Development of bioplastic utilizing cellulose extracted from corn-stalk
Dr. Apurba K. Das (PI IIT Indore)
Er. Harsha Wakudkar, Dr. Sandip Mandal (Co-PI CIAE Bhopal)
The present proposal aims to develop fully biodegradable and natural bioplastic using the cellulose extracted from the corn-stalk. Besides, the proposal intends to fabricate highly thermally stable and rapid degradable bioplastic from the modified cellulose. In contrast with this, the newly developed biodegradable bioplastic must be economic friendly, sustainable and consumer safe. Now-a- days, cellulose has turned to be one of the interesting biomaterial because of its inherent biodegradability, easily availability and most importantly low-priced. Madhya Pradesh is one of the traditional corn growing states and contributing most attractive almost 15% to the total corn production in the country. The modified cellulose derived bioplastic offers excellent tensile strength, shear resistance, moldability and good dielectric strength. Thus, the successful utilization of species of corn-stalk would be a promising biomass to derive the cellulose as an efficient material for bioplastic preparation and can be utilized in agriculture and packing industries.
Sustainable management of organic waste stream comprising fecal, municipal, and agro wastes employing resource recovery approach
Dr. Ashootosh Mandpe (PI IIT Indore)
Dr. Sandip Gangil (Co-PI CIAE Bhopal)
The Government of India (GoI) launched a benevolent campaign, ‘Swachh Bharat Mission-Gramin (SBM-G)’, to make villages open defecation-free (ODF) and provide access to toilets with onsite sanitation systems (OSS). However, the aspect of waste management generated from these OSS, which eventually contaminates soil and water, got somehow unheeded. It is reported that tremendous amounts of fecal waste are generated from these OSS. The present work is proposed to develop a methodology for treating fecal waste (FW) generated from OSS with other organic fractions comprising agricultural waste (AW) and municipal solid waste (MSW) by adopting the resource recovery approach.
Assessing the Farm Mechanization and its impacts on farmers’ Economic Wellbeing: A Case Study of Madhya Pradesh, India
Dr. Kalandi Charan Pradhan (PI IIT Indore)
Dr. Mohanasundari Thangavel (Co-PI IIT Indore)
Dr. Kaushik Prasun Saha (Co-PI CIAE Bhopal)
The proposed study intends to assess the farm machineries used in the agricultural production across the landholding households: Marginal/Small, Medium and large landholding households for the selected one to two district(s) of Madhya Pradesh. Adaptation of machineries in farm practices induce productivity of the agriculture, and it leads to enhancement of farmers’ welfare (Revenue). Therefore, our study will be focused on how far the usage of farm machineries induces the farm productivity across different types of landholdings. It also analyzes sources and cost of the credit for the purchasing farm machineries to measure the credit burden of the sample respondents.
Real-time detection of diseases in paddy / soybean using memristive crossbar array-based image processing for autonomous site-specific application of pesticide
Prof. Shaibal Mukherjee (PI IIT Indore)
Prof. Ram Bilas Pachori (Co-PI IIT Indore)
Dr. Manoj Kumar, Dr. Deepak Singh, Yogesh Rajwade (Co-PI CIAE Bhopal)
MCA-based technology for image processing in agriculture is feasible with a significant reduction in the cost per bit, density, chip area consumption, and power/energy consumption as compared to current technologies based on complementary metal-oxide semiconductor (CMOS) systems while significantly advancing in the high-speed operation and superior accuracy and circumventing the challenges due to Von Neumann bottleneck issues. In precision crop protection, (target-orientated) object detection in image processing can help navigate Unmanned Aerial Vehicles (UAV, crop protection drones) to the right place to apply the pesticide. Unnecessary application of non-target areas could be avoided. The speed of the operation of the drone is 3-4 m/s for spraying at 3 m height above the crop canopy. For real time detection of disease and autonomous spraying by drone needs processing at higher rate. The data processing in on-device computing is very challenging since embedded devices usually have tight constraints on computational power, memory size, and energy consumption, which prohibits the use of the complex state-of-art network. Presently very limited research on the real time disease detection and simaltanous spray application by dorne was reported which is in its initial stage. An automated detection of paddy/ soybean diseases would be investigated via experimentally-fabricated MCA-inspired model based image processing framework including image compression, reconstruction, and classification with the evaluation of promising values of peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) at diverse image decomposition levels.
Assessment of Soyabean based probiotics to combat antimicrobial resistance Helicobacter pylori growth and disease pathogenesis
Dr. Hem Chandra Jha (PI IIT Indore)
Dr. Samlesh Kumari (Co-PI CIAE Bhopal)
Antimicrobial resistance for gram negative bacteria is a growing concern in our society . H. pylori is classified as bad gut pathogen which led to gastritis, ulcer and gastric cancer, even many neurological disorders also associated . Hence, assessing the effects of probiotics in gastric epithelial cells before and after H. pylori infection and study the growth kinetics and disease pathogenesis is crucial to explore. Soybean is a superfood that is becoming the growing choice of health conscious population. Among the soy-based foods, the probiotic fermented soybean products are reported for various health benefits like antithrombotic, and anticancer properties . Therefore, utilizing soyabean based probiotics on the clinical isolates of H. pylori extracted from Malwa region hospitals possibly important aspect in this direction.
Development of economic superabsorbent Agri-gel for studying and soil, water and nutrient retention properties
Dr. Mrigendra Dubey (PI IIT Indore)
Dr. K V Ramana Rao (Co-PI CIAE Bhopal)
The rationale of writing this proposal is to achieve a more efficient economically viable water and fertilizer reservoir that will lead to more input use efficiency in crop production without causing harmful influence on soil environment. This proposal will focus on extensive design and synthesis of ‘O’ and ‘N’ functionalized various hydrogels to ameliorate the availability of all types of essential plant nutrients for plants. The basic idea behind the successful encapsulation/release is based on simple concepts of chemistry such as H- bonding between NPK/urea to N/O sites available in hydrogel matrix. In adverse conditions, uptake of fertilizers and water by the plants from hydrogel material could reduce the frequency of water irrigation which in turn helpful for the economy of farmers.
Deep CNN-based estimation of Above-Ground Biomass of corn crop using variable magnification UAV images
Dr. Ankur Miglani (PI IIT Indore)
Dr. Pavan Kumar Kankar (Co-PI IIT Indore)
Dr. Yogesh Rajwade (Co-PI CIAE Bhopal)
In precision agriculture, the Above Ground Biomass (AGB) is a crucial indicator of the effectiveness of crop production practices and predicting grain yield. Current methods of estimating AGB rely either on manual destructive sampling or data based on remote sensing. The former is time-intensive, costly, and prone to human error, while the latter has a fixed poor spatial resolution, and its effectiveness depends on the regression models used for determining the relationship between the agronomic factors and AGB. To overcome these limitations, the proposed project aims to estimate AGB with a high accuracy by applying state-of-the-art Deep-CNN models on the variable resolution RGB images at different growth stages of the sweet corn plant.
Design and development of cost-effective manually operated rice transplanter
Dr. Jayaprakash Murugesan (PI IIT Indore)
Dr. Rahul Rajaram Potdar (Co-PI CIAE Bhopal)
Manual method of rice transplanting, results in low-yield, due to low seed (root) placement, spacing efficiencies, large plantation time and labour problems. In the proposed research attempts were made to design, fabricate and develop cost effective environment friendly manually operated rice transplanter with the help of advanced simulation software , advanced fabrication techniques and advanced lightweight materials for utilization of small farmers, to enhance their rice productivity, reduce labor cost and time, and there by enhance livelihood of small farmers in rural areas. Field study / trials with the developed machine in rice fields will be also carried out.
Development of Cost-Effective Photo Active Soft Materials for Efficient Removal and Degradation of Pesticides from Contaminated Ground Water
Dr. Tushar Kanti Mukherjee (PI IIT Indore)
Dr. Abhishek M. Waghaye (Co-PI CIAE Bhopal)
The present proposal aims to develop cost effective and stable photo active soft materials to remove and photo‐catalytically degraded toxic pesticides in contaminated ground water. While removal of pesticides from contaminated wastewater is an active research field for quite sometimes, most of the methods can only remove the pesticide contamination. Moreover, most of the existing techniques are time consuming and require expensive setups. In the present proposal, we aim to simultaneously remove and degraded the toxic pesticides via photocatalytic processes. Designing of photocatalyst embedded soft materials having high affinity for pesticides is the first goal of this proposal.
Development of Mobile app for farmers to help them in Agricultural activities: Krishi Sewa
Prof. Aruna Tiwari (PI IIT Indore)
Dr. Shashi Rawat (Co-PI CIAE Bhopal)
The crops like wheat, rice, soyabean and mustard are affected by many disease/pests and some of them are serious enough to wipe out the whole crop within few days if not controlled in time. Thus, there is an urgent need for a computerized multilingual tool/app for correct diagnosis and to advise an appropriate management strategy for control of disease/pest. A forum will be maintained on the app so that it can provide a discussion channel for the agriculture community. Currently the app will be developed for 4 crops viz. Rice, Wheat, Soyabean, and Mustard. In the later course of the project, we plan the implementation of Machine Learning models to predict the diseases and the pest that affected the plant based on weather and other known parameters with the help of precision agriculture, image processing and AI/Ml technologies.
Sustainable Production of Polylactic Acid(PLA) using Agro-Industrial Waste for PLA based bioplastic Formulation.
Prof. Sampak Samanta (PI IIT Indore)
Dr. Manoj Kumar Tripathi (Co-PI CIAE Bhopal)
The greater awareness of non-renewable natural resources preservation needs has led to the development more ecological high-performance polymeric materials with new functionalities. In this regard, biobased composites are considered exciting options, especially those obtained from agro-industrial wastes and by-products. These are low-cost raw materials derived from renewable sources, which are mostly biodegradable and would otherwise typically be discarded. Most horticultural wastes are used as reinforcements or fillers in polymer composites for creating technology-innovative materials as a function of cost. The use of thermoplastic polylactic acid (PLA) in demanding technology applications has recently increased. Due to the attractive properties of high melting point, high density and good chemical inertness, it becomes an important choice for cost-effectiveness and biodegradable material development. Because of the composite’s nature, it can be remelted and recycled for various purposes. Thus, PLA composites are profitable and environmentally friendly.