Acharya N.G.Ranga Agricultural University (ANGRAU), LAM, Guntur, Andhra Pradesh, India is a state agricultural University that works under the Indian Council for Agricultural Research (ICAR). It’s a non-profitable registered organization. With the tripartite mandate of teaching, research and extension through innovative methods of ANGRAU, the state of Andhra Pradesh has witnessed a quantum leap in food productivity and production through agro-climate-based, location-specific research strategies of multi-faceted crops covering cereals, pulses, oilseeds, major and minor millets. The contribution of ANGRAU through a slew of technological interventions in developing new varieties, in ushering and transforming Andhra Pradesh into the “Rice Bowl of India” is phenomenal.In academics, “Enter to learn and leave to serve” is the dictum that drives ANGRAU to be a pioneer in preparing students to meet challenges around the globe through quality education with ethical and moral values. It offers B.Sc (Hons.), M.Sc(Ag.), Ph.D(Ag.) with various specializations in 18 colleges and also diploma courses for rural youth in around 80 colleges in Andhra Pradesh. It has been working for the enhancement of a student-centric learning environment through innovative pedagogy to meet technological upgrades. Sri Venkateshwara Agricultural College (SVAC), Tirupati is one of the best and most ancient colleges run under ANGRAU since 1961 to produce agricultural graduates targeting food security and sustainable agriculture.
Sree Padmavathi Venkateswara Foundation (SreePVF) is a non-profit organization based in Vijayawada, Andhra Pradesh. The foundation focuses on health care, education, innovation, and agriculture, offering awards, donations, and grants to individuals and institutions whose aims and activities are aligned with those of the foundation. Since its inception in 2014, SreePVF has been committed to enriching the lives of people through philanthropic activities and playing a vital role in nation-building.
In 2021, SreePVF expanded the Sree Ramakrishna Paramahamsa Research Grant to include the agricultural sciences. The grant aims to provide last-mile funding for novel and sustainable solutions that benefit small and marginal farmers in India. This program provides a 50-lakh grant over two years to individuals and institutions whose work aligns with our mission to improve agriculture practices and promote sustainable solutions in the field. At SreePVF, we believe that through research and innovation, we can help drive progress and make a positive impact on society. In 2022, this project is grated by Sree PVF. For more info please follow https://sreepvf.org/
Among cereals, Rice (Oryza sativa, f: Graminae) is an important food crop and major calorie source for over 3 billion people on the earth. India is first in terms of area under rice cultivation, with 47.8 million hectares, and second in terms of rice production with 138 million tonnes, accounting for 22.81 percent of global rice production with an average productivity of 2650 kg/ha. In Andhra Pradesh rice crop is cultivated in an area of 2.21 million ha, an annual production of about 8.25 M.t. with an average productivity of 4.3 tonnes/ha. ( www.ipad.fas.usda.gov. 2023-24).
Insect pests continue to be a constant problem for rice production among many others, in all the rice cultivated areas. Rice is prone to more than 100 invasive species of insects during its crop growth period which markedly reduce the productivity. The key insect pests affecting the yield are Scirpophoga incertulas, Yellow stem borer (Scirpophaga incertulas), Brown plant hopper (Nilaparvatha lugens), Rice leaf folder (Cnaphalocrocis medinalis), Gall midge (Orseolia oryzae).
Weather parameters viz., temperature, rainfall, relative humidity, sunshine hours and wind speed are the major weather elements determining the insect pests’ occurrence. Weather based pest forewarning models have been formulated to some extent by many researchers. Hence, an operationally feasible forewarning model for insect pests’ prediction is the need of the hour for efficient insect pest management. Considering this, an attempt is planned to predict the population occurrence of YSB, BPH and RLF using Artificial intelligence instead of other linear, nonlinear statistical and time series models as they failed to provide accurate predictions for count data like insects catches due to their underlying assumptions.
Most of the studies conducted for modeling and forecasting Pest in Rice are not bothered about excess zeroes in the data sets. Ignoring excess zeroes in data leads to redundancy in parameter estimation of the models. Crop pest modeling is one of the major areas of count data modeling wherein daily or weekly counts of insects or pests are considered by assuming the observations are derived from Poisson and negative Binomial distributions.
Moreover Artificial Neural Network (ANN) and Support Vector Machine (SVM) are most widely used Artificial Intelligence (AI) techniques to model and forecast the time series data. The major advantage of neural network is their flexible nonlinear modeling capability to model complex, undefined data and there is no need to specify a particular model specification.
With this background, a typical study is planned to develop zero excess models using count data driven approaches and Machine Learning models such as ANN (Artificial Neural Network), SVR (Support Vector Regression) to model pests in Rice to provide forewarning advisory services to the farming community to reduce the yield loss due to pest.
Finally, weather based pest forewarning advisory services will be kept available to the Rice cultivators in the southern zone of Andhra Pradesh. Validation and revision of the models will be done yearly by including newly added data for more accuracy in predictions.
Dr. P. Lavanya Kumari
Assistant Professor & Head
Dept. of Statistics & Computer Applications
S.V. Agricultural College, Tirupati,
Acharya NG Ranga Agricultural University,
LAM, Guntur, Andhra Pradesh (A.P)
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Division of Statistical Ecology and Environmental Statistics, ICAR - Indian Agricultural Statistics Research Institute, New Delhi |
ICAR-Indian Institute of Rice Research, Hyderabad |
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