Solving Nitrogen Deficiency in the Crops
The problem it can address is:-Nitrogen application problems, lower quality and yield of the crop, early disease detection in leaf, over fertilization which causes environmental pollution and groundwater contamination.
The quality and productivity of crop are directly related chlorophyll. Chlorophyll is an indirect estimation of nitrogen concentration in the leaves. Thus, the idea is to design and develop a system that can quantify the chlorophyll present in the crops and thus guide for the assessment of nitrogen status in the crop leaf. As we know, chlorophyll contains most of the Nitrogen so knowing the chlorophyll will gives indirect estimation of Nitrogen status in the Crops.
The innovation will help in reducing environmental pollution and ground-water contamination caused due to over fertilization. It will help guide N management in agricultural systems, to assess the effect of nitrogen on crops yield and also the early detection of diseases
The traditional method of measuring the chlorophyll are too slow, laborious, instruments are bulky, highly expensive and leaf sample can’t be retained for further measurements. Nitrogen, phosphorous and potassium are the three most vital soil nutrients required by plants, should be present in the ratio 4:2:1 to ensure healthy growth of cops. However, the current scenario for India sees a ratio of 6.8:2.7:1. This is due to the over fertilization of fields. Both over fertilization and under fertilization affects the quality and yield of crops.
The innovation will help in reducing environmental pollution and ground-water contamination caused due to over fertilization. It will help guide N management in agricultural systems, to assess the effect of nitrogen on crops yield and also the early detection of diseases.
118 million farmers are in India. Considering just 2% of it as Service obtainable market and catering it to this 1% market in 3 to 5 years, the market is for 300 crore Indian rupees. Similar product cost 40,000 rupees to 1.25 lakh rupees. We are considering the selling price of this to 20k which has a margin of almost 70%.
This device is dependent on the spectral reflectance data retrieved via calculating the percentage of reflectance data corresponding to light waves of a different wavelength falling on the Leaf surface. The GBNDVI parameter is hence calculated in order to determine the concentration of chlorophyll in real-time which correlates with the nitrogen concentration in the leaves.
The novelty comes in designing of the apparatus which provides a closed environment without interference from the external light. The LEDs used are of specific wavelength which is associated with the absorption properties of Leaf. The Spectral parameter is modified in such a way that it eliminates the variability of species across leaf and also sensitive to change in chlorophyll. The camera detector captures the RAW Bayer data (unprocessed data) of leaf surface and thus calculate the modified parameter called GBNDVI. Further, the Leaf is taken to the Lab and pigment is extracted using acetone and spectrophotometric analysis is done on the sample collected and thus chlorophyll is calculated using Arnon method
The system developed will be useful to the Farmers, Research labs, Agri Data analytics company, KVKs, FPOs.
We are planning to reach our to target farmers through distributors. To reach to data analytics company and FPOs, it will be direct b2b. We may reach them through our channel partners or with our own marketing team. We have not yet commercialized this technology
We are yet to conduct pilots in open fields. We have compared the results of our developed prototype with spectroscopy method (UV-VIS-NIR) Spectroscopy. Results are quite accurate.
Actual system prototype is near completion or ready and has been demonstrated in an operational environment or is at pilot level.
- Support small-scale producers with access to inputs, capital, and knowledge to improve yields while sustaining productivity of land and seas
The prototype built is cheap and can be easily affordable by the small scale farmers. Farmers with even 3-5 hectares of land could buy and use for their crops monitoring and nitrogen assessment. This will improves the quality of proves and also increase the yield of crops. The optimum fertilization shall increase the increase the fertility of land.
This novel application shall improves the food security to meet he demand of increasing population and hence will creates a sustainable food bank. It will reduce the environment pollution as well as ground water contaminationwhich is occurred due to over fertilization.
- Pilot: An organization deploying a tested product, service, or business model in at least one community
- A new technology
The available commercial chlorophyll meters(SPAD meter, Green-Seeker, atLeaf) is affected by the external light, thus producing erroneous in the result. The sampling area of these products is very small(6mm) which push to take too many readings which consume time. These product spectral parameter gets saturated as chlorophyll increases in the leaves, thus not suitable for quantifying nitrogen concentration the leaves contaning high concentration of chlorophyll. These products are also heftily priced. Thus it was a need to come up with the product which has a unique competitive advantage over the above products. Our innovation(product) is having a sampling area of 3cm, the GBNDVI parameter calculated is independent of the species(Leaf) and it does not get saturated as chlorophyll increases and thus better correlates with the nitrogen concentration in the leaves. It is portable, easy to use, unaffected by external light, cost-effective which is easily affordable for a common farmer
Proposed meter-Version 1
Principles
Reflectance
Wavelengths
3 specific wavelength LEDS
External influence
Not affected by sunlight conditions
Sampling Area
Measuring sampling area is 3 cm square
Time
Faster and easier to use
Detector
NoIR Camera, Array of Photodiode
Cost
$170-180
Sensitivity
Sensitive to the change in chlorophyll and do not get saturated
Apart from the above mentioned core technology used, the prototype could be integrated with drones for aerial inspection/imaging of field.
We are yet to conduct pilots in open fields. We have compared the results of our developed prototype with spectroscopy method (UV-VIS-NIR) Spectroscopy. Results are quite accurate.
We have database for more than 80 samples.
Actual system prototype is near completion or ready and has been demonstrated in an operational environment or is at pilot level.
- Artificial Intelligence / Machine Learning
- Imaging and Sensor Technology
Nitrogen, phosphorous and potassium are the three most vital soil nutrients required by plants, should be present in the ratio 4:2:1 to ensure healthy growth of cops. However, the current scenario for India sees a ratio of 6.8:2.7:1. This is due to the over fertilization of fields. Both over fertilization and under fertilization affects the quality and yield of crops.Thus, the idea is to develop an imaging system that can determine the chlorophyll status in the crops in the real-time. The problem it can address is:-Nitrogen application problems, low quality and yield of the crop, early disease detection in leaf, over fertilization which causes environmental pollution and groundwater contamination
- Rural
- Urban
- Poor
- Low-Income
- Middle-Income
- 2. Zero Hunger
- 3. Good Health and Well-Being
- 6. Clean Water and Sanitation
- 9. Industry, Innovation, and Infrastructure
- 13. Climate Action
- India
118 million farmers are in India. Considering just 2% of it as Service obtainable market and catering it to this 1% market in 3 to 5 years, the market is for 300 crore Indian rupees. Similar product cost 40,000 rupees to 1.25 lakh rupees. We are considering the selling price of this to 20k which has a margin of almost 70%.
We are planning to reach our to target farmers through distributors. To reach to data analytics company and FPOs, it will be direct b2b. We may reach them through our channel partners or with our own marketing team. We have not yet commercialized this technology. As far as acceptance is concerned, there are similar products which are available and are used by agricultural scientists and big farmers. The only challenge is to reach marginal farmers and convince them to invest in this technology.The project implementation for next 4-5 months
1-2 month: Packaging and Industrial design. /Improvisation in software
2-3 months - collecting large sets of data to implement AI/ML models to train the system for different applications.it will be ready in 5-8 months.
The innovation add more features like displaying image captured and real time monitoring of nitrogen status. Most of the existing instrument gives chlorophyll value only. Here we plan to offer early disease detection which causes major loss to farmers. Apart from that cost of these instrument is much lower than the market price of the competitive product. So, the innovation will have great impact in socio-economic aspects and will be useful for the agriculture research and common farmers can easily buy this. The only challenge is to reach marginal farmers and convince them to invest in this technology.
We are planning to reach our to target farmers through distributors. To reach to data analytics company and FPOs, it will be direct b2b. We may reach them through our channel partners or with our own marketing team
- Nonprofit
full-time staff = 2
Part-time staff = 3
Maryam Shojaei Baghini - Professor, Department of Electrical Engineering, IIT-Bombay
Rajul Patkar - CEO-SoilSens | Research consultant - IIT Bombay | Deputy State Convenor (MH) CIMSME
Praveen kumar Sah - Ex M.Tech IIT Bombay, Currently Electrical Engineer at Philips
Ekdeep Singh Lubana - B.Tech -IIT Roorkee
We are planning to reach our to target farmers through distributors. To reach to data analytics company and FPOs, it will be direct b2b. We may reach them through our channel partners or with our own marketing team. We have not yet commercialized this technology. As far as acceptance is concerned, there are similar products which are available and are used by agricultural scientists and big farmers. The only challenge is to reach marginal farmers and convince them to invest in this technology.The project implementation for next 4-5 months
1-2 month: Packaging and Industrial design. /Improvisation in software
2-3 months - collecting large sets of data to implement AI/ML models to train the system for different applications.it will be ready in 5-8 months.
- Organizations (B2B)
Financial aspect to develop more robust software and hardware, implementation , marketing, creating business model.
- Business model
- Solution technology
- Funding and revenue model
- Marketing, media, and exposure
MIT faculty to review and provide competency and feedback to develop more accurate and precision device.
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