Sustainable AI-Driven Applications for Plant Care and Treatment

Muhammad Naveed, Nafeesa Zahid, Ibtihaj Fatima, Ayesha Saleem, Muhammad Majeed, Amina Abid, Khushbakht Javed, Rehmana Wazir, Amina Qasim

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

8 Citations (Scopus)

Abstract

Technology has emerged as a formidable ally in the endeavor, with artificial intelligence (AI) leading the charge in revolutionizing farming practices via the notion of precision agriculture. Since the dawn of the civilization, there has always been a basic human need in the field of agriculture as plants were a primary source of food. The plant disease poses a serious threat to food security because it legitimately affects harvest yield, which reduces the growth of a crop yield and leads to significant loss and consequent financial losses. As a result, there is a demand for quick and effective plant disease detection and evaluation strategies. AI intervention in agriculture is assisting farmers in regaining their farming efficiency and reducing adverse environmental influences. By substituting traditional methods with more effective ones, it is bringing about a revolution in agriculture. Plant disease is one of the most important and critical challenges that affects the agriculture and its trading system. Plant diseases can adversely affect the growth of plants and, in severe cases, might lead to the plant death. AI-driven technologies have the capability not only to detect the disease but also to assess its toxicity and precisely classify the specific type of disease detected in a given plant sample. It investigates AI’s revolutionary role in improving farming practices through precision agriculture. Precision agriculture is based on data-driven decision-making. The importance of AI extends beyond data collection to data processing and interpretation. AI algorithms analyze the acquired data to uncover patterns, correlations, and anomalies that the human eye may not see.

Original languageEnglish
Title of host publicationMicroorganisms for Sustainability
PublisherSpringer
Pages235-258
Number of pages24
DOIs
Publication statusPublished - 2024
Externally publishedYes

Publication series

NameMicroorganisms for Sustainability
Volume47
ISSN (Print)2512-1898
ISSN (Electronic)2512-1901

Keywords

  • Artificial intelligence
  • Environmental influences
  • Plant diseases

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