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Applied Ecology and Environmental Sciences
Number of Followers: 29

This is an Open Access Journal

Open Access journal
ISSN (Print) 2328-3912 - ISSN (Online) 2328-3920
Published by Science and Education Publishing

[75 journals]

Markov Chain Model for Observing Changing Behaviours of Air Quality Index
- Authors: Sumithra P; Loganathan A, Deneshkumar V
  Pages: 498 - 502
  Abstract: The rising industrial revolution, urbanization and increasing human activities are the some of the primary reasons for increasing air pollution. Increasing air pollution adversely affects human health, agricultural production, wild animals. It is also an underlying cause for climate changes and these ultimately culminate in economic losses. Analysis of air quality index (AQI) can help to make recommendations to restrict outdoor air exposure and plan for demand on the healthcare system during periods of higher pollution. This study examines the stochastic behaviour of the AQI in Chennai city. Probabilities have been computed transitions among various states of AQI. Furthermore, steady state probability and mean first passage time have been evaluated.
  PubDate: 2022-08-01
  DOI: 10.12691/aees-10-8-1
  Issue No: Vol. 10, No. 8 (2022)
Assessment of Causal Relationship between Agricultural Productivity and
Food Availability at Circle Level (Cluster of Villages) in Junnar Tahsil
of Pune, Maharashtra
- Authors: Ashok Dushing; Ravindra Jaybhaye, Pravin Kokane
  Pages: 503 - 508
  Abstract: The most important indicator of the spatial pattern of agricultural development is agricultural productivity. It aids in identifying regions that are performing less or more efficiently than neighbouring regions and identifies the true cause of a region's agricultural backwardness. According to the physio-socio-economic condition of each region, it will be of great assistance in planning the sustainable development of each area. Population pressure on cultivable land is rapidly increasing, resulting in a rising demand for agricultural products. To solve the foodgrains problem, it is always a challenge to increase production per unit area and per unit of time. This paper attempts to assess the relationship between agricultural productivity and food availability at micro scale that is at cluster village (circle) as case study in Junnar. The Junnar Tahsil of the Pune District relies heavily on agriculture and is home to a variety of crops, necessitating agricultural planning for local food availability due to diversity in physical and socio-economic conditions of area. For 2019-20, the Shafis Calories Per Capita Index was utilised to evaluate productivity. In this study, the following ten crops were considered: rice, wheat, jowar, bajara, groundnut, soybean, gramme, sugarcane, onion, and tomato. Consideration was given to rice, wheat, jowar, and bajara for the production of cereal grains. Using geospatial techniques, a choropleth map has now been created. Analysis of the research revealed the spatial dimension of productivity in terms of regions with low, moderate, and high productivity. The trend in the medium and high productivity regions is toward a higher proportion of cash crops and a lower in foodgrains. Changes in cropping patterns are a result of the command area's irrigation facilities. On the basis of the findings, it has been concluded that area with high agriculture productivity of non-food crops are deficit in local food-grain availability and area of low agriculture productivity have high local food availability and this allows for more food diversity required for local food security.
  PubDate: 2022-08-05
  DOI: 10.12691/aees-10-8-2
  Issue No: Vol. 10, No. 8 (2022)
Intelligent Smart Agriculture Methane Crop Yields Detection and Prediction
for Machine Learning Techniques
- Authors: S. P. Ramesh; Dr. Muthusamy Periyasamy
  Pages: 509 - 518
  Abstract: The MEVM (methane energy value model) was created for several energy crops. Machine learning has been created with big data developments and better enrolling than make new open doors for data genuine science in the multi-disciplinary agri-business progresses territory. By applying machine learning to sensor data, farm the chief's frameworks are forming into ceaseless artificial intelligence engaged tasks that give rich recommendations and encounters to farmer decision help and action. IoT contraptions give data about the nature of developing fields and a short time later make a move dependent upon the farmer input. The arrangement endeavors to mastermind diverse possible unstructured associations of crude data, assembled from different kinds of IoT devices, united and advanced self-ruling style using the upside of model changes and model-driven designing to change data in a coordinated structure.
  PubDate: 2022-08-09
  DOI: 10.12691/aees-10-8-3
  Issue No: Vol. 10, No. 8 (2022)

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