Agriculture is the backbone of India. It is the major support to the Indian economy. The money flow starts from the farmer’s hand as that is where the essential food products make their entry. Almost 70% of the people live in rural basins with more than 50% of the whole Indian population taking agriculture as their main work.
India is the second-largest producer of fruits and vegetables in the world. Still, the sector suffers from a number of issues including ignorance and non-recognition. Climate change, unpredictable monsoon, drought, floods, migration of farmers towards cities for better jobs are some of the major distress that agriculture industry goes through.
Even the most acknowledged platform like media fail to cover field agriculture and go after agriculture ministers in the country to cover the issues which lack the farmers part. As institutions failed to provide loans and farmer welfare schemes, it is time for the Data science technologies to take over the far left behind the sector.
Agriculture is standing next in the line to IT, banking, manufacturing, finance, healthcare in Data Science making its entry. The platform features several applications in which the agriculture industry could further curtail its wings.
Some applications of data science in the agriculture sector
Finds soil type and features crop mapping
Every time a crop is reaped from the land, the soil structure changes. It is hard to find the crop that would next suit the soil type. Some people in the agriculture industry maintain acres of land which makes it difficult to penetrate the potential problems in the other corner of their land piece. Data science has a solution for all this.
The building of digital maps for soil types and properties could make things easier. Developed countries like Ireland use this technology to monitor the soil and land with the help of satellite. This aid in finding a solution quickly as it scans and gives an answer to what kind of crop could fit in the soil and reap most income.
Weather forecast to keep a check on crops health
A bad rain could soak the whole farm and earn zero penny while a no rain signal for too long could preferably yield the same. Therefore, weather plays a vital role in agriculture growth, development and yielding of crops. Even after it is reaped, the condition of which it is transported and stored plays critical. The quality of the crops depends adversely on the weather. That is why data experts have come up with a solution to use tools to identify the weather scenario. The findings brought about remarkable changes by sifting through database and studies to conclude things like the weather in the agriculture process.
Major elements that feature the agriculture forecast are,
• Rainfall and snow
• Wind speed and direction
• Humidity level
• Amount and type of coverage of clouds in the sky
• Low-pressure areas, cyclones, tornadoes and depression
• Sudden catastrophic changes like fog, frost, hail, thunderstorm and wind squalls
A Canada based company named Farmers Edge takes daily satellite image of farms and combines it with relevant data which includes more than 4000 interconnected weather stations.
Fertilizer suggestions through keen diagnosis
Maintaining a field is like an art. Fertilizer is an important colour that needs to be added to the art piece to make it look good. But often, farmers end up choosing unsuitable fertilizers for their crops which further leads to spoiled or unhealthy products out of it. Knowing the exact fertilizer rate is a science and requires a thorough analysis of multiple factors. The parameters on which the crop gets detected include crop nutrient uptake rates, research data, soil chemical, physical and biological properties, weather, water composition, land type, soil testing methods, irrigation techniques, fertilizer characteristics, interactions between fertilizers and many more.
Misuse and wrong prediction on fertilizer usage is a global phenomenon. But with the emerging technologies, data science professionals are now able to advise the farmers on what fertilizer suits their land and crops.
Suggests pesticides and detects crop diseases
Pests and diseases are a threat to crops. Ignorance of such issues or wrong treatment could make the crop unhealthy and spoiled. Analytics is providing advanced algorithms which could identify the pattern and behaviour of nature that helps in forecasting the invasion of pests and the spread of microscopic diseases.
Data science is informing the farmers how to manage pests. Digital tools and data analysis in agriculture are being utilized to scientifically deal with harmful insects. Some companies have organized data science professionals to sensitize farmers on pesticide usage through user-facing platforms.
The images captured through drones help find the difference between good and bad pests. The solution given by data science professionals makes way to killing only the bad pests leaving the good insects to enrich the crop state.
Automated irrigation system to minimize water use
According to a study by WWF, water is becoming scarcer worldwide. It is predicted that one-third of the total population will end up facing water shortage in 2025. Water bodies might cover 70% of the total planet area, but only 3% of it is fresh and available to use. At a time when every drop of water matters, agriculture industry should also take the initiative to use minimum water in a much useful way.
The technological solution that is provided by data science for the issue is automated irrigation system. One kind of automated irrigation system functions based on small scale farms while the other uses weather predictions. By the process of drip irrigation, the use of water could be minimized on a global scale.
DATOS, a risk reduction application functions on the current advancements of computing technology and applies in the fields of Geographic (GIS), Remote Sensing (RS), Artificial Intelligence (AI) and data science. The DATOS project has developed a map using satellite images and extracts the temporal signature of crops. It is capable of detecting the flood situation in areas through AI help.
Currently, the manoeuvre of Data science and the researches on its diverse usage in the agriculture sector is less; it is predicted that the opportunities will multiply soon. Technology has advanced on a vast scale in the agriculture sector. It is no wonder even if a desert grows useful food crops in future.