Pavan Kumar S T

• Doctor of Philosophy (Statistics)
• Professor (Assistant) at Central Agricultural University

The present study aims at estimating the multiple change points for the time series data of COVID-19 confirmed cases and deaths and trend estimation within the estimated multiple change points (MCP) in India as compared with WHO regions. The data were described using descriptive statistical measures, and for the estimation of change point’s E-divis...

Available data of 171 species of Phytoseiidae family were classified into three distinct subfamily clusters i.e., Amblyseiinae (Cluster-I), Phytoseiinae (Cluster-II) and Typhlodrominae (Cluster-III) based on key setae characters. PCA was deployed to know the strength of characters in enhancing the separations of the clusters and Discriminant analys...

Selection of parameters for Auto Regressive Integrated Moving Average (ARIMA) model in the prediction process is one of the most important tasks. In the present study, groundnut data was utlised to decide appropriate p, d, q parameters for ARIMA model for the prediction purpose. Firstly, the models were fit to data without splitting into training a...

Limitation of classical regression regarding specification of model and residuals characteristics, nonlinear techniques play a vital role. Artificial Neural Networks and Regression techniques were applied. Two techniques were compared based on model accuracy like RMSE, R-square and ANN technique provided better model accuracy than the regression me...

The predatory mite family, Phytoseiidae is one of the most explored groups worldwide as biological agents against phytophagous mite pests and small insects viz thrips, whiteflies, coccids and pseudo coccids in alternative to application of acracides. In search of key traits of predatory mites for proper identification as the species level classific...

Aquaculture, fisheries, and water resources are important to a region’s socioeconomic growth. The study was conducted by using a descriptive research design in all seven blocks of three sub-divisions of the Sepahijala district of Tripura to assess the water resources and utilisation dynamics for fisheries and aquaculture production in the district...

Under the neo-endogenous rural development outlook for social change in low- and low-middle-income countries (LMICs), digitised knowledge and information-sharing tools such as mobile-based agro-advisory systems (MBAS) emerged as long-awaited social innovations. A farmer-centric mobile phone-based aquaculture extension approach (named Matsya Varta)...

The study aimed to ascertain a relationship between agricultural status, socioeconomic factors, and nutrition of farm families. The study was conducted in selected villages in the West Garo Hills district of Meghalaya, using Stratified Random Sampling (St. RS). Using pretested interview schedules, we collected primary data from respondents in 2020...

The Interactive Information Dissemination System (IIDS), a unique mobile-based agro advisory system (MBAS), was put under study in the Design Science Research approach with 2820 farmers in Garo Hills of Meghalaya, India. The study aims to design and develop a user-centric MBAS (m4AgriNEI) for augmenting sustainable smallholder farming systems in hi...

Cotton grown in the Garo hills of Meghalaya, India, belongs to the Indian cotton species, Gossypium arboreum race cernuum and this cotton is popularly known as Comilla cotton or Assam Comilla. It is cultivated under traditional jhum cultivation in a mixed cropping system with 10–15 crops in a single piece of land. The cernuum race is bestowed with...

Under global warming and climate change (CC), the vulnerable piece of land is India’s Eastern-Himalayan-Region (EHR), where millions’ livelihood activities are at risk. Quantifying the degree of CC-induced vulnerability over the highly climate-sensitive mountain zone is challenging due to data inadequacy. This paper attempted to assess the CC perce...

The present study was conducted to understand the present and future perspective of milk production in Karnataka and to develop a suitable model for prediction of milk production in the state. The present study is having advantage as the past trends of milk production in the state have been impressive with growth, contributing significantly to over...

The study aims at ascertaining the conditional selection of key indicators affecting severe, moderate, mild, and no anaemia levels for women of reproductive age in India. The secondary data for levels of anaemia and personal records of individuals collected for India from the 7th phase of District Health Survey program of the United States Agency f...

This study seeks to identify the change points, tendencies, and trends in climatic parameters and to investigate their relationship with forest cover loss and carbon dioxide (CO2) emission in the Garo Hills region of Northeast India.This study is based on secondary data on Precipitation, Maximum Temperature, Minimum Temperature, Relative Humidity,...

Jackfruit gets wasted to the tune of $5.8 million every year from 0.4-0.5 million jackfruit trees in Garo Hills due to lack of suitable infrastructure, limited scientific know-how regarding processing and storage, and restricted market access. The study aims to explore the status of jackfruit cultivation and utilisation of locally available jackfru...

The data series tested for stationarity using an augmented dickey-fuller test and data was found non-stationary, and it was analyzed using Autoregressive Integrated Moving Average with explanatory variables model with first differencing, and Feed-Forward Neural Network regression. The ARIMAX model outperformed the feed-forward regression model with...

In the present study, an attempt was made to forecast the ginger area and production using Artificial Neural Networks and Box-Jenkins ARIMA models, and both models were compared on the basis of accuracy criteria. The ANN models utilize backpropagation and conjugate gradient methods to train the data in the hidden layers, and the sigmoid function as...

Latin America is a region that is dependent on natural resources; thus, posing severe challenges for achieving economic progress along with social inclusion. This research aims to examine how the formation of trade blocs moderates the link between natural resource rents-economic progress in Latin America using non-linear econometric methods. In add...

In the present study, pest and disease incidence and population of damselfly in rice crop were estimated using conventional regression (Stepwise Regression) and Fuzzy linear regression. The weather parameters viz., Maximum Temperature, Minimum Temperature, Relative Humidity Morning, Relative Humidity Evening, Rainfall and Sunshine Hours were utiliz...

In the present investigation, trends in population dynamics of major insect pests of soybean crop have been studied through probability model. Among the major insect pests the numbers of larvae of S. litura, Thysanoplusia orichalce, Spilosoma oblique Walker and their natural enemies namely Anisoptera, and spider were observed on soybean. The occurr...

Limitation of classical regression regarding specification of model and residuals characteristics, nonlinear techniques play a vital role. Artificial Neural Networks and Regression techniques were applied. Two techniques were compared based on model accuracy like RMSE, R-square and ANN technique provided better model accuracy than the regression me...

Available data of 171 species of Phytoseiidae family were classified into three distinct subfamily clusters i.e., Amblyseiinae (Cluster-I), Phytoseiinae (Cluster-II) and Typhlodrominae (Cluster-III) based on key setae characters. PCA was deployed to know the strength of characters in enhancing the separations of the clusters and Discriminant analys...

Time series prediction of pest and natural enemies is most important for the crop management and minimizing the pesticide use and the Artificial neural network (ANN) model is most powerful Artificial intelligence (Al) machine learning models have the capacity to generalize more with less error and it is also important to investigate the convergence...

Variations in different characters of the pigeonpea were studied using 122 accessions under rainfed condition during 2013. The characters considered viz., days to 50 per cent flowering, plant height (cm), days to physiological maturity, pods per plant, pod bearing length (cm), seeds per pod, 100 seed weight (g) and seed yield per plant (g) were use...

Study was carried out by using eleven years data regarding shoot fly egg count and the per cent dead heartat four different intervals of the crop. Toknow the effect of the different weather parameters viz. maximum temperature, minimum temperature, relative humidity in morning, relative humidity in evening and rainfall on incidence of shoot fly in r...

In the present investigation, trends in population dynamics of major insect pests of soybean crop have been studied through probability model. Among the major insect pests the numbers of larvae of S. litura, Thysanoplusia orichalce, Spilosoma oblique Walker and their natural enemies namely Anisoptera, Coccmellidae and spider were observed on soybea...

The present study was based on the available data of eleven years for shoot fly from 2000-2010 for kharif season. Different models viz., linear and non linear were tried to fit, Amongst, the linear, quadratic and cubic models produced better coefficient of determination and the models viz., EGG(Shoot fly Egg) =3.760+0.196(DOS) (R2 =0.892) and EGG(S...

To know the association between different weather parameters viz, Maximum temperature, Minimum temperature, Relative humidity in morning, Relative humidity in evening, Rainfall and shoot fly in kharif season. Correlation study revealed that, rainfall found an important weather parameter which was having negative association with the egg population,...

Variations in different characters of the pigeonpea were studied using 122 accessions under rainfed condition during 2013. The characters considered viz., days to 50 per cent flowering, plant height (cm), days to physiological maturity, pods per plant, pod bearing length (cm), seeds per pod, 100 seed weight (g) and seed yield per plant (g) were use...

Weather based prediction model for shoot fly incidence in sorghum crop was developed for Dharwad region of Karnataka using the weather variables viz., maximum and minimum temperature, relative humidity in morning and evening, rainfall and shoot fly egg and dead heart per cent data during Rabi season. Stepwise regression analysis was carried out to...

Arecanut (Areca catechu) also popular by name supari or betelnut. It is one of important commercial crop in Uttara Kannada district, contributing around 9 percent of area and 11 percent of production to the Karnataka state total. The present study is based on the secondary data of over 30 years collected from Directorate of Economics and Statistics...

Artificial Neural Networks model have been used in plant pathology to study dynamics, modeling and forecasting of several disease in recent years. Artificial neural networks are parallel computing systems made up of a large number of simple, highly interconnected processing elements called nodes or neurons that process information by their dynamic-...