PRECISION AGRICULTURE SUING AMOSEL TO DETECT DISEASE IN TOMATOES
CHAPTER ONE
Background of the study
Tomatoes are erect with short stems or vine-like with long, spreading stems. The stems are covered in coarse hairs and the leaves are arranged spirally. The tomato plant produces yellow flowers, which can develop into a cyme of 3–12, and usually a round fruit (berry) which is fleshy, smoothed skinned and can be red, pink, purple, brown, orange or yellow in color. Tomato (Solanum lycopersicum L.) belongs to the Solanaceae family just like eggplant, pepper, potato. It is one of the most consumed foods because of its high content in nutrients such as vitamins and minerals that are important for human well-balanced diets. Moreover, tomato is an essential dietary component; it contains a high level of lycopene, an antioxidant which might reduce the risks associated with several types of cancer (Srinivasan, 2010).
The agricultural sector remains a key contributor to the uganda economy, representing about 15% of gross domestic product (GDP). Disease attacks are constant threats to agriculture and cause heavy losses in the country’s economy. Therefore, early detection can mitigate the severity of diseases and protect crops. However, manual disease identification is both time-consuming and error prone, and requires a thorough knowledge of plant pathogens. Instead, automated methods save both time and effort (Mpiima et al., 2019).
Since the Industrial Revolution, agriculture practices in developed countries have tended to support greater energy inputs using large machineries and increased applications of chemicals and fertilizers, while these practices have been used for producing food for human consumption in the last 7 decades the information technology system is changing the way agriculture is practiced. Agricultural Internet of things (IoT) refers to a network in which physical components, such as animals and plants, environmental elements, production tools, and various virtual “objects” in the agricultural system, are connected with the internet through agricultural information perception equipment under certain protocols to perform information exchange and communication. It intends to realize the intelligent identification, positioning, tracking, monitoring, and management of agricultural objects and processes.
Across the globe, Precision Agriculture (PA) is changing the way people farm as it offers a myriad of potential benefits in profitability, productivity, sustainability, crop quality, environmental protection, on-farm quality of life, food safety and rural economic development. PA is an innovative, integrated and internationally standardized approach aiming to increase the efficiency of resource use and to reduce the uncertainty of decisions required to manage variability on farms. PA has been hailed as one of the most scientific and modern approaches to production agriculture in the 21st century, as it epitomizes a better balance between reliance on traditional knowledge and information and management-intensive technologies (Mpiima et al., 2019).
At present, there is an increasing commitment to reduce reliance on excessive chemical inputs in agriculture. Numerous technologies have been applied to make agricultural products safer and to lower their adverse impacts on the environment, a goal that is consistent with sustainable agriculture. PA has emerged as a valuable component of the framework to achieve this goal (Tellaeche et al., 2008).
PA is an integrated, information- and production-based farming system that is designed to increase long term, site-specific and whole farm production efficiency, productivity and profitability while avoiding the undesirable effects of excess chemical loading to the environment or productivity loss due to insufficient input application (Kizza et al., 2016).
Worldwide, investments in research and technology development on PA have considerably increased during the past decade (Schellberg et al., 2008). The importance of PA has been widely recognized as a key contributor in crop production technology around the globe, but so far, this technology is only becoming practicable on large farms. PA is based on innovative systems approach and these new systems approach depends on a combination of fundamental technologies such as Geographic Information System (GIS), Global Positioning System (GPS), computer modeling, ground based/airborne/satellite remote sensing, variable rate technology and advanced information processing for timely in-season and between season crop management.
In Uganda, 40,124 tons of tomato are produced from 6,671 hectares. The crop is mainly grown by smallholder farmers who sell the fresh fruits in regional and domestic markets in their localities to generate income. It is also a reliable source of food security and employment for on- and off-farm. As such, it is regarded as an economic crop for rural and peri-urban farmers. In Uganda, tomato is consumed by about 3 million households in their most meals due to their nutrition value. It can be processed and combined in many different dishes and eaten in different ways, such as tinned paste, fresh vegetable, tomato juice, sauce, or soup. Tomato is known for its nutritive value; it is rich in vitamin C and contains lycopene, a very vital antioxidant which prevents cancers (Moodley, Gubba, & Mafongoya,2019).
In the recent past, there has been a decline in supply of tomatoes within the domestic market has provided an opportunity for smallholder farmers to engage in tomato farming, which has led to 14.8% increase in production. The increase is attributed to conversion of new areas for tomato production rather than increment in yield per unit area. Hence, tomato yields per unit area remain as low as 4 t ha-1 compared to potential yield of 16 t ha-1 for the East African region. However, over the last few years tomato production in Uganda has intensified with the introduction of high yielding varieties such as Asilla F1 and Tengeru97; however, yields continue to be low at 6 t ha-1 compared to potential yield of 16 t ha-1 for the East African region (Ramathani, 2021).
The low tomato yield is mainly attributed to biotic and abiotic factors. Biotic factors of notable economic importance in tomato production comprises of pests and diseases. Bacteria wilt (Ralstonia solanacearum Smith), tomato yellow leaf curl virus disease, early and late blight (Alternaria solani and Phytopthora infestans) are key among the diseases. The infections caused by tomato diseases result in yield losses and jeopardize incomes and livelihoods of growers and other beneficiaries along the crop value chain. On the other hand, key pests known to limit tomato production like invasive leaf miner, mites and thrips also contribute to considerable loss in yield and quality. Additional limitations to tomato production include lack of improved varieties, and poor agronomic practices. Sanitation is practised by some farmers, but only in association with fungicides, to control late blight. Plant nutrition is not perceived as playing a major role in late blight management. Problems associated with pesticides and poor marketability were identified as major constraints to tomato production in Uganda.
Tomato production is an important part of Uganda’s economy, as well as a food source for its people. However, Uganda’s rainy season makes tomato plants very susceptible to diseases and pests. For the home gardener in Uganda, growing tomatoes is a challenge best met with planning and careful maintenance. Manual identification of crop diseases is both fastidious and inaccurate, meaning it is only feasible in small farms. In contrast, automatic disease detection is significantly more accurate and takes less time and labor
Statement of the problem
Tomato is an important cash crop for commercial and small-scale farmers in Uganda. Insects cause severe crop losses by directly feeding on the plants, and by transmitting viruses which cause plant disease. Currently Ugandan Farmers reported caterpillars followed by thrips (Frankliniellspp), worms and white flies (Bemisia argentifolii) as the major pests of tomato. Some of the pests like Aphids (Aphidoidea spp) and worms (Lepidoptera spp) had been earlier reported as major tomato pests in Uganda., The other pests such as moth, spider mites (Tetrancychus urticae), leaf hoppers (Epoasca fabae), despite the pest which are known to cause damage to Tomato they high demand in the recent past, the short supply in tomato within the domestic market has provided an opportunity for smallholder farmers to engage in tomato farming, which has led to 14.8% increase in production. The increase is attributed to conversion of new areas for tomato production rather than increment in yield per unit area. Hence, tomato yields per unit area remain as low as 4 t ha-1 compared to potential yield of 16 tha-1 for the East African region. However, over the last few years tomato production in Uganda has intensified with the introduction of high yielding varieties such as Asilla F1 and Tengeru97; however, yields continue to be low at 6 t ha-1 compared to potential yield of 16 t ha-1 for the East African region. Though there has been increase on the government investment in agriculture by specifically providing sprays for pests and disease most of the tomatoes get destroyed by pests as a result Uganda Framers loose about more that 20% of their earning to pests to the low tomato yield is mainly attributed to biotic and abiotic factors, Bacteria wilt (Ralstonia solanacearum Smith), tomato yellow leaf curl virus disease, early and late blight (Alternaria solani and Phytopthora infestans) are key among the diseases. The infections caused by tomato diseases result in yield losses and jeopardize incomes and livelihoods of growers and other beneficiaries along the crop value chain. It is against this Background that this study intends to precision agriculture using amodel to detect disease in tomatoes.
Objectives of the study
- To examine the different classification of tomatoes disease and their symptoms
- To Apply IoT in the Field of Tomato Disease Recognition and detection
- To examine the Applications of IoT and data analytics as smart system in agriculture
- To statistically analyze the most common disease affecting Tomatoes
Research Questions
- What is the different classification of tomatoes disease and their symptoms?
- To what can Application of IoT in the Field of Tomato Disease Recognition and detection
- What are the Applications of IoT and data analytics as smart system in agriculture?
- What is statistical analyze of the most common disease affecting Tomatoes
Scope of the study
This section includes; content scope, time scope and Geographical scope.
Content scope
The study content will include; the different classification of tomatoes disease and their symptoms, Apply IoT in the Field of Tomato Disease Recognition and detection, the Applications of IoT and data analytics as smart system in agriculture and to statistically analyze the most common disease affecting Tomatoes
Time scope
The study will be carried out in the period of
Geographical scope
The study will be carried out in Sironko district Tomato plantations.
CHAPTER TWO
LITERATURE REVIEW
2.1 To examine the different classification of tomatoes disease and their symptoms
One of the main factors limiting tomato output is disease. Two categories can be used to classify diseases. The first category includes illnesses brought on by infectious microorganisms such nematodes, bacteria, viruses, and fungus. These illnesses can spread from plant to plant in a field, frequently quite quickly when the atmosphere is conducive. They are infectious. The second category consists of injuries brought on by physical or chemical causes that are not contagious, such as harmful environmental conditions, dietary or physiological issues, and herbicide damage. Non-infectious illnesses cannot transmit from plant to plant, but if a whole planting is exposed to the risk factor, the disease’s distribution may be fairly uniform and widespread (Anamika et al., 2011).
leaf spot from septoria the most prevalent foliar disease of tomatoes is septoria leaf spot, which is brought on by the fungus Septoria lycopersici. It starts out as little, wet patches that quickly become into 1/8-inch-diameter circular areas the most recognizable sign of Septoria leaf is the light-colored cores of dots (Garg,Cheema, & Dhatt, 2008). Wilt diseases are caused by pathogens that invade the vascular system (xylem tissue) and disrupt water flow through the plant. Fusarium wilt is the major wilt disease of tomato in Oklahoma. Verticillium wilt is easily confused with Fusarium wilt, but has not yet been reported in Oklahoma. The first symptom is usually a yellowing of the lower leaves, which gradually wilt and die. Symptoms may first occur on only one side of the plant. The disease progresses up the stem until all of the foliage is killed and the plant dies. If stems or petioles from wilted areas of diseased plants are
Early blight is a common leaf-spotting fungal disease of tomato. Extensive defoliation from early blight exposes fruit to sunscald and increases fruit rot. Early blight also attacks stems and fruit. Foliar diseases are most severe in eastern Oklahoma where rainfall and relative humidity levels support disease development, or wherever sprinkler irrigation is used (Majumdar, Meena, & Baghel,2010).
2.2 Apply IoT in the Field of Tomato Disease Recognition and detection
Numerous agronomic applications employ wireless sensor networks, such as remote environmental and soil condition monitoring to forecast crop health. By using WSN as an observer of environmental parameters such pressure, humidity, temperature, soil moisture, soil salinity, and soil conductivity, irrigation schedules for agricultural areas may be predicted (Olaniyi et al., 2010).)
The key contributions of several scholars are covered, and there has been a lot of work done in the literature, the scalable network design was suggested by writers to monitor and manage agricultural fields in rural regions. They suggested an IoT-based control system for the advancement of farming and agriculture (Muriithi, Bett, & Ogaleh,2009). The solution of routing and MAC in IoT achieved energy efficiency, less delay and high throughput.To achieve this performance the system combines Wi-Fi based long distance (WiLD) network and fog computing solution. In Bhargava et al. (2014) authors have proposed WSN framework design, intentionally to setup a DSS for the detection of Apple Scab in Himachal Pradesh using Mills tables.
A survey on the tomato late blight situation and current practices for disease management was carried out in Uganda using an informal structured questionnaire approach. Ten districts from different agroclimatic zones were selected for the survey. Phytophthora infestans isolates from tomatoes were obtained from the zones and only the A1 mating type was recovered. Tomato cultivation is practised year-round. The major commercial varieties grown, Moneymaker, Marglobe, Heinz and Roma, were susceptible to late blight
2.3 Applications of IoT and data analytics as smart system
Climate-smart agriculture is a holistic concept. It unites numerous issues related to agricultural development and other global development objectives. It covers environmental issues, for example energy and water, as well as social issues, such as gender, and economic issues. Achieving the four dimensions of food security (availability and access to of food, utilization of food for adequate nutrition, and stability of food supply) needs to be the overall goal of food production and distribution systems in developing countries. Multiple components contribute to food security, and adapting food systems to climate change involves a diversity of approaches and resources (Patel, & Sayyed, 2014).
Poor farmers’ livelihoods are being severely impacted by low yield and significant loss. The farmer’s cash flow and short-term capacity to react to market movements are strongly impacted by the scant yield. It eventually limits the farmer’s capacity to make investments in the farm’s future in order to increase productivity and lower crop-related risks through the use of inputs including seeds, fertilizer, crop insurance, market and weather data, and animal health care, (Kumar et al., 2013).
CHAPTER THREE
METHODOLOGY
3.1 Research Design:
The study shall use experimental and also quantitative research design. Experimental research design will be used in examining the Applications of IoT and data analytics as smart system in agriculture, Applying IoT in the Field of Tomato Disease Recognition and detection and examining the different classification of tomatoes disease and their symptoms, while secondary data will be used in statistically analyze the most common disease affecting Tomatoes.
3.2 Data Sources.
Secondary data will be obtained from the data base, records, publications and journals in the ministry of Agriculture.
3.3 Data processing and Data analysis techniques. The process of data processing will involve editing in order to check for errors and omissions and coding to reduce the data to a meaningful pattern of responses. Soft wares will be employed in the tabulation and processing of the findings will be done in order to prepare data, analyze and compile a research report.
The study will use Information technology in detecting disease in Tomatoes, while descriptive statistics will be used to describe the information got from the field this will be inform of graphs and tables when analyzing the most common diseases affecting Tomatoes.
Data Analysis will involve applying statistical techniques on it for easy presentation. It will include the interpretation of research findings in the light of the research questions, and objectives to determine if the results are consistent with those research questions.
3.3.1 Applying IoT in the Field of Tomato Disease Recognition and detection
IoT/sensor nodes are playing a key role in precision agriculture to collect the real time data (Sri et al., 2019). These nodes have the capability to make the system more practical by collecting the real time data from the crop fields to make the agriculture system precise. By incorporating data analytics and machine learning the agriculture system becomes more workable. All these technologies have tremendous applications in other fields.
The first phase it consists of the number of sensors/ IoT nodes to monitor physical or environmental conditions, soil conditions, plant conditions, e.g the soil moisture sensor records.
In establishing of the system to recognize and detect any Tomatoes.
The following system will be used in designing a systems
Soil selection and planning
- Wireless sensor
- router
- public cloud
- central data base
- computer
3.3.2 Statistically analyze the most common disease affecting Tomatoes
The process of data processing will involve editing in order to check for errors and omissions and coding to reduce the data to a meaningful pattern of responses. Model specification and soft wares employed in the tabulation and processing of the findings will be done in order to prepare data, analyze and compile a research report. The Stata will be used in analyzing the disease affecting the tomatoes.
Ethical considerations: The researcher will begin the study by explaining the purpose of the research, which basically means to help decision makers of ministry of Agriculture, sironko district officials and Makerere university academic department to give permission to the researcher to carry out the study.
REFERENCES
Muriithi, A. G., Bett, E., & Ogaleh, S. A. (2009, October). Information technology for agriculture and rural development in Africa: Experiences from Kenya. In Conference on international research on food security, natural resource management and rural development (pp. 6-8).
Patel, S., & Sayyed, I. U. (2014). Impact of information technology in agriculture sector. International Journal of Food, Agriculture and Veterinary Sciences, 4(2), 17-22.
Kumar, R., Srivastava, K., Singh, N. P., Vasistha, N. K., Singh, R. K., & Singh, M. K. (2013). Combining ability analysis for yield and quality traits in tomato (Solanum lycopersicum L.). Journal of Agricultural Science, 5(2), 213.
Anamika, Simon, S., Singh, K. P., & Ghosh, G. (2011). Distribution of root-knot nematode on major field crops in Uttar Pradesh (India). Archives of Phytopathology and Plant Protection, 44(2), 191-197.
Garg, N., Cheema, D. S., & Dhatt, A. S. (2008). Genetics of yield, quality and shelf life characteristics in tomato under normal and late planting conditions. Euphytica, 159(1), 275-288.
Majumdar, S. P., Meena, R. L., & Baghel, G. D. S. (2010). Effect of levels of compaction and potassium on yield and quality of tomato and chilli crops grown on highly permeable soils. Journal of the Indian Society of Soil Science, 48(2), 215-220.
Olaniyi, J. O., Akanbi, W. B., Adejumo, T. A., & Akande, O. G. (2010). Growth, fruit yield and nutritional quality of tomato varieties. African Journal of Food Science, 4(6), 398-402.
Muriithi, A. G., Bett, E., & Ogaleh, S. A. (2009, October). Information technology for agriculture and rural development in Africa: Experiences from Kenya. In Conference on international research on food security, natural resource management and rural development (pp. 6-8).
Mpiima, D. M., Manyire, H., Kabonesa, C., & Espiling, M. (2019). Gender analysis of agricultural extension policies in Uganda: informing practice?. Gender, technology and development, 23(2), 187-205.
Tellaeche, A., BurgosArtizzu, X. P., Pajares, G., Ribeiro, A., & Fernández-Quintanilla, C. (2008). A new vision-based approach to differential spraying in precision agriculture. computers and electronics in agriculture, 60(2), 144-155.
Moodley, V., Gubba, A., & Mafongoya, P. L. (2019). A survey of whitefly-transmitted viruses on tomato crops in South Africa. Crop Protection, 123, 21-29.
Ramathani, I. (2021). Practices and constraints of tomato production among smallholder farmers in uganda. African Journal of Food, Agriculture, Nutrition & Development, 21(2).
Kizza, T., Fungo, B., Kabanyoro, R., & Nagayi, R. (2016). Effect of Drip Irrigation Regimes on the Growth and Yield of Tomatoes in Central Uganda. J. Sci. Res. Adv, 3(2016), 306-312.
