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App for field trials and Pest Control

By: Sai Siddartha, Kamal and Sushrita

May 2017

Quoting Food and Agriculture Organization of the United Nations, "In many developing countries, farmers do not benefit from the advantages of using good quality seeds ..". To test whether certain seeds are suitable for a particular area, in this case Gujarat, researches give out seeds of different varieties for farmers to try out and monitor the crop and it’s yield. Based on which, good quality seeds are identified. Until now, researchers at NIF have been distributing seeds to the farmers and the collection of crop data is done by scouts who would visit the farms at regular intervals and manually collect data. A group of scouts would leave for the fields and collect data from the farmers. This process lasts for a couple of days depending on the number of crops and number of farmers who sowed them. If 5 varieties of seeds were given to 5 farmers of a single crop, scout has to visit each one of them, collect data, segregate and tabularize it according to the attributes involved and only then could researchers start working on evaluating the performance of seeds. Research in agriculture generally takes long since data at every stage of the life cycle of the crop is required and the intricacies of the process have to be recorded. This method of collecting data is only making it longer, the team strongly feels that this is a dire need.

 

Problem Statement 1.1:

The problem we have to understand and work on is, how to make this process more streamlined, less time consuming and efficient using a mobile app. The various fields and attributes that would help understand the health of the crop and any other requirements were implemented under the guidance of Prof Anil Gupta, Dr. Satya, Dr. Hardev Chowdhary and Dr. Noushad. The list of requirements as mentioned are listed below.

 

1. Profile:

Farmers when registering with the application are expected to create a profile in order to provide researches with the basic background and a specific data base for themselves. The following details are expected to provide a basic set of farmer’s details.

  • Name of the Innovator

  • Complete Address with Pin Code

  • Contact Number

  • Nearest City

  • Nearest Railway Station

  • Nearest Bus Stand

  • Education Qualification

  • Occupation – Present and Past

2. Stage and the growth of the crop:

To record and observe different stages of the plant growth.

  • Date of Sowing

  • Images of the crop sample after 15days

  • Images of the crop sample after 30days

  • Images of the crop sample just before Harvesting.

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3. Weather implications:

  • Temperature

  • Rainfall

  • Other abiotic stress

 

4. Study of the effects of weeds on plant growth.

  • Is the weed present or not? (Some weeds are predominant for some crops)

 

5. Data when harvesting

  • Qualitative (Germination percentage, Total Yield(in kg), Total area harvested, etc)

  • Quantitative (Disease instance: present/absent, Disease problem: major/minor, Variety performance: Bad/Good/Very Good,etc)

 

Some characteristics which are not genetically specific(height, number of branches, spike, etc) are to be collected for atleast 10 plants and the others specific for every plant.

In one of our field visits to demonstrate our App, we met Mr. Hajur Singh Bhai who is the caretaker of the NIF Farm. We visited the Brinjal plantation which was pest infested and the crop is in it’s flowering stage. The damage of the pest was very high and Hajur Bhai couldn’t identify the pest. Previous years’ brinjal plantation has never seen this pest. These situations are not uncommon and farmers use an array of pesticides which eventually degrade the soil’s nutrients.

 

Problem Statement 1.2:

Provide a common platform for researchers and farmers to share knowledge and tackle the estimated 10million insect per acre of land.(Earth’s surface are : 36.48 billion acres)

The pest control section of our app is aimed at identifying the pests and reducing over-usage of pesticides. Farmers can fill in the details and add pictures of the pest infestation, this query can then be answered either by the researchers from NIF Lab or a fellow farmer(Solution suggested is first verified). This app is also aimed at bridging the gap between traditional and scientific knowledge. Farmers can add their knowledge of solutions to various pests, which after being verified, are made public for all the farmers. For instance, we met Mr. Talja Bhai who showed us the crop of Mag, which was grown using very little water and almost no fertilizers. He claims that this is the best way to grow mag and won’t cause any pest infestation since there is no moisture. We asked him to add his solutions and innovations in the app and he’s hoping this would help his fellow farmers.

The requirements of this section are listed:

 

1. Possible Abnormality:

Any abnormality that the farmer spots can be shared with the researchers. It could be classified as Insect- Pest or Disease or Nutrient Deficiency. If it’s identified as pest farmer can identify the abnormality,

  • Classification of Abnormality : Major/Minor

  • Name of the Abnormality: Local English(Optional)

  • Symptoms of the abnormality - Images

  • Extent of the damage for all the three mentioned : Scale(1-3)

 

2. Present Solution:

This section is intended to record and share any traditional or experiential knowledge of the farmers and also for researches to share knowledge that may not be known to the farmers.

  • Name of the material used

  • Source of the material used : Leaf, root,etc

  • Phonological Stage : Fresh fruit, ripen, dried, etc

  • Method of preparation : Composition of the ingredients and the order in which they are added.

  • Method of Application : Spraying on the leaves, mixing it with water for roots,etc

  • Dosage(ml)

  • Precautions(if any)

  • Source of Knowledge: Traditional/Own Innovation/Improvement

User Feedback from Field Visits:

The team visited farmers around Grambharti for their inputs on the app and the two main inputs that we received were:

  • To make the app compatible in Gujarati and Hindi along with English.

  • To add more crops and specific details.

We updated the app with Gujarati and Hindi on the PlayStore. Adding more crops and localize it to other states of the country would be the future scope.

 

Technical Aspects:

The app is compatible with Android Versions 4.1 (Jelly Bean) and above. It is developed using Android Studio.

 

Process of Understanding the problem:

The team discussed the problem with the researchers at NIF Lab and found that the requirements they were seeking. Prior art search revealed that there is a similar app by ICRISAT, PlantIX. The details of the requirements and it’s mapping to the app was discussed and brainstormed using the mind map approach that was introduced to us. There are two mind maps, the second one with updated requirements. The images of the mind maps:

Ideas neglected:

The first conception of the problem statement by the team was to make an app which was to work with little involvement by the researchers. The plan was to train the system with the data base available using neural networks and respond with the computed solution. In case there is no match beyond a threshold value, researchers could be prompted.

 

Existing challenges and future scope:

The app is limited for paddy and farmers have requested it to be a multi crop app. The app presently does not allow filling data offline and upload it when the device goes online. This is a key feature since network is erratic in the regions we’ve visited. Currently, the app is specific to Gujarat, it could be extended to other parts of the country. This would help share knowledge, farmers from across the country could share knowledge resulting in efficient use of pesticides and usage of good seeds.

 

Acknowledgements:

The team is extremely grateful to the farmers’ support and hospitality. They’ve given us honest feedback regarding the app and on a personal level, they’ve been the kindest. Special Mention, Hajur Singh Bhai, who has helped us connect with more farmers and willing to share the app in the farmers’ whatsapp group and help farmers’ use it. The team feels fortunate to work with Dr. Satya, Dr. Noushad, Dr. Hardev and Prof Anil Gupta who have given us feedback constantly and helped us make it better at every stage.

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