A Comprehensive Review on Intelligent Techniques in Crop Pests and Diseases

Artificial intelligence (AI) has transformative potential in the agricultural sector, particularly in managing and preventing crop diseases and pest infestations. This review discusses the significance of early detection and precise diagnosis of various AI tools and techniques for disease identification, such as image processing, machine learning, and deep learning. It also addresses the challenges of AI implementation in agriculture, including data quality, costs, and ethical concerns. The analysis classifies the hurdles and AI offers benefits such as improved resource management, timely interventions, and enhanced productivity. Collaborative efforts are essential to harness AI's potential for sustainable and resilient agriculture

Genome organization of <i>Arthrobacter</i> phage Laroye, Cluster AL.

<p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0180517#pone.0180517.g005" target="_blank">Fig 5</a> for details.</p

Genome organization of <i>Arthrobacter</i> phage Gordon, Cluster AU.

<p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0180517#pone.0180517.g005" target="_blank">Fig 5</a> for details.</p

Nucleotide sequence comparison of <i>Arthrobacter</i> phages.

<p>Dot Plot of <i>Arthrobacter</i> phage genomes displayed using Gepard [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0180517#pone.0180517.ref035" target="_blank">35</a>]. Individual genome sequences were concatenated into a single file arranged such that related genomes were adjacent to each other. The assignment of clusters is shown along both the left and bottom.</p

Splitstree representation of <i>Arthrobacter</i> phages and average nucleotide comparisons of Cluster AO <i>Arthrobacter</i> phages.

<p>All <i>Arthrobacter</i> phage predicted proteins were assorted into 1052 phams according to shared amino acid sequence similarities. Each genome was then assigned a value reflecting the presence or absence of a pham member, and the genomes were compared and displayed using Splitstree [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0180517#pone.0180517.ref036" target="_blank">36</a>]. Cluster and subcluster assignments derived from the dot plot and ANI analyses are annotated. The scale bar indicates 0.001 substitutions/site.</p

Genome organization of <i>Arthrobacter</i> phage Amigo, Cluster AQ.

<p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0180517#pone.0180517.g005" target="_blank">Fig 5</a> for details.</p

Genome organization of <i>Arthrobacter</i> phage Jawnski, Cluster AO.

<p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0180517#pone.0180517.g005" target="_blank">Fig 5</a> for details.</p

Genome organization of <i>Arthrobacter</i> phage Korra, Cluster AK.

<p>The genome of <i>Arthrobacter</i> phage Korra is shown with predicted genes depicted as boxes either above (rightwards-expressed) or below (leftwards-expressed) the genome. Genes are colored according to the phamily designations using Phamerator and database Actinobacteriophage_692, with the phamily number shown above each gene with the number of phamily members in parentheses.</p

Endolysin domains.

<p>Endolysin domains.</p