"Rice killers" have nemesis
Spring ploughing and spring management are at the right time, and there is a boom all over the country. Recently, the General Office of the Ministry of Agriculture and Rural Affairs issued a notice on the "2024 Action Plan for Ensuring a Bumper Harvest by Insects and Grains", pointing out that in 2024, the overall occurrence of the two chemical borers will be heavy to large, and the occurrence of rice planthoppers, rice leaf rollers, and rice sheath blight will be more serious, and according to the prediction and analysis of the National Agricultural Technology Center, the occurrence area will reach 1.24 billion mu. Rice planthoppers feed themselves by absorbing rice juice, and will also spread the virus to rice plants, which brings great damage to the quality of rice, but due to the small size of the insects, manual identification and counting are time-consuming and laborious, and the detection rate and accuracy have been difficult to improve. As a leading digital agricultural enterprise in China, Top Yunnong is well versed in the pain points and difficulties of small insect body detection and reporting, and has independently developed an intelligent insect detection and reporting system under the professional guidance of agricultural research institutes.
For insect pests such as rice planthoppers that are small in size, difficult to identify, and harmful in harm, the small insect intelligent detection and reporting system of Top Yunnong has broken through key technologies such as live photography, specific insect trap spectrum, and deep learning algorithm identification, so as to fill the gap in the current phototaxis millimeter-level insect detection and reporting. A specific light source is used to trap millimeter-level small insects such as rice planthoppers and leafhoppers, and the structure of the insect entrance is specially customized to filter the interference of large insects and realize the efficient attraction of small insects at the source. The general insect detection and reporting lamp may have different degrees of insect stacking, large insects covering small insects, etc., high temperature heating and insecticide, the posture of the dead body is difficult to control, sometimes it is difficult to capture the characteristic details of the planthopper's back plate, and it is impossible to distinguish the specific species; The white-backed planthopper and other planthoppers that do not harm rice make the monitoring of rice planthopper more refined and accurate.
In order to verify the accuracy and effectiveness of the intelligent detection and reporting system for small insects, in 2023, Top Yunnong will go deep into the practical application scenarios, actively look for plant protection monitoring and reporting personnel, and conduct field trials in 7 places in Jiangsu, Sichuan, Chongqing, Hunan, Guangxi, and Hainan. The results showed that the intelligent detection and reporting system could monitor the outbreak of rice planthoppers in the field in a timely manner, and the number of rice planthoppers automatically identified was highly accurate and credible, which provided favorable data support for the detection, reporting and control of rice planthoppers. In addition, under the leadership of the National Agricultural Technology Extension Service Center, Top Yunnong conducted experiments in Jiangsu, Sichuan, Yunnan and other places, and verified that the identification accuracy of the small insect intelligent detection and reporting system for brown planthoppers, white-backed planthoppers and gray planthoppers can reach more than 90%, which is basically consistent with the results of manual identification, and the peak and trend fitting degree of planthoppers are basically the same. In 2024, Top Yunnong will continue to participate in the field trials organized by the National Agricultural Technology Service Center in Fujian, Jiangxi, Hunan, Guangdong, Guangxi, and Guizhou, so as to further enrich the database of phototaxis millimeter-level insects and improve the intelligent light trap monitoring technology of planthopper leafhopper small insects.
With its own innovation and efficiency, the small insect intelligent detection and reporting system of Top Yunnong has been listed as the "2023 Excellent Project of New Technologies, New Products and New Models of Digital Agriculture and Rural Areas" recommended by the Information Center of the Ministry of Agriculture and Rural Affairs, and has been successfully selected as a key recommended plant protection product in Hebei Province in 2024. The popularization and application of this equipment can effectively reduce the cost of manual monitoring and reporting, and at the same time can improve the real-time and accuracy of prediction and prediction of rice planthoppers.
Broaden the scene "fruit" and "tea" upgrades
The problem of millimeter-level pest detection and reporting not only exists in rice production, but also exists in production scenarios such as tea production and fruit tree planting. The National Agricultural Technology Center issued the "2024 Technical Plan for the Prevention and Control of Major Pests and Diseases of Horticultural Crops", pointing out that green bugs and leafhoppers are typical millimeter-level pests that harm orchards and tea gardens, and it is necessary to implement the plant protection policy of "prevention first, comprehensive control" to focus on prevention and control to ensure the quality and safety of fruit and tea production.
The green blind bug is an omnivorous pest, when spring comes, the adults or nymphs of the green blind bug invade the growth of pears, grapes, apples, tea and other crops in groups, silently infesting the leaves of fruit trees and tea trees, stabbing the young green leaves, sucking the sweet juice, leaving black-brown necrotic spots and escaping. The leafhopper looks like a cicada, and the adult and nymphs suck the juice as a pest, and the host is tea, peach, grape, etc. Early sucking calyx, petals, after flowering sucking leaves, the victim leaves appear green white spots, severe the whole leaves are pale, early defoliation. These two millimeter-level insects are harmful to orchards and tea gardens, and have become a big problem for farmers.
In the face of the recurrence of pests and diseases, Top Yunnong has made efforts to solve the pain points of the market, and while continuously achieving phased results, it has further consolidated the hardware foundation of the intelligent monitoring and reporting system for small insects and comprehensively optimized the software kernel. In response to the market demand for pest control in rice, tea plantations and orchards, the insect species of rice planthoppers and leafhoppers were expanded, and the green blind bugs that harmed orchards were added. At the same time, it breaks through the original recognition capabilities and application scenarios, so that the intelligent detection and reporting system of small insects ushers in a new round of comprehensive upgrades, and the identification of insects can be expanded to 20 millimeter-level microscopic insects, including rice planthoppers, green blind bugs, leafhoppers and so on. In addition, Top Yunnong further consolidates the hardware foundation, adopts solar power supply mode and rainproof design, which effectively increases the battery life by 30% and realizes normal insect catching work on continuous rainy days.
Customized identification to meet specific needs
TOP Yunnong has a rich insect database and strong algorithm capabilities, and can also support customized identification services to identify other phototaxis micro pests (insect size between 1.5mm-10mm) to meet the specific needs of the market and users.
Based on the abundant worm database, customized identification can be quickly realized. If it is greater than 500, the algorithm will be directly launched, the training and testing time will be about 5 working days, and the initial recognition rate can reach more than 80%. The initial recognition rate is expected to reach 80%. The device continues to collect and update the model every 3 days, and the recognition rate can reach 85%-90% after 9 working days.
If the pests you want to identify are small or no in the existing database, based on strong algorithm capabilities and team advantages, we can also meet your specific needs. First of all, it is necessary to conduct insect body research on the target pest, obtain the size of the insect, flight altitude, sensitive band and other information; secondly, it is necessary to install equipment for the target pest in the area where the insect pest occurs for insect trapping, and the number of traps is greater than 500 heads can be put on the algorithm, and the algorithm can be trained by establishing a deep learning recognition model, if the equipment can trap more than 50 heads every day, the algorithm can update the model once every 3 days, and then after about 9 working days, the identification rate of the target pest can reach 85%-90%.
The mainland is a major producer of crops, and it is also a country prone to pests and diseases. At present, changes in climatic conditions, agricultural practices, and the complexity of the occurrence of pests and diseases have made the mainland plant protection work face new problems. As a leading provider of comprehensive digital agriculture solutions in China, Top Yunnong has cultivated a deep love for agriculture for many years and has continued to practice, insisting on using digital technology and data services to empower the high-quality development of the planting industry and industry. In the future, TOP Yunnong will continue to uphold the mission of "changing traditional agriculture with science and technology and creating a better life with service", deeply integrate the new generation of information technology with plant protection monitoring and reporting, continue to upgrade and improve the monitoring and reporting tools, and take market pain points and user needs as the starting point to further improve and innovate the intelligent monitoring and reporting system for small insects, broaden the application scenarios and fields of pest detection and reporting, and contribute more wisdom and strength to the construction of a digital system of plant protection in the mainland.