Global Journal of Computer Science and Technology, G: Interdisciplinary, Volume 23 Issue 1

Applications of Emerging Smart Technologies in Farming Systems: A Review © 2023 Global Journals Global Journal of Computer Science and Technology Volume XXIII Issue I Version I 57 ( )G Year 2023 nutritional quality in depleted soils. ( CuffariBenedette 2021 ) Aside from these priorities, gene discovery using computer software has enabled researchers to develop targeted strategies for improving seed quality, introduce extra micronutrients into plants for improved human health, and engineer plants with phytoremediation capabilities. Some of the most widely used plant/crop bioinformatics online databases include BGI Rice Information System, Gateway of Brassica Genome, Chloroplast DB, The Crop Expressed Sequence Tag (CR-EST_ database, CyanBase, the European Molecular Biology Laboratory (EMBL) nucleotide sequence database, and many more (biotechgo.org ,Bulgaria) . Bioinformatics tools play a vital role in providing information about the genes found in the genomes of species. These technologies have also allowed researchers to predict the function of specific genes and the factors that influence them. For example, the information the tools provide about the genes enables scientists to develop drought, herbicide, and pesticide- resistant plant varieties. Similarly, specific genes can be altered to increase meat and milk production. Furthermore, their genes can be altered to make them disease resistant. Plants' genomes stayed conserved and did not supply much information when evolutionary changes occurred. It is now feasible to extract the needed information from the genome of certain plants thanks to bioinformatics techniques. There are two species of food plants, the genome of which has been entirely mapped, for example, Arabidopsis thaliana and Oryza sativa (CuffariBenedette 2021) . These two species of plants have their names in English as watercress and rice, respectively. Watercress is a tiny plant that grows on rocks. Because of its smaller genomic size, researchers took an interest in its genome and studied plant developmental processes. Its genome consists of 5 chromosomes on which 100 Mbp DNA is distributed. It reproduces in 5 weeks and makes a new generation. Therefore, knowledge of its genes and how they are expressed reveals information about the proteins and expressions of other plants. By adding the desired genes, many plants have become insect-resistant. For example, Bacillus thuringiensis is a bacterial species that improve soil fertility while protecting plants from pests. When the researchers sequenced its genome, they incorporated its genes into the plant to make it insect-resistant. Corn, cotton, and potatoes, for example, have all been insect- resistant in the past. When insects consume plants with bacterium genes in their genomes, the bacteria enter their circulation and starve them, eventually killing them. Bt corn is a type of food plant that the introduction of bacterial DNA has genetically modified. It works against insects by causing them to acquire resistance. The use of Bt genes in the plant's genome has made agriculturists use insecticides in minimal amounts. As a result, plants' productivity and nutritional value will also increase and benefit human health. When alterations are introduced to a plant's genome, the nutritional value of the plant rises as well. For example, some genes are added to the rice genome to boost the crop's Vitamin A levels. n) Soft Computing in Agricultural Soft computing refers to a collection of computational techniques that includes fuzzy logic (FL), artificial neural networks (ANN), and genetic algorithms (GA ). (JacekMZurada et al. 2017 ) Soft computing is advantageous in offering strategies for incorporating human-like ambiguity and real-world uncertainty into traditional computing algorithms. For instance, soft computing-based categ- orization, modelling, prediction, optimization, and control have been used to tackle problems in soil and water, crop management and post-harvesting, precision agriculture, food processing, food quality and safety, and agricultural vehicle and robotics. ( Lotfi A. Zadeh ). Agricultural production management is a challenge that includes determining the best sowing season, crop variety selection, land preparation, sowing method, fertilizer, and pest selection based on variety. There is a need for a more versatile fuzzy logic based expert system approach that provides the end user with a diverse range of farming approaches. (Expert-system- questions, 2018). Agricultural pest management used the color co-occurrence approach for textural analysis to see if classification algorithms could distinguish between sick and normal citrus leaves. i. Fuzzy Logic Fuzzy logic is very well-known for its application in developing an image capture/processing system for weed detection ( Dubey Sonal et al. 2013 ) and a fuzzy logic decision-making system for deciding where and how much herbicide to spray in a crop field. However, information on the economic thresholds of weed influence on crop productivity is difficult to adapt to a specific region or farm. (Ogunleye G O et.al 2018) Therefore, a fuzzy logic approach was used to convert image data into sprayer commands, allowing farmers to use their experience to classify weed status at a given location in the field this research indicated that a fuzzy logic system could understand and facilitates the representation and processing of human knowledge in a computer. A functional approach to soil characterization is used in the precision agricultural decision support system, which includes water stress, nitrate stress, nitrate leaching, and residual nitrogen content at harvest. First, a fuzzy c-means classifier was used to classify the soil profiles into functional groups. Next, the researcher investigated ways to use the nitrification inhibitor for management zone designation based on