Information Tecnology Based Decision Support System for Integrated Pest Management on Rice

The epidemiological aspect including monitoring is a critical component of implementing an early warning system. The tungro epidemic in rice is influenced by the population dynamics of the green leafhopper vector. Likewise, rainfall and biotic factors affect the abundance of green leafhopper vectors. Long-term data are essential to explain that mechanism, so population predictions on a seasonal scale can be obtained accurately. This paper analyses weekly data on catching green leafhoppers and other arthropods in a continuous cropping system from 2013-2019. We utilize the climatic data gathered to assess the impact of climatic conditions on population dynamics. To improve the additive and homoscedasticity of the time series, we transform the data. The data are fitted in a linear model. The results showed that the green leafhopper population affected the incidence of tungro in the field. From January to December, the population dynamics of the green leafhopper can be characterized. It can assist in monthly population forecasting for the following years. Exogenous and endogenous variables, however, still need to be studied more comprehensively to identify any other predictive components that should be incorporated.

Section: Discussionmentioning

confidence: 99%

Evaluate the population development of green leafhopper as a tungro vector in the endemic area from long-term data

Senoaji

Ibrahim

Rosida

et al. 2023

“…Pest and disease control that is not carried out properly through integrated pest control will result in less effective and efficient control methods. Implementation of integrated pest management by considering the economic threshold in rice cultivation will ensure the sustainability of rice farming [21,22].…”

Section: Application Level Of Rice Cultivation Technologymentioning

confidence: 99%

Farmers’ responses to the use of rice agro-advisory service application in South Bengkulu Regency

Ishak,

Margono,

Alfayanti

et al. 2024

The Rice Agro-advisory Service which in Indonesian is called “Layanan Konsultasi Padi (LKP)” is an internet-based digital application developed by IRRI to compile recommendations for rice cultivation technology. This study aims to determine the response of farmers in the production centers of irrigated lowland rice in South Bengkulu Regency to the application. The research was carried out from September to November 2022 through a survey involving 87 farmers in 42 villages. The data collected includes farmers’ responses to recommendations for lowland rice cultivation technology generated by LKP and farmers’ responses to its attributes, namely mobility (ease of accessing applications), interactive (recommendations by needs of farmers), communicative (recommendations easily understood by farmers), and autonomous (applications can be operated by farmers independently). Data were analyzed descriptively and correlated using contingency coefficients. The results showed that 83.91% of farmers responded well to the application recommendations. Responses to LKP were classified as good for all attributes as mobility (95.40%), interactive (96.55%), communicative (98.95%), and autonomous (74.71%). Farmers’ responses to the LKP recommendations were positively correlated with the interactive attribute which means that a good response to LKP recommendations is closely related to the needs of farmers for site-specific recommendations for lowland rice cultivation.

“…The economic loss as the effect of its attack is huge. According to [2], for Indonesia itself, the economic loss in 2020 was more than IDR 39 Billion or USD 250 thousand.…”

Section: Introductionmentioning

confidence: 99%

“…Monitoring is important in determining attack and estimating the effect [2,3]. The traditional monitoring approach is usually conducted by visual observation and field scouting with limitations, such as subjectivity and time consumption.…”

Section: Introductionmentioning

confidence: 99%

Rice brown planthopper monitoring and detection by spectral reflectance: a review

Arifin,

Koesmaryono,

Impron

2023

Brown planthopper (BPH) has been one of the main pests of rice worldwide. Monitoring is important factor for determining attacks and estimating their effects. The traditional monitoring approach is usually conducted through visual observation and field scouting, with limitations such as subjectivity and time consumption. Remote sensing is an alternative pest monitoring method that covers a larger area in a shorter time. This paper discusses a remote-sensing method that uses a spectral approach to detect BPH attacks. Literature was filtered and processed using the PRISMA method. According to the spectral sensor, studies were classified into multispectral and hyperspectral sensors. Based on this scale, there are four studies on the panicle, leaf, canopy, and field levels. The model used single-wave reflectance and spectral indices as predictors. Various algorithms were used in the studies: linear regression, Principal Component Analysis, and Machine Learning to estimate the severity class, BPH Population density, and yield loss. A combination of spectral reflectance with other parameters, such as weather, fertilizer application, and infestation time, was conducted to improve the performance of the detection model. This review provides state-of-the-art spectral reflectance usage for detecting BPH attacks and opportunities for future development.