Sugarcane In India Research Articles

First report of Fusarium andiyazi causing red rot disease on sugarcane in India

First report of Fusarium andiyazi causing red rot disease on sugarcane in India

Forecasting Monthly Export Price of Sugarcane in India Using Sarima Modelling

Sugarcane is the primary agricultural industry that sustains and promotes economic growth in India. In 2018, the majority of India's sugarcane production, specifically 79.9%, was allocated for the manufacturing of white sugar. A smaller portion, 11.29%, was used to produce jaggery, while 8.80% was utilized as seed and feed components. A total of 840.16 million metric tonnes of cane sugar was shipped in the year 2019. The primary objective of this research is to determine the most suitable forecasting model for predicting the monthly export price of sugarcane in India. The input consists of a time series with 240 monthly observations of the export price of sugarcane in India, spanning from January 1993 to December 2013. The SARIMA approach was employed to predict the monthly export price of sugarcane and it is concluded that the SARIMA (0, 1, 1), (0, 0, 0)12 model is the best-fitted one by the expert modeler method. As a result, the fitted model appears to be adequate. The RMSE and MAPE statistics are used to analyze the precision of the model.

Heterogeneous climate effect on crop yield and associated risks to water security in India

ABSTRACT This study uses the Just–Pope approach to investigate the effects of seasonal weather variables and extremes on the mean yield and yield variability of rice, bajra, chickpea, groundnut and sugarcane in India during the period 1990–2015. Results reveal that changes in rainfall and evapotranspiration across seasons largely affect mean yields for most crops, including bajra, chickpea and groundnut. However, high summer rainfall and low monsoon evapotranspiration extremes reduce groundnut and chickpea yield variability. Considering the importance of water availability to crop yields, this study suggests improving irrigation and water reallocation and management to reduce the severity of seasonal climate effects.

Expert system for smart farming for diagnosis of sugarcane diseases using machine learning

Agriculture is one of the oldest occupations in the world and continues to exist today. In some form or another, the world’s population depends on agriculture for its needs. The major loss in sugarcane production in India is due to pests, plant disease, malnutrition, and nutrient deficiency in plants. To identify these diseases, farmers go to local farmers, experts, agricultural people, and fellow neighbors to identify the problem caused. In some cases, their information may be adequate, but in others it is not. These people cannot solve all the problems caused by their crops can be solved by these people; there is a need to accurately predict the correct disease and provide the proper treatment at the right time. This can only be done by applying machine learning-based Internet of Things solutions in real time. This article proposes a method for a smart farming system to address the needs of farmers producing sugarcane in India by applying intelligent solutions that use image processing and soft computing. Four sugarcane diseases are investigated, such as Eyespot, Leaf Scald, Yellow Leaf, and Pokkah Boeng, and three characteristics such as color, shape, and texture. Images were used for training data in Artificial Neural Network (ANN), Neuro-Fuzzy, and Case-Based Reasoning (CBR) algorithms, and the performance of the feature extraction technique was evaluated in terms of sensitivity, specificity, F1 score, and accuracy.

Different Silicon Application Sources and Factors Influencing Mandibular Wear in Sugarcane Early Shoot Borer, Chilo infuscatellus Walker

Silicon (Si) can improve plant resistance to herbivorous insect attack. Early shoot borer (ESB), is one of the most solemn lepidopterans borers on sugarcane in India. Even with insecticide application, management of this pest is difficult. The management requires a fresh new approach. As a result, the current study aims to determine the effect of silicon on the early shoot borer, Chilo infuscatellus Walker, through biophysical factor analysis and mandibular wear documentation. When sugarcane leaves were treated with calcium silicate at 1000 kg/ha, scanning electron microscopy revealed the presence of silicified cells and trichomes, as well as increased cell wall thickness, silicon content, and waxes content. Furthermore, larvae of an early shoot borer fed silica-treated plants showed a complete wearing of mandibles as compared to untreated check.

Impact of weather parameters on maize agroecosystem and adaptation strategies under changing climatic conditions: A review: Sustainable and climate-resilient adaptation strategies in maize agroecosystem

Change in precipitation patterns and increase in the frequency and intensity of extreme weather events (high temperatures and heat waves) harm crop productivity. As per the future prediction, the temperature may increase by 2.5 0C by 2050 and by 2-30 C by the end of the century. The present review evaluates the impact of a rise and fall in temperature, solar radiation, and CO2 on the productivity of maize and other crops. Agronomic management practices during the crop growth period of selecting crop cultivars, date of sowing, plant population, dosage, timing, and methods of application of inputs are influenced by temperature, rainfall, solar radiation, and CO2 concentration in the atmosphere. Overall crop productivity will reduce by 50.9 % in wheat in the USA, 46% in maize in China,17% in cotton in India, and 30% in sugarcane in India. Changing the sowing date and adopting improved early and short-duration varieties of corn and other crops are becoming significant under low-cost adoption technologies to mitigate climate change. Info Crop-SORGHUM simulation model predicts that change in the sowing date of a variety in sorghum reduces the impact of climate change and vulnerability to 1- 2 % by 2020, 3-8 % by 2050, and 4-9% by 2080. The review highlights the impact of heat stress and drought on soil processes, and overall soil health. The authors conclude to implement climate adoption technologies based on Agriculture 4.0 to sustain crop production globally.

Twisted top disease a destructive disease of sugarcane in India

Twisted top disease a destructive disease of sugarcane in India

Athelia rolfsii causing sprout and shoot rot of sugarcane in India

Athelia rolfsii causing sprout and shoot rot of sugarcane in India

Web mite Schizotetranychus krungthepensis on sugarcane in India: molecular evidence for occurrence and the way forward

Web mite Schizotetranychus krungthepensis on sugarcane in India: molecular evidence for occurrence and the way forward

Performance Evaluation of Sugar Industry in India

Sugar industry is the 2nd biggest agro-based industry in India and it significantly contributes altogether to the socio-economic development of the country. The aim of the present paper is to assess the performance of sugar industry in India. Sugar production, export & import and domestic consumption are taken as performance indicators. Further, the study analysed the trends in Fair Remunerative Prices (FRP) sugarcane in India. The study based on the secondary data that has been taken from the various government reports and websites. The results of the study indicated that total agricultural cropped areas are increasing and percentage of sugarcane areas in total cropped areas are increasing and decreasing over the period. Annual growth rate of FRP of sugar was highest in 2009-10 with 59.94 %. There are zero annual growth rates of FRP of sugar during the period 2008-09, 2016-17 and 2019-20 whereas compound annual growth rate of FRP was 8.74 over the period. Export of sugar was increasing whereas import of sugar was decreasing over the period. Domestic consumption of sugar was decreasing between 2018-19 to 2019-20, after that it was continuously increasing.

Growth, Varietal Scenario and Seed Production of Sugarcane in India: Status, Impact and Future Outlook

Growth, Varietal Scenario and Seed Production of Sugarcane in India: Status, Impact and Future Outlook

Plant Quarantine Regulations With Reference to Sugarcane in India: Strengths and Challenges

Plant Quarantine Regulations With Reference to Sugarcane in India: Strengths and Challenges

First report of Maize yellow mosaic virus (MaYMV) infecting sugarcane in India and its molecular characterization

First report of Maize yellow mosaic virus (MaYMV) infecting sugarcane in India and its molecular characterization

Molecular identification of 16SrXI-B subgroup of phytoplasma related strain with yellow leaf disease of sugarcane (Saccharum officinarum) in India

In India, yellow leaf disease (YLD) is known to be caused by Sugarcane yellow leaf virus (SCYLV) and Sugarcane yellows phytoplasma (SCYP; 16SrI-B). Therefore, present study was conducted to confirm the association of specific phytoplasma with YLD in Co 0238 and CoS 510 sugarcane genotypes during 2019-2020 at Indian Institute of Sugarcane Research, Lucknow. The YLD affected genotypes were characterized by yellowing of leaf mid-ribs and leaf-lamina, leaf-tip necrosis, bunching of leaves at crown region and drying of plants with an incidence ranged from 28.26-35.81%. YLD symptomatic leaf samples were collected from the two genotypes and subjected to genomic DNA extraction by DNeasy Plant Mini Kit followed by nested PCR assay using universal phytoplasma primers (16S rDNA region). The nested PCR assays of samples from both the genotypes showed specific amplification. 16S rRNA gene sequence analyses of CoS 510 isolate (MN913611) revealed 100% identity with Sugarcane white leaf phytoplasma (SCWLP) belongs to 16SrXI-B subgroup. Similarly, virtual RFLP analyses revealed 1.00 similarity coefficient with 16SrXI-B subgroup. Thus, present study first time reports the association of SCWLP related strain with YLD of sugarcane in India. Phytoplasma infecting sugarcane are more diverse and needs systematic studies on their single or mixed infections in different varieties in India.

Spatial Growth and Instability Analysis of Area, Production and Yield of Sugarcane in India

In the present study, spatial compound growth rates were estimated to know the growth pattern and instability in the area, production, and productivity of sugarcane in major sugarcane growing states of India. A secondary time series data of major sugarcane producing states of India like Uttar Pradesh, Maharashtra, Karnataka, Tamil Nadu, Bihar, Andhra Pradesh, Haryana, Gujarat, Punjab, Madhya Pradesh, and Odisha for the period thirty years from 1990-91 to 2019-20 have been utilized for the present study. The compound growth rates were computed with the help of exponential function, and instability/variability has been computed by using techniques of co-efficient of variation and Cuddy Della-Valle Index method. Student’s t-test was applied to check the significant differences in area, production, and productivity trends using compound growth rates (CGR). CGR of sugarcane production was 1.13 per centpercent in India during the study period with a significant growth rate in area (1.12%) and yield (0.39%). The statistically significant instability in sugarcane production was high at 9.67 percent than area (7.20%) and yield (5.26%) in the study period. The state-wise compound growth rate of sugarcane production was positively significant in Madhya Pradesh (5.31%), Bihar (3.65%), Maharashtra (3.39%), Karnataka (1.42%), and Uttar Pradesh (1.36%). The highest negative growth rate was observed in Odisha (-5.45%) and Andhra Pradesh (-1.63%). The instability of sugarcane production was highest at 44.06 percent than area (36.66%) in Odisha and yield (14.80%) in Madhya Pradesh.

Design and Evaluation of Drip Irrigation System for Sugarcane in India

Design of drip irrigation system (DIS) for any crop is to be done based on the root spread of the crop and its soil type to maximize the benefits with minimum wastage of water and fertilizers. Soil moisture sensing is very useful in ascertaining performance and to improve real-time operation of the irrigation system. In the present work, design of DIS was done for sugarcane crop grown in sandy clay loam soil, and evaluation of the functioning of the DIS was done by installing soil moisture sensors in the root zone. Daily actual evapotranspiration was estimated using the water balance analysis in the root zone. Deep drainage from the root zone was estimated at every 15-min interval using the Darcy–Buckingham equation. Daily average drainage rate below the root zone was found to be 0.34 mm/day for drip irrigated sugarcane crop in sandy clay loam soil. From the soil moisture sensor observations, it was found that the width of wetted strip never went beyond 60 cm laterally from the lateral. Dripper spacing of 0.3 m was found to be suitable to optimally apply water and fertilizers for sugarcane crop grown in sandy clay loam soil. The information obtained from this study is useful in management of irrigation and fertigation optimally.

Incidence and Diversity of Termites Associated with Sugarcane in North-West Zone of India with New Records

Termites, being serious pests of sugarcane, have been posing threat to its cultivation in Indo-Gangetic plains of North-West zone of India. Monthly observations round the year revealed a highest per cent incidence of termites in the month of August to the tune of 25.45% followed by 22.73, 21.82, 18.18 and 15.45% in the months of July, September, October and June, respectively. The incidence was lower in winter months, i.e. January, February and March with 4.55, 5.45 and 7.27%, respectively. It is evident from the weather data that monsoon season with high relative humidity and moderate temperature was favourable for the build-up of the population of termites, while winter season was unfavourable. Study on relative abundance of different species of termites in sugarcane revealed that termite species, Odontotermes obesus, occupied the maximum percentage of occurrence to the tune of 28.57% followed by that was 21.42, 14.28, 14.28, 14.28 and 7.14% of Microtermes obesi, O. horni, O. vaishno, O. bellahunisensis and Odontotermes sp., respectively. Of the total species recorded during the course of study, three species, viz. Odontotermes horni (Wasmann), O. vaishno Bose and O. bellahunisensis Holmgren and Holmgren, were recorded for the first time to infest sugarcane in India. An illustrated key was developed for easy and quick identification of termite species collected from sugarcane. The study holds promise for strategic planning for the management of termites in sugarcane agro-ecosystem.

Production of Sugarcane Forecasting using ARIMAX Model

The main objective of this study is to analyze the production of sugarcane in India and to forecast the sugarcane production using Auto Regressive Integrated Moving Average with Exogenous variable or Inputs model (ARIMAX). This model mainly focused in the area of forecasting and it gives the accurate prediction. Data has been collected from Sugarcane Breeding Institute, Coimbatore. The ARIMAX model was introduced by Box and Tiao in their study. At present this model was used minimum amount of people in their studies. When we compare with ARIMA model, the ARIMAX model gives the greater accuracy

Trends and Pattern of Sugarcane Production in Shahjahanpur District, Uttar Pradesh: A Geographical Analysis

Sugarcane is important commercial crop of India. It is a major source of raw material for not only sugar industry but also other allied group of industries. Sugarcane plays a vital role for the overall socio-economic development of farming community. Uttar Pradesh is one of the leading producers of sugarcane in India. Shahjahanpur district of Uttar Pradesh has been selected as study area which is famous for sugarcane production. The main objectives of present paper are to assess the trends and patterns of sugarcane production in the district and explain the reasons behind the changes in the sugarcane production. The study is based on secondary sources of data. The study reveals that there is uneven trend of area under sugarcane as well as production of sugarcane in the district and it is found that government policies were important determinants for such trends. Jatipur and Dadrol blocks of the district show high concentration of sugarcane crop. The study further reflects that this area is experiencing an ongoing agricultural development pertaining to the sugarcane cultivation.

ANALYSIS OF SUGARCANE ACREAGE AND YIELD ESTIMATES DERIVED FROM REMOTE SENSING DATA AND OTHER HYBRID APPROACHES UNDER FASAL PROJECT

Abstract. Sugarcane (Saccharum spp.) is a most important cash crop of India. India has the largest area under sugarcane cultivation in the world and is the world’s second largest producer of sugarcane next to Brazil. Uttar Pradesh stands as the leading producer of sugarcane in India followed by Maharashtra. Under FASAL project, the crop acreage and yield forecasts at National/State/District level, is issued at two levels. This study was carried out to analyze under FASAL Project at Mahalanobis National Crop Forecast Centre, New Delhi during year 2018. Five-year state and district level area, yield and production estimates were observed and analyzed using different approaches in 6 major sugarcane producing states of India. The state and district-wise sugarcane area yield and production estimates of MNCFC were compared with the DES Data of the corresponding year. Two statistical parameters were computed namely, Root Mean Square Error RMSE (%) and correlation coefficient (R). The results when compared to the DES statistics revealed that the RMSE (%) for district level analysis were 23.4%, 30% and 18.35%, while the correlation coefficient (R) between the DES and FASAL estimates was computed 0.94, 0.95 and 0.60 for area, production and yield respectively. These results revealed that RS based technique can be effectively used for state level acreage, yield and production estimation. The national level statistics revealed that the correlation of FASAL sugarcane area and production is in good agreement with the DES estimates as compared to Yield estimates.