Using Artificial Intelligence to Detect Psyllids in Citrus Research Paper

 

 

Sophisticated technology has developed across the world allowing industries to adopt cost-effective production methods that increase the profits realized at the end of each operating period. Industries globally have invested in research and development to come up with creative and innovative ways in which they can simplify the work done (Tang et al., 2021). Agriculturists have also found the methods to ensure crop production is at a high level; management of plant diseases is easy and resilient seeds that can survive different weather conditions in various parts of the world. Citrus farming is one of the most profitable activities globally with farmers producing raw materials to manufacture different products. Demand for citrus has increased over the years which motivates farmers to increase their yield every harvesting period. However, the dangerous psyllids have been a threat that discourages farmers from investing in the fruit due to the impact the disease has on the plant both in the short-term and in the long-term.

Psyllids are highly infectious since it has a high probability of being infected with greening, which then transmits and spreads the disease to citrus plants. According to Ampatzidis et al. (2019), greening has spread to more than 40 nations across the globe, affirming that other countries are at risk due to the trade activities and open boundaries. For instance, in Florida County, the production rate decreased by more than 70% between 2000 and 2017 (Ampatzidis et al., 2019). Farmers were mainly discouraged and affected by the tremendous losses resulting from greening after psyllids penetrated the region in 2005.

Background

Asian-based citrus psyllids are some of the smallest trees that produce fruit, but they affect global production due to their risk of getting the greening disease. Psyllids have been detected using the ‘tap sample method’ when they strike branches and affect the entire plant as well as its probability to increase in size. Local farmers from Florida reported cases of psyllids in their farms after electronic methods were used to detect the presence of the condition (Byrne et al., 2017). Automated systems were easier, faster, and more effective in collecting and analyzing the data from the machine vision. AI has been incorporated into the equipment used to capture trees’ images and insects that attack the citrus groves (Partel et al., 2019). The justification for using AI in the management of citrus diseases is that it has the comparative advantage of differentiating psyllids and other pests that attack the citrus groves and affect their growth rate.

The AI-enabled machine comprises a tapping mechanism that highlights some branches that have been pre-selected with a grid of cameras. After pictures have been taken and developed, the AI algorithm has the power and capacity to analyze images, and potential defects, and quantify the adult psyllids (Byrne et al., 2017). The justification for using AI-based systems is that they have a high accuracy rate with psyllids being detected and identified at a 90% precision level (Ampatzidis et al., 2019). Farmers’ use of digital systems in enhancing crop production which allows them to have high yields in the long term.

Each citrus grove that has a camera sends specific information about the psyllids attacking such a plant, with the data collected enhancing the development of maps. This means researchers and farmers are more informed and can apply or spray the right amount of pesticides on plants that have pests (Tang et al., 2021). Protection of the environment through agrochemical use and other associated expenses for the farmer is reduced by a large margin since only the right quantity of pesticide is applied. Harvest management and yield mapping systems are embraced in the farms which ensure that all plants that would generate incomes for the farmers have been incorporated. Sustainable methods that would support citrus farming would enhance the use of modernized techniques and technologies to identify the stress status of plants as well as crop health (Deng et al., 2020). Detecting early diseases and pests affects the yield produced at the end of each period. AI makes it easy to distinguish other deficiencies in the citrus fruits, recognizing the fact that other conditions may have similar symptoms, and if left untreated, may affect the production levels.

Details and Description

AI can play an important role in detecting psyllids in citrus framing in the management of citrus greening. AI is suitable for the management and detection of diseases since it is fast and easy as it uses technology to collect and analyze all relevant data. Ampatzidis et al. (2019) claimed that knowledge about the psyllid populace is crucial for all citrus growers as it allows them to make informed decisions on the best AI sy

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