JOURNAL OF AGRICULTURAL METEOROLOGY

Scope & Guideline

Exploring the Nexus of Weather and Agriculture.

Introduction

Delve into the academic richness of JOURNAL OF AGRICULTURAL METEOROLOGY with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageEnglish
ISSN0021-8588
PublisherSOC AGRICULTURAL METEOROLOGY JAPAN
Support Open AccessNo
CountryJapan
TypeJournal
Convergefrom 1943 to 1944, from 1948 to 2024
AbbreviationJ AGRIC METEOROL / J. Agric. Meteorol.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressC/O NISHIMURA TOSHADO CO LTD, 1-6-4 KAMIMACHI, KOCHI, 780-0901, JAPAN

Aims and Scopes

The JOURNAL OF AGRICULTURAL METEOROLOGY is dedicated to advancing the understanding of the interactions between agriculture and meteorological phenomena. It encompasses a wide range of research areas that contribute to improving agricultural practices and sustainability through meteorological insights.
  1. Impact of Climate on Agriculture:
    Research focusing on how various climatic factors, such as temperature and precipitation, affect agricultural productivity and crop yields.
  2. Mitigation of Agricultural Emissions:
    Studies aimed at understanding and reducing greenhouse gas emissions from agricultural practices, including methane and carbon dioxide.
  3. Crop Physiology and Adaptation:
    Investigations into how crops respond physiologically to environmental changes, including light, temperature, and atmospheric CO2 levels.
  4. Remote Sensing and Monitoring Techniques:
    Utilization of advanced technologies such as drones and satellite imagery for monitoring crop health, growth, and environmental impacts.
  5. Soil and Water Management:
    Research on soil health, moisture management, and the effects of various agricultural practices on soil and water resources.
  6. Ecosystem Services and Biodiversity:
    Exploration of how agricultural practices influence ecosystem services and biodiversity within agricultural landscapes.
The JOURNAL OF AGRICULTURAL METEOROLOGY is currently witnessing several emerging trends that highlight the evolving landscape of agricultural meteorology and its intersection with technology and climate change.
  1. Climate Change Adaptation Strategies:
    Increasing focus on developing and assessing strategies for agricultural adaptation to climate change, including crop diversification and resilient farming practices.
  2. Utilization of Machine Learning Techniques:
    Growing interest in applying machine learning and artificial intelligence to analyze agricultural data and improve predictive modeling for crop yields and environmental impacts.
  3. Sustainable Agricultural Practices:
    A rising trend towards research on sustainable practices, including organic farming and agroecology, emphasizing environmental stewardship and resource conservation.
  4. Integration of Remote Sensing Data:
    Enhanced incorporation of remote sensing technologies for monitoring and evaluating agricultural systems, leading to more precise and timely agricultural management.
  5. Research on Crop Resilience to Extreme Weather:
    Increased studies focusing on how crops can withstand extreme weather events, such as droughts and floods, highlighting the need for resilient agricultural systems.

Declining or Waning

While the JOURNAL OF AGRICULTURAL METEOROLOGY has seen numerous research themes, some areas are experiencing a decline in focus. This may reflect shifts in agricultural priorities or advancements in methodologies that render previous approaches less relevant.
  1. Historical Climate Assessments:
    There has been a noticeable decrease in publications focusing solely on historical climate assessments in agriculture, as more emphasis is placed on real-time data and predictive modeling.
  2. Traditional Pest Management Practices:
    Research on conventional pest management strategies appears to be waning, possibly due to a shift toward integrated pest management and sustainable farming practices.
  3. Static Modeling Approaches:
    The use of static models to predict agricultural outcomes is declining as dynamic, real-time modeling approaches gain traction, reflecting the need for more adaptable agricultural strategies.

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