the world, air pollution has its own peculiarities. In a much planned urban setup industrial pollution takes a backseat and cooler admission takes the president's as the major cause of urban air pollution in the present investigation your pollution torrents index was calculated for various plant species growing around the Allahabad Highway. Five plants available commonly in all locations were selected for the present research namely Azadirachta indica (Neem), Delonix regia (Gulmohar), Saraca asoca (Ashok), Ficus benghalensis (Bargad), Ficus religiosa (Pepal). Using normal procedures, ascorbic acid, leaf extract pH, overall chlorophyll, relative water content and air quality tolerance index were analysed. Both plants tested in both areas have been shown to be pollution-sensitive, varying from 02.29 to 12.53. No pollution tolerant organisms studied were found. The maximum value of pH was 7.8 found in Neem tree spp. (Azadirachta indica) in Rewa Road (NH-35) and the minimum value of pH was 5.9 found in Gulmohar tree spp. (Delonix regia) in Varanasi Road (NH-19), The maximum value of RWC (89.99 %) found in Ashok tree spp. (Saraca asoca) and the minimum value of RWC (58.64 %) found in Neem tree spp. (Azadirachta indica) in Mirzapur Road site (NH-76). The maximum value of Total Chlorophyll Content was 1.55 mg/g found in Ashok tree spp. (Saraca asoca) in Mirzapur Road (NH-76) and the minimum value of Total Chlorophyll Content was 0.71 mg/g found in Bargad tree spp. (Ficus benghalensis) in Control Site and Rewa Road (NH-35). The maximum value of Ascorbic Acid (1.07 mg/g) found in Ashok tree spp. (Saraca asoca) in Rewa Road site (NH-35) and the minimum value of Ascorbic Acid (0.39 mg/g) found in Pepal tree spp. (Ficus religiosa) in Mirzapur Road site (NH-76) The variance may be due to alternative biochemical parameters being reflected. Plant can filter the air through aerial elements especially through their twigs stem leaves air pollution management is the better manage by the afforestation program. Air pollution tolerance index (APTI) is an intrinsic quality of tree to control air pollution problem which is currently of major concern of local urban locality. The trees having higher tolerance index rate or tolerant towards air pollution and can be used as a major component to reduce air pollution whereas the tree having less tolerance index can be an indicator to know the rate of air pollution. Hence, it is essential to protect the plants.
The experiment was carried out in a Pongamia pinnata-based agroforestry system to assess the impact of land use systems, sowing dates, and wheat varieties on wheat cultivation at the Forestry Research Farm, JNKVV, Jabalpur during the Rabi season of 2021-22 The experiment followed a three-factor double split plot design with two systems (open system and agroforestry system) as the main plot, three sowing dates (12th November, 27th November, and 12th December) as subplots, and two wheat varieties (MP-3336 and GW-322) as sub-sub plots. The results showed that the open system outperformed the agroforestry system in terms of plant population, plant height at harvest, grain yield, straw yield, biological yield, and harvest index. Early-sown wheat consistently showed better performance in most parameters compared to timely-sown and late-sown varieties. Among the wheat varieties, the MP-3336 variety exhibited higher plant population, while the GW-322 variety showed taller plants at harvest, longer spikes, higher grain yield, and better harvest index. These findings provide valuable insights into optimizing wheat cultivation in agroforestry systems and emphasize the importance of considering land use systems, sowing dates, and wheat varieties to maximize crop productivity.
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