Climate-Based Modeling and Prediction of Rice Gall Midge Populations Using Count Time Series and Machine Learning Approaches

The Asian rice gall midge (Orseolia oryzae (Wood-Mason)) is a major insect pest in rice cultivation. Therefore, development of a reliable system for the timely prediction of this insect would be a valuable tool in pest management. In this study, occurring between the period from 2013–2018: (i) gall midge populations were recorded using a light trap with an incandescent bulb, and (ii) climatological parameters (air temperature, air relative humidity, rainfall and insulations) were measured at four intensive rice cropping agroecosystems that are endemic for gall midge incidence in India. In addition, weekly cumulative trapped gall midge populations and weekly averages of climatological data were subjected to count time series (Integer-valued Generalized Autoregressive Conditional Heteroscedastic—INGARCH) and machine learning (Artificial Neural Network—ANN, and Support Vector Regression—SVR) models. The empirical results revealed that the ANN with exogenous variable (ANNX) model outperformed INGRACH with exogenous variable (INGRCHX) and SVR with exogenous variable (SVRX) models in the prediction of gall midge populations in both training and testing data sets. Moreover, the Diebold–Mariano (DM) test confirmed the significant superiority of the ANNX model over INGARCHX and SVRX models in modeling and predicting rice gall midge populations. Utilizing the presented efficient early warning system based on a robust statistical model to predict the build-up of gall midge population could greatly contribute to the design and implementation of both proactive and more sustainable site-specific pest management strategies to avoid significant rice yield losses.

Comparative efficacies of insecticides and botanicals against rice gall midge, Orseolia oryzae (Wood-Mason) and their effect on the parasitoid Platygaster oryzae in rice ecosystem of Odisha, India

A field experiment was carried out to determine the comparative efficacy of newer insecticides with botanical insecticides, viz., Chlorantraniliprole 0.4G @ 10 kg ha-1, Fipronil 5 SC @ 1500 ml ha-1, Acephate 95 SG @ 750 g ha-1, Lambda cyhalothrin 4.9 CS @ 550 ml ha-1, Thiamethoxam 25 WG @ 150 g ha-1 @ Carbofuran 3 CG @ 30 kg ha-1, Carbosulfan 25 EC @ 875 ml ha-1, Cedarwood oil @ 1000 ml ha-1, Azadirachtin 0.03 EC @ 2500 ml ha-1, applied at 20 and 35 DAT, against rice gall midge, Orseolia oryzae (Wood-Mason) in rice during kharif, 2019 and 2020. All the treatments were effective for gall midge. Lambda cyhalothrin 4.9 CS @ 550 ml ha-1 was significantly superior (>80% reduction over control) for gall midge management and grain yield was 4.75 t ha-1. Both botanical and untreated plots had more number of parasitized gall midge (40- 53.3%) than other chemical treated plots.

Identification of a new resistance locus against the rice gall midge, Orseolia oryzae (Wood-Mason), in Thai rice landrace MN62M

Background The rice gall midge (RGM), Orseolia oryzae (Wood-Mason), is one of the most destructive insect pests of rice, and it causes significant yield losses annually in Asian countries. The development of resistant rice varieties is considered as the most effective and economical approach for maintaining yield stability by controlling RGM. Identification of resistance genes will help in marker-assisted selection (MAS) to pyramid the resistance genes and develop a durable resistance variety against RGM in areas with frequent outbreaks.Results A mitochondrial gene, cytochrome C oxidase I (COI), was used to analyze the genetic diversity among Thai RGM populations. The phylogenetic tree indicated that the Thai RGM populations were homogeneously distributed throughout the country, except for some populations in central and northeast Thailand that probably became isolated from the main population. The reactions of the resistant rice varieties carrying different resistance genes revealed different RGM biotypes in Thailand. The Thai rice landrace MN62M showed resistance to all RGM populations used in this study. We identified a novel genetic locus for resistance to RGM, designated as GM12 , on the short arm of rice chromosome 2. The locus was identified using linkage analysis in 144 F 2 plants derived from a cross between susceptible cultivar KDML105 and RGM-resistant cultivar MN62M with single nucleotide polymorphism (SNP) markers and F 2:3 phenotype. The locus was confirmed and mapped using SNP and simple sequence repeat (SSR) markers surrounding the target chromosomal location. Finally, the locus was mapped between two flanking markers, RM6800 and S2_419160.Conclusions We identified a new RGM resistance gene, GM12 , on rice chromosome 2 in the Thai rice landrace MN62M. This finding yielded SNP and SSR markers that can be used in MAS to develop cultivars with broad-spectrum resistance to RGM. The new resistance gene provides important information for the identification of RGM biotypes in Thailand and Southeast Asia.