Tuesday, October 29, 2019

Can we predict the yield before harvest?? Yes! We CAN, technology is here: Case study of Soybean in Dewas 2019.

Through Fasal Salah App, approximately 150,000 Lakh farmers are linked to us on one to one basis. These farmers are cultivating different crops. The sowing date, variety and agriculture management practices follows by them are received at the back end for analytical purposes. Based on these input from farmer’s yield determining factors like temperature, humidity, sunshine is crunched into a dynamic crop model specially developed for this purpose . We selected soybean as crop and Dewas of Madhya Pradesh as area of study. Dewas is situated between North latitude 22o 17’00” & 23o 20’00” and east longitude 22.962267, 76.050797 and covers 7,020km sq area .
Study Area

This study covered about 1200 farmers cultivated soybean who were connected on Fasal Salah App. Through this app farmers received weather basis advisory based on crop physiology of soybean being cultivated in real time. Farmers in farm were providing feedback of management practices being followed by them for application of farm input such as fertilizer, application of pesticides etc.

Besides, farmers also forward their crop pictures on weekly basis which helps us to monitor their crop more precisely. We ran artificial intelligence on the pictures received which fine tunes the crop yield determination by the dynamic model.  It is note worthy that the farmers field are
geo-located as also all the pictures received from them are geo located. This help us in correlating the ground recorded vegetation index with high resolution satellite data (In this case Sentinel-2A and Its NDVI are used). In this process we are able to expand the area of interest beyond the limits of farmers on Fasal Salah App.
Normalized Difference Vegetation Index (NDVI) of Dewas district were obtained. Collected GPS coordinates of soybean field were overlaid over calculated NDVI and NDVI values of each field were recorded as training sets. The refined training set data statistics were used for performing maximum likelihood supervised classification based on recorded vegetation data.

With this methodology we have estimated area under soybean in Dewas district for year 2019, to be 3.8 Lakh hectare. The average yield determined by the hybrid of crop model and crop pictures for Dewas district based on input from farmers using our Fasal Salah App came to 813 kg  per hectare thus total yield of soybean in Dewas district expected to be 3,078,000 Quintal in Kharif 2019.

While actual field estimates are yet to come this figure will stand the test of time when official results are posted. 

I would like to remind that this year Dewas experienced some excessive rains. Our calculations take into account such damages because of excessive rains. However what is not accounted for is the damage because of floods.

The innovation  which made our team win The Agriculture Grand Challenge 2019 and was awarded best App for Agriculture by Indian Mobile Congress 2019 ( all Mobile operators of India  form this congress)  is ready to be used  by the  Industry for actionable market intelligence for commodity trading. 

Come join our innovation


Thursday, February 7, 2019

BKC Aggregators LLP, winner of HDFC's digital innovation summit

Good, better, best and never take rest until your good becomes better and better become best; it is the principle which is followed by Dr BK Singh, who is working tirelessly for the welfare of farming community across the country.

After bagging Agriculture Grand Challenge (Govt. of India) 2018, once again his newly incubated BKC Aggregators LLP has become winner of HDFC's Digital Innovation Summit which was organized in  Gujarat on 31st January 2019.
BKC Aggregator is declared winner for its app "Fasal Salah" which provide timely and personalised agri- advisory for the welfare of farmers, a perfect solution for several problems being faced by farmers.

Using dynamic crop models and artificial intelligence analytics BKC has been able to generate an algorithm for calculation of yields well before the harvest. Thus it is possible now to have an accurate estimate of the crop before it is harvested by the farmers. Forecasting the yield before harvest is going to become strong tool for several problems associated to the losses and difficulties being faced by farming community and insurance agency as well, as agriculture is a sector which is a gamble of monsoon and bundle of risks we need adequate solutions for win-win situation.

Aggregation of this technology on mass scale will lead to a situation where in the production estimate of the crop will be available in good time for planning of import as well as exports This could also act as a tool for Crop Insurance where in the inspector will no longer be required to go and inspect the crop to assess the damages and process the insurance claim.

Tuesday, January 29, 2019

Tecnology - Advising Farmers and Crop Estimation

Food security in the light of climate change is a global imperative. In developing nations, the problem is exacerbated by variable weather, lack of reliable extension services to optimize yield and fair market access.

In India, most farmers do not have access to weather advisory forecasts that are hyper local to their field and timely in nature. As all farming activities are heavily dependent on weather, decisions on application of fertilizers and pesticide, irrigation, and even plucking of fruits & vegetables and harvesting cannot be taken efficiently. In addition, significant crop losses, that are entirely preventable, accrue through adverse weather events.

Crop advisory services, where available, are generic and not pegged to a farmer's seed variety, date of sowing, and growing conditions and hence do not dispense timely, actionable advice, directly relevant to a farmer.

Likewise, market trends pertinent to their particular crop and location are not available. BKC Aggregator is entrenched in bridging these gaps for individual farmers using data science and software and has developed a scalable solution that can address each farmer in India, individually, to optimize their yields and reduce losses.

Our solution is two pronged: help farmers optimize yields and income; predict yield in advance of harvest for better positioning in markets. Through our app FASAL SALAH, farmers are guided throughout the crop cycle-hyper local weather forecasts, how to prepare the field, seed availability, where to buy inputs, hire implements, application of fertilizers and pesticides, when to harvest, what to do after harvest, where to sell products and latest techniques of preservation. Farmers also send their crop pictures in prescribed manner and intervals for remote yield estimation and improving advisories.

We are with farmers all the time as FASAL SALAH works as their personal adviser.

FASAL SALAH serves ~120, 000 farmers across India. A farmer's location, seed variety, and sowing date are ascertained. Then using dynamic weather-based crop modeling, IoT, and automated image processing techniques, their crop is monitored remotely. Dynamic advisories that change with changing weather patterns are available round the clock. Crop pictures are analyzed for remedial measures and arrival of yields before actual harvest .
FASAL SALAH also provides market trends, prices, news, and has evolved into a trusted platform for meaningful interactions in the communities it serves.

We also predict crop yields and production quality. Thus, along with farmers, food processors benefit by taking a position in advance and making gains on the commodity market. Our technology is scalable to multiple geographies.

Problem it is solving

We are solving 2 problems:
1. Timely crop advisories to Individual farmers therough our app Fasal Salah
2. Crop yield estimation prior to harvest using dynamic crop model n crop pictures with IA

Aggregators -How it all started: Founder CEO

Aggregators -How it all started: Founder CEO: Dr.BK Singh holds a Ph.D. degree in agriculture from Indian Agricultural Research Institute Delhi and has served Govt Ow...