Farming Blogs

Lentil: Area and Yield survey in UP and MP

Farmonaut did Lentil satellite survey of Lentil in states of major districts Uttar Pradesh and Madhya Pradesh in the year 2022-23 which showed area of Lentil increased in Uttar Pradesh by 3% over last year in major districts and yield increased 7% over last year, and yield in Madhya Pradesh increased by 4% over last year in major districts.  

In Uttar Pradesh, Jhansi reported highest rise in area in area with rise of 15% over last year at 31.34 thousand hectares followed by Bharaich which rose 6% over last year at 55.67 thousand hectares while Jalaun reported largest fall in acreage by 6% to over last year at 29.45 thousand hectares followed by Mahoba which saw a fall of 2% over last year at 31.33 thousand hectares. Similarly, Bahraich showed highest rise in yield by 10% over last year at 937.97 Kg/Ha followed by Jalaun  showing a rise by 7% over last year at 902.92 Kg/Ha while Lalitpur showed lowest increase by 2% over last year at 859.70 Kg/Ha followed by Shravasti which rose by 4% over last year at 865.53 Kg/Ha. The highest area was reported in Bahraich followed by Banda which showed increase of 1% in area over last year at 36.56 thousand hectares. Moreover, highest yield was reported in Jhansi which rose by 6% over last year at 978.78 Kg/Ha followed by Bahraich. Highest production was reported in Bahraich at 52.22 thousand tons followed by Banda at 32.02 thousand tons while the lowest production was reported in Shravasti at 16.72 thousand tonnes followed by Lalitpur at 18/33 thousand tonnes. The total area in major districts of UP rose by 3% over last year at 279.88 thousand hectares and average yield for the state rose by 7% and is reported at 905.51 Kg/Ha. Overall, the total production for 2022-23 in major districts of Uttar Pradesh was reported at 253.44 thousand tonnes. 

Similarly in Madhya Pradesh highest area was reported Sagar at 95.91 thousand hectares followed by Vidisha 71.32 thousand hectares while the lowest area was in Panna at 19.23 thousand hectares followed by Ashoknagar at 28.67 thousand hectares. In Madhya Pradesh, yield rose the most in Damoh by 11% over last year at 1136.36 Kg/Ha followed by Vidisha which rose by 7% over last year at 973.24 Kg/Ha  while it fell most in Dindori by 5% compared to last year at 896.85 Kg/Ha followed by Narshinghpur which fell by 1% over last year at 900.19 Kg/Ha. Moreover, highest yield was reported in Damoh followed by Vidisha at 973.24 Kg/Ha. Similarly, highest production was reported at Sagar at 87.03 thousand tonnes followed by Vidisha at 69.41 thousand tons. Lowest production was reported in Panna at 17.72 thousand tonnes followed by Narshinhpur at 30.0 thousand tonnes. Average yield of the major districts Madhya Pradesh were reported higher by 4% over last year at 951.36 Kg/Ha. Overall, the total production for 2022-23 in Madhya Pradesh was reported at 396.69 thousand tonnes. Favourable weather in both Uttar Pradesh and Madhya Pradesh led to higher yield in both states.

Farmonaut is revolutionizing agriculture through satellite data with a vision to help farmers and agriculture enthusiast worldwide in cost-effective way. By providing data on Crop Health, water stress, Weather forecasts and many more; the agriculture industry can make informed decisions about crop management. As climate change continues to posses’ risk on Agriculture industry, Farmonaut’s services can play a crucial role in mitigating risks. 

By utilizing Farmonaut’s platform, farmers an access up-to-date information on vegetation water stress, evapotranspiration, soil organic carbon and weather forecasts, allowing them to make data-driven decisions on fertilization, pest management, irrigation needs and advisory. This proactive approach to crop management can potentially help mitigate the effects of climate change, reduce the risk of lower crop yields, and decrease inflationary impacts on food prices.

With over 1 million hectares of farmland monitored, Farmonaut is providing data to farmers and corporates worldwide. Some of our major clients/partners include Godrej Agrovet, ITC Limited, Coromandel International, Troforte Fertilizers, Australia, FFBS Germany and so many more!

Land Use Land Classification

Land classification is basically providing information on the type of activity taking place on the land and categorizing it. The land uses are of different types such as for industrial use, residence use, rural, urban, water reserves, agriculture area, etc. It can be classified and displayed through remote sensing using the satellite. Remote sensing would provide reliable and accurate information on the land use.

Benefits of LULC

Land Use Land Classification helps the private and government institutions in following ways:

 

  • Initiate in formation of policies and schemes for development.

  • Know the land utilization aspects 

  • Helps in managing, monitoring and planning at district, taluka and village level.

  • Keep an eye on the urban and rural development over years.

  • Study the changes in the environment.

  • Create a sustainable solution for future development.

  • Check the progress in every sector such as agriculture, forest, industrial, etc.

New Addition by FARMONAUT

Farmonaut has recently added a new feature to their application which majority can be useful to the industries and government as a whole. The feature added can be said as Land Classification based on its use. The Land on district level, taluka level or village level can be classified based on the activities being carried out. However there are multiple use cases to such addition being made by Farmonaut. We have been providing services to individual farmers and corporations on a large scale in the field of agriculture. With addition of land classification through satellite monitoring, we tend to help institutions beyond agriculture.


As stated above the benefits of land classification for institutions in a vast range, Farmonaut has received a request from their former client to introduce such features for their own use.

How to use Land Use Land Classification?

Step 1: Login to your account on the Farmonaut application.

Step 2: Select the farm you want the Land classification for.

 

 

 

 

Step 3: Open the dropdown menu of the Map controls on the left.


Step 4: Click on the “LULC” button under the For Land Use Land Classification.

Step 5: The image will be displayed on the map.

 

 

Step 6: Analyze using the color coding provided.

Soil Testing : Introduction

Soil tests are conducted on one or more varieties of soil for knowing the health of soil or to analyze various possible soil parameters. Soil testing is majorly performed in Agriculture and construction industries to possibly know the health and to get better results. However, in India agriculture isn’t much aware about the importance of soil testing for crop health and soil health.

The parameters involved in soil testing are Soil temperature, Soil pH, Nutrients such as N, P, Mg, K, Cl, etc.

Importance of soil testing in agriculture

In agriculture, 60% of crop yield depends on soil fertility which accounts into making sure of the good quality of soil. With better quality results in better yield of crops. Some other importance of soil testing can be as follows:

  • Know the current health of soil and improve it: Testing reports provides various soil parameters which would be helpful to know the condition and add on the required nutrients or maintain the soil moisture as well. Eventually results in better soil fertility and higher yield.

  • Avoid soil erosion, degradation, etc: With each year soil fertility has been decreasing due to erosion which has caused imbalance in soil management. Also, soil degradation affects the livelihood and health of people. However, Soil restoration is a costly and time consuming process hence, soil management is the efficient and effective way of maintaining soil conditions.

  • Minimize the use of fertilizers: Excess use of fertilizers can degrade the soil quality and fertility. With soil reports excess use of fertilizers can be avoided.

  • Decrease the cost: Unawareness of excess fertilizers used in the farms, the cost of fertilizers and labor increases. It can be reduced by knowing the required amount of fertilizers.

  • Maintain uniformity in nutrients across fields: the soil testing provides all the nutrients data as well which gives an idea to the farmers on what nutrients are to be used. Soil samples from different locations on farms would help to maintain uniformity in the soil nutrients along the field.

  • Improve in yield: Knowing all the parameters of soil would result in better soil quality and improve the yield.

SOIL SAMPLING

Soil sampling is done by the farmers by collecting the soil samples from different locations on the farms. It is basically the soil collected from different locations of the farms (based on the area) and sent to the labs for knowing the nutrients and soil health. The soil must be clean from plants and must be taken from a depth of 6-12 inches (varies according to the test).

What FARMONAUT offers?

Farmonaut, along with crop health monitoring, has introduced a feature to reduce the work of farmers and help them in efficient soil testing procedures. Soil reports can be obtained by the Farmonaut platform. The feature is currently available on the web application of Farmonaut, they have been working to provide the same on mobile application as well. The farmers already associated with Farmonaut have been using this feature for soil testing their farms. They have also been providing the services to businesses and individual farmers as well. Troforte Innovations is an example of using this feature for their farmers in collaboration with Farmonaut. 

 

The soil testing would as follows:

  1. COLLECTION OF SOIL: The farmer must collect the soil from his/her farm from different locations in the bags. The bags provided have barcodes with 8-10 digits on them for digital use.

  2. FORWARD THE SAMPLES: The bags are sent to the soil testing Labs for soil testing.

  3. TESTING THE SOIL: Soil testing Labs performs multiple tests nearly 10-15 tests. The tests help to identify various parameters such as pH, EC (electric conductivity), Carbon content, Saturation percentage and Nutrients like Potassium, Nitrogen, Magnesium, Phosphorus, etc.

  4. UPLOADING THE RESULTS: The result of soil tests were obtained manually by the farmers. Farmonaut has made it easier through technology which provides the data digitally on their devices. The soil testing labs can upload the results of the tests through API endpoint which then will match with the barcode added by the farmers in order to display the results on their device.

  5. EASY ACCESS TO RESULTS: The access to the soil tested data can be gained by scanning the barcodes on the bag. The farmer/user have to add the field and the soil sample information which includes 3 data points as shown in the figure below: 

  • Select the field: The field must be selected from the fields that have already been marked/geotagged by the user.

  • Barcode: The barcode can be scanned or barcode number can be typed by the user.

  • Sample Location: The user has to select the location on the map from where the soil sample was taken.

The platform has an option “REPORTS” which displays the soil results and also helps to add the soil sample data as above. After adding the field if the results of the test are available it shows Purple color otherwise gray if results are not available.

The reports that are obtained from the testing labs included more than 100 parameters. Also, the user can easily search for the parameters they need.

conclusion

Soil fertility has been a major issue over the past years in agriculture production. Soil sampling is done by the farmers from their farms which is then sent to testing labs. The reports generated were manually sent to the farmers which may take more than a day. To overcome this, Farmonaut has come up with a service that provides data with ease to the farmers on their devices just by a few clicks.

Wheat Yield Calculation in Saharsa (Bihar) Based on Remote Sensing

Introduction:

Yield calculation of the crop is very important for assessing the production and it depends on many variables like soil, weather, agricultural practices (date of planting, amount of irrigation and fertilizer use), seeds, pests, weeds, biotic stress plant varieties etc.

Remote sensing provides an effective and efficient way to forecast yield. Remote sensing has been widely used by many institutions across world to calculate area and yield of a crop.

In this paper, we focus on forecasting yield of wheat based on data from Sentinel-2 satellite data. The study area was wheat crop in Saharsa (Bihar). The crop is in advanced stage and has vegetated fully and harvest is expected in next 20-30 days.

Methodology:

Data from Sentinel-2 was used and random fields were selected from the mapped area and yield was calculated using NDVI (Normalized Difference Vegetation Index) and LAI (Leaf Area Index).

Farmonaut platform was used to map fields to create bounded regions (fields) as shown in Figure-1. On the dates of observations the sample fields were free from clouds and normal data was observed. Crop classification was done manually by ground truthing to ascertain the crop is standing in the field.

Figure-1 Comparison of peak NDVI in 2022 Vs 2022 wheat crop

Figure-2 Comparison of peak NDVI in 2023 Vs 2021 wheat crop

NDVI was used to calculate yields for the given fields which means peak vegetative growth rate. Peak vegetative growth helps to forecast yields more accurately.

Below are the observations of NDVI of the various fields. The maximum NDVI was reached on 11-Feb-2023 compared to 8-March-2022 and 21-Feb-2021. From the NDVI, LAI was calculated which was subsequently used to calculate yield. This approach is being used after going through a lot of available texts and final model was considered.

In this procedure the estimated LAI was used with WTGROWS model for yield mapping. This model suggests direct correlation between grain yields and LAI. This relationship was applied to all the fields to calculate yields.

NDVI started to rise after planting of crop in November continued to rise until 11-Feb-2023 which is 10 days before normal peak NDVI, making the inappropriate for calculating yield. So, the next NDVI read on 16-Feb-2023 was used to calculate yields. The NDVI started falling after 11-Feb-2023 and will fall until harvest. Best results of yield are obtained when the NDVI is maximum. However, if it reaches its peak NDVI before time and falls sharply then max NDVI is not the best barometer and the next 2 NDVI reads are very important.

NDVI and LAI showed the best correlation for the estimated yields. The yields ranged from 3.35-3.64 compared to 2.87 Tons/ha to 2.98 Tons/ha last year (2021-22) and 3.5 Tons/ha to 3.7 Tons/ha in (2020-21).

Figure-3

  Area (sq. m.) 01-Feb-23 11-Feb-23 16-Feb-23 21-Feb-23 Maximum LAI Estimated Yield Kg/ha
Field 1 3600 0.7 0.7 0.6 0.4 1.827376043 2981
Field 2 7700 0.67 0.7 0.6 0.4 1.827376043 2981
Field 3 1500 0.7 0.69 0.6 0.39 1.80621064 2963
Field 4 3100 0.7 0.7 0.6 0.39 1.80621064 2963
Field 5 6600 0.68 0.65 0.59 0.34 1.684268057 2853
Field 6 2700 0.66 0.67 0.6 0.4 1.827376043 2981
Field 7 2000 0.65 0.62 0.6 0.34 1.704004521 2871
Field 8 4300 0.57 0.67 0.6 0.4 1.827376043 2981
Field 9 1700 0.65 0.63 0.68 0.35 1.892372025 3036
Field 10 3700 0.71 0.7 0.6 0.4 1.827376043 2981

Figure-4

  Area (sq. m.) 26-Feb-22 03-Mar-22 08-Mar-22 13-Mar-22 Maximum LAI Estimated Yield Kg/ha
Field 1 3600 0.4 0.5 0.5 0.44 1.827376043 2981
Field 2 7700 0.4 0.5 0.5 0.43 1.827376043 2981
Field 3 1500 0.4 0.48 0.5 0.45 1.827376043 2981
Field 4 3100 0.4 0.49 0.5 0.43 1.827376043 2981
Field 5 6600 0.4 0.44 0.49 0.4 1.785290384 2944
Field 6 2700 0.39 0.43 0.47 0.4 1.704004521 2871
Field 7 2000 0.4 0.48 0.49 0.42 1.785290384 2944
Field 8 4300 0.4 0.44 0.48 0.41 1.744173984 2908
Field 9 1700 0.4 0.46 0.5 0.44 1.827376043 2981
Field 10 3700 0.4 0.49 0.5 0.48 1.827376043 2981

 

Figure-5

  Area (sq. m.) 01-Feb-23 11-Feb-23 16-Feb-23 21-Feb-23 Maximum LAI Estimated Yield Kg/ha
Field 1 3600 0.6 0.7 0.7 0.7 2.912119253 3713
Field 2 7700 0.6 0.7 0.69 0.67 2.912119253 3713
Field 3 1500 0.59 0.7 0.7 0.69 2.912119253 3713
Field 4 3100 0.6 0.7 0.7 0.69 2.912119253 3713
Field 5 6600 0.59 0.7 0.68 0.67 2.912119253 3713
Field 6 2700 0.57 0.7 0.68 0.67 2.912119253 3713
Field 7 2000 0.52 0.64 0.64 0.64 2.532181241 3493
Field 8 4300 0.59 0.7 0.7 0.7 2.912119253 3713
Field 9 1700 0.52 0.65 0.66 0.64 2.591873781 3530
Field 10 3700 0.6 0.7 0.7 0.69 2.912119253 3713

Figure-6

Observations and calculations:

The early Max NDVI occurred due to warm winter, dry conditions, less clouds and heat tolerant yield variety. The early NDVI reached and forecast of high temperatures will adversely impact yield of the crop. Generally peak NDVI reached by 20-28 Feb but this year it has reached 10 days before and the average temperature is much higher than normal temperature and forecasted temperature is almost 10 Degree Centigrade higher than normal year will adversely affect yield in maturity stage. Higher NDVI reached before due date is abnormal and due to that peak NDVI is not used here but the next reading on 16-Feb-2023 was used to calculate yields. Also, the fall in NDVI is much sharper than 2021-22 and 2020-21 which shows that there will be major fall in yields.

Also, the average max temperature in the crop season was above corresponding period last year and 2020-21 and humidity and cloud cover were significantly lower than 2021-22 leading to more sunlight and higher temperatures on the crop thereby affecting the quality of crop and lower yields. Lower humidity leads more sunlight in winter and if temperatures remain above average than it impacts yields. Also, there is forecast of temperatures reaching 38 Centigrade by March 5 will adversely impact crop when it is in maturity phase.

In the Figure 1, there is comparison of peak NDVI of 2022-23 wheat crop vs 2021-22 while crop showing that last year wheat crop was in worse condition than current year and the average yield was 2.96 Tonnes/Hectare in the above plot while this year the average yield in the above 10 fields are 3.37 Tonnes/Hectare which is approximately 14% above last year and 9% lower than 2020-21. The data was corroborated with discussion with Krishi Vigyan Kendra- Saharsa which said the peak crop yield will fall for late shown non heat resistant varieties and heat resistant varieties have low yields. Advisories have been given to irrigate fields and use micronutrients to mitigate fall in yields. Also, heat resistant varieties have yield in the range of 3.5-4.0 Tonnes/Hectare. Long Period Average yield of rice is 4.3-4.5 Tonnes/Hectare for normal varieties which are sown on time. The yield in 2022-23 is 3.37 Tonnes/Hectare was 2.96 Tonnes/Hectare last year which is approximately 25-30% lower than Long Period Average but 14% higher than last year. The crop will be ready to harvest by End-March-2023 compared to mid-April last year and start of April in 2020-21.

Results:

Data from our observation show that the average yield is 3.37 Tonnes/Hectare compared to 2.96 Tonnes/Hectare in the same fields last year. The yield ranges from 3.31 Tonnes/Hectare to 3.64 Tonnes/Hectare compared to 2.87 Tonnes/Hectare to 2.94 Tonnes/Hectare last year and 3.4 Tonnes/Hectare to 3.71 Tonnes/Hectare in 2020-21.

The above-mentioned forecasted yields can vary depending upon weather and other unavoidable factors before harvest. If normal condition prevail then the above yields can be achieved subject to error of 10%.

The researches done in the area of yield forecasting of field crops by remote sensing has demonstrated good results. With the help of new sensors and indexes, researchers can calculate yields with less errors in future.

 

Global economic slowdown will reduce exports and slow Indian economy, causing income and inflation issues. This will particularly impact farmers and the poor due to peak food inflation.

 

Farmonaut is revolutionizing agriculture through satellite data with a vision to help farmers and agriculture enthusiast worldwide in cost-effective way. By providing data on Crop Health, water stress, Weather forecasts and many more; the agriculture industry can make informed decisions about crop management. As climate change continues to posses’ risk on Agriculture industry, Farmonaut’s services can play a crucial role in mitigating risks. 

By utilizing Farmonaut’s platform, farmers an access up-to-date information on vegetation water stress, evapotranspiration, soil organic carbon and weather forecasts, allowing them to make data-driven decisions on fertilization, pest management, irrigation needs and advisory. This proactive approach to crop management can potentially help mitigate the effects of climate change, reduce the risk of lower crop yields, and decrease inflationary impacts on food prices.

With over 1 million hectares of farmland monitored, Farmonaut is providing data to farmers and corporates worldwide. Some of our major clients/partners:








Written By:

Dipanker Gyan

 

CONTACT US AT:

BIGGEST RISK
FOR INDIA IN 2023

The biggest risk India is facing is the risk of climate change. Climate change effects yield of crops, lower cropped area and droughts. Higher temperature in March 2022 led to lower yield of Wheat in 2022 and erratic monsoon led to lower yield in Rice. Hit in both the crops has led to severe cereal inflation. The government is struggling to bring down prices of cereals as it impacts the most impoverished. Even with free distribution of 5 kg of grains for 80 crore people has led to lower stocks of wheat and rice in central pool. This has led government to close the scheme in December. 

 

With India having high food component in headline inflation, the risk of inflation induced by climate change effects the whole economy. It forces RBI to slow down economy by raising interest rates despite weak aggregate demand at the lower end of pyramid, nascent recovery after 3 years of adverse impact by Corona pandemic.

Various climate agencies are predicting more than 50% probability of EL Nino in 2023 which reduces the monsoon intensity in South Asia. The heating of Pacific leads to drought in Southeast Asia which produces palm, rubber, rice, sugarcane, pulses etc faces risk of reduction of production stroking inflationary impact on these prices which are directly related to Indian prices as India imports palm oil, rubber, pulses etc. The risk of lower rains will affect the already adverse supply position of agriculture products in the market.

 

The consumption in the lower end of pyramid is facing distress since 2018 will face lower income and higher inflation of goods especially food. The government will have either close exports of many agriculture commodities or forced to import more. With the war in Ukraine impacting the Agri Supply chain of grains to sunflower oil will adversely impact ability to import and the imported inflation of food items.

 

Global economic slowdown will reduce exports and slow Indian economy, causing income and inflation issues. This will particularly impact farmers and the poor due to peak food inflation.

 

FARMONAUT:

To Reduce Risk

To mitigate the incoming risk faced due to weather change, Farmonaut is providing its technology and data analytics.

Farmonaut is revolutionizing agriculture through satellite data with a vision to help farmers and agriculture enthusiast worldwide in cost-effective way. By providing data on Crop Health, water stress, Weather forecasts and many more; the agriculture industry can make informed decisions about crop management. As climate change continues to posses’ risk on Agriculture industry, Farmonaut’s services can play a crucial role in mitigating risks. 

By utilizing Farmonaut’s platform, farmers an access up-to-date information on vegetation water stress, evapotranspiration, soil organic carbon and weather forecasts, allowing them to make data-driven decisions on fertilization, pest management, irrigation needs and advisory. This proactive approach to crop management can potentially help mitigate the effects of climate change, reduce the risk of lower crop yields, and decrease inflationary impacts on food prices.

With over 1 million hectares of farmland monitored, Farmonaut is providing data to farmers and corporates worldwide. Some of our major clients/partners:

 

Written By:

Dipanker Gyan
Shivani Dudhatra

FIND AND

CONTACT US AT:

Introduction:

Yield calculation of the crop is very important for assessing the production and it depends on many variables like soil, weather, agricultural practices (date of planting, amount of irrigation and fertilizer use), seeds and biotic stress.

Remote sensing provides an effective and efficient way to forecast yield. Remote sensing has been widely used by many institutions across world to calculate area and yield of a crop.

In this paper, we focus on forecasting yield of wheat based on data from Sentinel-2 satellite data. The study area was wheat crop in Saharsa (Bihar). The crop is in advanced stage and has vegetated fully and harvest is expected in next 20 days.

Methodology:

 Data from Sentinel-2 was used and random fields were selected from the mapped area and yield     was calculated using NDVI (Normalized Difference Vegetation Index) and LAI (Leaf Area Index).

Farmonaut platform was used to map fields to create bounded regions (fields) as shown in Figure-2. On the dates of observations the sample fields were free from clouds and normal data was observed. Crop classification was done manually by ground truthing to ascertain the crop is standing in the field.

Maximum NDVI was used to calculate yields for the given fields which means peak vegetative growth rate. Peak vegetative growth helps to forecast yields more accurately.

Below are the observations of NDVI of the various fields. The maximum NDVI was reached on 21 Feb 2021 which was used to calculate yield. From the maximum NDVI, LAI was calculated which was subsequently used to calculate yield. This approach is being used after going through a lot of available texts and final model was considered.

In this procedure the estimated LAI was used with WTGROWS model for yield mapping. This model suggests direct correlation between grain yields and LAI. This relationship was applied to all the fields to calculate yields.

NDVI started to rise after planting of crop in November continued to rise until 21-Feb-2021 making the data as best date for calculating yield. The NDVI started falling after 21-Feb-2021 and will fall until harvest. Best results of yield is obtained when the NDVI is maximum.  

 

NDVI and LAI showed the best correlation for the estimated yields. The yields ranged from 3.5 Tons/ha to 3.7 Tons/ha.  Figure-1

 

 

 

Area (sq. m.)

16-Feb-21

21-Feb-21

26-Feb-21

03-Mar-21

Maximum LAI

Estimated Yield  Kg/ha

Field 1

3600

0.6

0.7

0.7

0.7

2.912119253

3713

Field 2

7700

0.6

0.7

0.69

0.67

2.912119253

3713

Field 3

1500

0.59

0.7

0.7

0.69

2.912119253

3713

Field 4

3100

0.6

0.7

0.7

0.69

2.912119253

3713

Field 5

6600

0.59

0.7

0.68

0.67

2.912119253

3713

Field 6

2700

0.57

0.7

0.68

0.67

2.912119253

3713

Field 7

2000

0.52

0.64

0.64

0.64

2.532181241

3493

Field 8

4300

0.59

0.7

0.7

0.7

2.912119253

3713

Field 9

1700

0.52

0.65

0.66

0.64

2.591873781

3530

Field 10

3700

0.6

0.7

0.7

0.69

2.912119253

3713

 

Results:

Data from government institution show the wheat yield in Madhepura district of Bihar ta 3.8 Tons/ha which is just next to Saharsa district.

The above mentioned yields can vary depending upon weather before harvest. If normal condition prevail then the above yields can be achieved subject to error of 10%.

The researches done in the area of yield forecasting of field crops by remote sensing has demonstrated good results. With the help of new sensors and indexes, researchers can calculate yields with less errors in future.

We will keep posting about any such informative information on to our blogs, to help as many people as possible. Farmonaut is built upon a vision to bridge the technological gap between farmers and strives to bring state-of-the-art technologies in the hands of each and every farmer. For any queries/suggestions, please contact us at [email protected]

We have some more interesting articles coming up soon. Stay tuned!

ESTIMATION OF THE YIELD OF POTATOES

INTRODUCTION

India is country which has an economy dependent on the agriculture. The production and distribution of agriculture is very much associated with the economy of India. Crop growth and yield monitoring over agricultural fields is an essential procedure for food security and agricultural economic return prediction. The advances in remote sensing have enhanced the process of monitoring the development of agricultural crops and estimating their yields. Achieving the maximum crop yield at the lowest investment is an ultimate goal of farmers in their quest towards an economically efficient agricultural production. Early detection of problems associated with crop yield can greatly help in reducing the loss and reaching the targeted yield and profit. Potato is classified as being the fourth major staple around the globe, which is still quickly attaining importance. The growing interest in potato, along with the diminishing agricultural lands, introduces the need for germplasm yield enhancement, better crop protection and much more efficient and productive management systems. Prediction of potato crop yield prior to the harvest period can be very useful in pre-harvest and marketing decision making. Many studies showed that traditional methods of crop yield estimation could lead to poor crop yield assessment and inaccurate crop area appraisal. In addition, these methods normally depend on rigorous field data collection of crop and yield, which is a costly and time-consuming process. Remote sensing (RS) and Geographical Information System (GIS) technologies can be used to assess the temporal variation in crop dynamics, including crop yield and its spatial variability. Visible (blue, green and red) and near infrared (NIR) portions of the electromagnetic spectrum have already proven their effectiveness in accessing information on crop type, crop health, soil moisture, nitrogen stress and crop yield. Advancement in RS techniques enhanced the use of multispectral images as an effective tool in determining and monitoring vegetation conditions, crop stress and crop yield prediction. Liu and Kogan revealed that remote sensing data offered exceptional spatial and temporal land surface characteristics, including the environmental impacts on crop growth. Numerous studies have reported that there could be a good correlation between the vegetation indices provided by the RS techniques and the crop yield and biomass. A crop yield research that is conducted at a regional scale, which employs coarse or low-resolution satellite images, can provide a broader information on the crop canopy conditions and crop yield estimates. Hence, decisions in the quantitative export and import of the product within the region could be made in assured way.

What environmental factors affect the yield?

 

Plant growth and geographic distribution are greatly affected by the environment. If any environmental factor is less than ideal, it limits a plant’s growth and/or distribution. Environmental factors that affect plant growth include light, temperature, water, humidity, and nutrition. It is important to understand how these factors affect plant growth and development. With a basic understanding of these factors, you may be able to manipulate plants to meet your needs, whether for increased leaf, flower, or fruit production. By recognizing the roles of these factors, you also will be better able to diagnose plant problems caused by environmental stress.

                        i.         Light: Three principal characteristics of light affect plant growth are quantity, quality, and duration. Light quantity refers to the intensity, or concentration, of sunlight. It varies with the seasons. The maximum amount of light is present in summer, and the minimum in winter. Light quality refers to the colour (wavelength) of light. Blue and red light, which plants absorb, have the greatest effect on plant growth. Blue light is responsible primarily for vegetative (leaf) growth. Red light, when combined with blue light, encourages flowering. Plants look green to us because they reflect, rather than absorb, green light. Duration refers to the amount of time a plant is exposed to light. Photoperiod controls flowering in many plants. Scientists initially thought the length of light period triggered flowering and other responses within plants. Thus, they describe plants as short-day or long-day, depending on what conditions they flower under. We now know that it is not the length of the light period, but rather the length of uninterrupted darkness, that is critical to floral development.

                       ii.         Temperature: Temperature influences most plant processes, including photosynthesis, transpiration, respiration, germination, and flowering. As temperature increases (up to a point), photosynthesis, transpiration, and respiration increase. When combined with day-length, temperature also affects the change from vegetative (leafy) to reproductive (flowering) growth. Depending on the situation and the specific plant, the effect of temperature can either speed up or slow down this transition. Low temperatures reduce energy use and increase sugar storage. Thus, leaving crops such as ripe winter squash on the vine during cool, fall nights increases their sweetness. Adverse temperatures, however, cause stunted growth and poor-quality vegetables.

                     iii.         Water and Humidity: Most growing plants contain about 90 percent water. Water plays many roles in plants. It is a primary component in photosynthesis and respiration. Responsible for turgor pressure in cells (Like air in an inflated balloon, water is responsible for the fullness and firmness of plant tissue. Turgor is needed to maintain cell shape and ensure cell growth.) A solvent for minerals and carbohydrates moving through the plant. Responsible for cooling leaves as it evaporates from leaf tissue during transpiration. A regulator of stomatal opening and closing, thus controlling transpiration and, to some degree, photosynthesis. The source of pressure to move roots through the soil. The medium in which most biochemical reactions take place.

 

                     iv.         Plant Nutrition: Plant nutrition often is confused with fertilization. Plant nutrition refers to a plant’s need for and use of basic chemical elements. Fertilization is the term used when these materials are added to the environment around a plant. A lot must happen before a chemical element in a fertilizer can be used by a plant. Plants need 17 elements for normal growth. Three of them carbon, hydrogen, and oxygen are found in air and water. The rest are found in the soil. Six soil elements are called macronutrients because they are used in relatively large amounts by plants. They are nitrogen, potassium, magnesium, calcium, phosphorus, and sulphur.

What soil factors affect the yield?

Potatoes grow best during cooler weather. Plant potatoes 2-4 weeks before the last frost in the spring, when the soil temperature is at least 40 degrees F. In warm climates, potatoes are planted from January to March and harvested between March and June. In cooler areas, potato-planting time is usually between April and June, with harvest between July and September. Plant potatoes where they will receive full sun, and choose and well-drained, acidic soil. Avoid planting in the same spot in which peppers, eggplants, or tomatoes were grown in the previous season, as potatoes are particularly susceptible to diseases carried by those plants. Cut seed potatoes into 1- to 2-inch squares with two to three eyes (bud sprouts) per piece, then allow them to dry for a couple of days before planting. Plant seed potatoes 12 to 18 inches apart and four inches deep. The eyes should be facing up and the cut side facing down. If planting in-ground, space rows 24 to 36 inches apart to leave room for hilling and walking between the plants.

Does harvesting method play a role in increased/decreased yield?

Harvest “new” (immature) potatoes for eating after the plant begins flowering. Gently scratch some soil under the plants aside and feel around for a few small tubers and pull them out, then replace the soil so the plants will keep growing. For full-sized potatoes, wait until after the tops of the plants have died. Carefully dig up the entire plant using a garden fork, doing your best not to bruise or pierce the potatoes. Bring them inside and keep them in a dark, cool, humid spot (such as an unfinished basement or garage) for two weeks to “cure” so the skins will thicken and dry for storing. Store in a covered, ventilated box or bin.

 

What indices are generally used for this kind of study?

Monitoring of crop growth and forecasting its yield well before harvest is very important for crop and food management. Remote sensing images are capable of identifying crop health, as well as predicting its yield. Vegetation indices (VIs), such as the normalized difference vegetation index (NDVI), leaf area index (LAI), Soil adjusted vegetative index (SAVI), normalised differential water index (NDWI) calculated from remotely sensed data have been widely used to monitor crop growth and to predict crop yield.

RESULTS

The fields of potato observed and the Normalised Differential Vegetation Index (NDVI), Normalised Differential Water Index (NDWI) Vegetative Condition Index (VCI) are calculated. The values of indices are given below.

The above image shows the NDVI values of the study area. The value of NDVI varies from -1 to +1, as the values increases the amount of vegetation increases. The study area is observed for two months from April to May. From the above image we can identify the changes in the level of vegetation for each period of time.

Normalized Difference Water Index (NDWI) is used to differentiate water from the dry land or rather most suitable for water body mapping. Water bodies have a low radiation and strong absorbability in the visible infrared wavelengths range. The value of NDWI varies from -1 to +1.

The Enhanced Vegetation Index (EVI) is an optimized vegetation index designed to enhance the vegetation signal with improved sensitivity in high biomass regions and improved vegetation monitoring through a de-coupling of the canopy background signal and a reduction in atmosphere influences. The value range of EVI is between -1 to +1 and with healthy vegetation generally around 0.20 to 0.80.

CONCLUSION

The estimation of yield of potatoes using remote sensing is a very toughest process. The cultivation of potato in the study area was during March 2020 to May 2020 and the satellite data of that period is used for the study. Various indices like NDVI, NDWI, EVI are used to estimate the growth of plants and by that estimate the outcome. The values of NDVI, NDWI and EVI for beginning of April month is 0.33, 0.32, 0.31 respectively. The crops are in the beginning stages of the growth and so NDVI and EVI value are higher. The NDWI value shows some water stress in the soil. Similarly, the values of April last week are 0.34 for NDVI, 0.23 for NDWI and 0.31 for EVI. Also, for first week of May is 0.32 for NDVI, 0.21 for NDWI and 0.31 for EVI. The results for last week of May is 0.48 for NDVI, 0.41 for NDWI, 0.48 for EVI.

 

The values of May last week shows that the crop has attained a very good condition. The water stress in the field is good, and so the yield of the crop will be better. On analysing the values of the different considered indices, we can conclude that the crop shows a very good health conditions, by that we can expect a very good amount of yield. The potatoes in each field of our study area will give a moderately above amount of yield.

We will keep posting about any such informative information on to our blogs, to help as many people as possible. Farmonaut is built upon a vision to bridge the technological gap between farmers and strives to bring state-of-the-art technologies in the hands of each and every farmer. For any queries/suggestions, please contact us at [email protected]

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Evapotranspirartion In Agriculture

Evapotranspiration is a crucial process by which water is transferred from the land to the atmosphere by evaporation from the soil and by transpiration from living plants.

Button 3: Select a field: By clicking on this button, the user will be taken to another screen on which they can select the boundary points of a region they want to be monitored through satellites. A point can be selected on the map by long pressing on the screen for about 1 second. At least three points must be selected. Once the points are selected, the user will click on the submit button. At this point, our server will generate metadata of the selected field including the approximate field area of the bounded region. According to the field area, the payment screen will appear through which user will have to select one of the four options (1 month, 3 months, 6 months, 12 months) depending upon the cultivation cycle of the user.

 

 

Button 1: My Fields: The button opens another screen on which the field results are visualized on the map. If the user has multiple fields, they can toggle between results of multiple fields from the field addresses given at the bottom of the screen. On the right side, there are buttons of : Map Controls, Index Results, Reports, Weather Data and Field Chat. 

 

 

Map Controls: From map controls, users can choose a. which index result to display on the map, b. the date of the satellite visit of the results, c. the colormap of the displayed result. By clicking the “show on map” button, the results of the selected option will be displayed on the map.

Index Results: On this screen, a line graph is displayed of several indices, providing a time series analysis of the field.

 

 

Reports: On this screen, the dates for which the reports are available is displayed. These dates are listed in two different categories: successful days and failed days. Successful days are the days on which the satellite was able to capture results of the field successfully. Failed days are the days on which the satellite was not able to capture results of the field due to cloud cover. By clicking on any on the dates, the report will be displayed on the app.

Weather Data: This screen provides the current weather data as well as weather forecast of the field (7 days forecast).

Field Chat: On this screen, users can start discussion about their fields (problems, solutions etc) with other community members. Users can upload field images too with the post and comment on the posts as well as the individual images.

 

Button 2: Public Fields: This screen consists of a list of our farmers who have voluntarily made their field data public so that the other farmers can see the progress of these farmers through time. By clicking on the address of the public field, user will be directed to the map on which the field results will be displayed.

We will keep posting about any such informative information on to our blogs, to help as many people as possible. Farmonaut is built upon a vision to bridge the technological gap between farmers and strives to bring state-of-the-art technologies in the hands of each and every farmer. For any queries/suggestions, please contact us at [email protected]

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FARMONAUT

Satellite Based Crop Health Monitoring, Crop Issue Identification System, Farmers’ Social Network, Govt. Approved Farming Database, Satellite Imagery Access For Research and Much More

Soil Organic Carbon And Its Importance In Agriculture

INTRODUCTION

Soil organic carbon is the carbon that remains in the soil after partial decomposition of any material produced by living organisms. It is present as a main component of soil organic matter and is
believed to play crucial role for many soil functions and ecological properties. The amount of organic carbon present in a soil depends upon the local geology, climatic conditions, land use and management. Organic carbon is mainly present in the top soil (2500 pg of c to 2-m depth).The amount of carbon that is present in the soil is twice larger the amount present in atmosphere hence soil act as an important reservoir of carbon. 

IMPACT ON AGRICULTURE

Soil organic carbon is the basis of sustainable agriculture. Farmers are interested in retaining and increasing soil organic carbon for individual fields in order to improve soil health and yield. One of the main reasons behind this is the ability of soil organic carbon in maintaining the soil fertility. SOC improves soil aeration, water retention capacity, drainage, and enhances microbial growth. As carbon stored in the soil is increased carbon is “sequestered” (long -term storage) and risk of loss of nutrients through leaching and erosion is reduced. When the amount of carbon in the soil is increased it reduces the amount of carbon dioxide present in the atmosphere which provides a better climatic condition for plant growth. An increase in soil organic carbon results in more stable carbon cycle and enhanced overall agricultural productivity. 

DEPLETION OF SOIL ORGANIC CARBON

According to the study conducted in Sweden, nationwide the 270 TG c stocks in agriculture surface soil is rapidly decreasing at a rate of 1 TG per year. One of the reasons behind this according to the study of GUO and GIFFORD is change in land use pattern. There is a chance of reduction of 10% of c stock when there is change in land use from forest to crop land. Unsustainable management practices like excessive irrigation, over grazing, deforestation, excessive tillage, practice of burning agricultural fields also causes soc losses. A large amount of carbon in the soil is reduced due to plant harvesting processes. The process of decomposition done by micro-organisms present in the soil where half of the organic carbon is released in the form of carbon dioxide is a major reason behind soil organic carbon depletion. Greater root bio-mass also results in carbon loss due to increased rate of respiration that take place through these roots. The amount of organic carbon present in the soil is affected by factors like climate, texture, hydrology (water content), land use and vegetation. When the amount of carbon in soil is reduced it affects the ability of soil to supply nutrients to the plant which in turn leads to low yield and affect food security. It also reduces the soil bio-diversity since it affects the growth of microbes. Global warming also contributes in depletion of organic matter present in the soil.

PRACTICES TO PROMOTE SOIL CARBON STORAGE 

Soil carbon storage is a vital ecosystem service. In an agricultural land soil carbon loss takes place as a result of improper methods of soil managements such as excessive tillage, increased rate of irrigation, increased use of chemical fertilizers etc. 

  • One of the most effective methods for leaving the soil undisturbed is the practice of zero-tillage. 
  • Soil fertility can be maintained by introducing proper management strategy for grazing and by reducing the use of chemical fertilizers. Replacing chemical fertilizers with organic fertilizers and manures will help to restore the soil health. 
  • Erosion of top soil which brings down the amount of carbon present in soil can be controlled by maintaining the ground cover. Growing cover crops like eucalyptus can reduce the wash away of top soil. 
  • Excessive irrigation can deteriorate soil health. So the amount of water supplied to the plants should be according to its needs, not more, not less. 
  • Another method of increasing carbon storage is by growing high yield, high biomass crops. 
  • The amount of carbon present in the soil will increase if the crop frequency of a place is maxi-mum.

HOW TO ACHIEVE THIS 

Monitoring the field to assess whether the change in management is restoring or depleting the carbon resource is an important step towards protecting the soil organic carbon content. This can be done using the technology of remote sensing. Quantitative and qualitative estimation of soil using the conventional method is difficult since soil show variability from site to site even within the same field. The method of remote sensing is cost-effective and rapid. FARMONAUT app uses remote sensing technology to create a SOC image that provides color map of percentage of organic matter present in the selected field. If the content of SOC is more than 5% the area appears dark green in the color map and it appears red if the SOC content is less than 1%.Change in SOC content with time is also  noted with the help of remote sensing in FARMONAUT. This provides precise information to the farmers which help them to take the right measures, in the right time, and in the right place hence ensuring productivity and soil health. 

Once Farmonaut data has identified some locations to be having less SOC levels, farmers can get the soil testing done on those regions and add required nutrients to those regions to rejuvenate the soil organic matter levels. This will ultimately lead to better yields.

We will keep posting about any such informative information on to our blogs, to help as many people as possible. Farmonaut is built upon a vision to bridge the technological gap between farmers and strives to bring state-of-the-art technologies in the hands of each and every farmer. For any queries/suggestions, please contact us at [email protected]

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How Natural Farming Can Reinvent The Way Farming is Done Today - Viswamatha Farms | A Case Study

The agricultural practices in use today have a very big impact on the environment. Pollutants, waste, soil degradation, irrigation problems, deforestation, climate change are damaging the agriculture in one way or the other. Excessive use of urea, nitrate, pesticides etc. have affected air, water, and soil quality in a severe way.

Natural Farming

Natural farming is touted as the answer to the above mentioned issues. It was first made popular by Masanobu Fukuoka (Japan) and is famously known as ‘Do-nothing farming’ or ‘No-tillage farming’. This idea in it’s simplest form is to allow nature play a prominent role to as much extent as possible. The farmer is only considered as a care-taker and most of the work is done by the nature itself. Moreover, there are no good or bad organisms in a natural farm. Existence of all of them is important for a balanced ecosystem.

Key Principles of Natural Farming

No till farming – growth of weeds is enhanced if the soil is ploughed since it alters the natural environment of the soil.

No weeding by tillage or herbicides – weeds are suppressed by spreading straw over newly sown land and growing ground cover.

No chemical fertilizers – adding chemical fertilizers can help in the growth of the plant but not of the soil.

No chemical pesticides – nature’s own balancing act prevents any one species from gaining the upper hand.

Viswamatha Farms

Viswamatha farms was born from a passion to share natural farming with the world.

http://viswamathafarms.com/

It believes in the power of nature and the positive change it can have on our land and peoples lives. It is  passionate about real natural food that tastes great, is of highest quality, is full of nutrients and is good for our health and environment.

All the products are produced by natural farming techniques of Shri.Subhash Palekar ji with out using any chemicals.

Viswamatha Farms has been using Farmonaut’s Satellite Based Crop Health Monitoring System since September, 2019.

 

About The Farm

Viswamatha farms owns and cultivates pulses, millets, rice, spices, groundnut, gingle, vegetables and fruits. The farm is situated in Andhra Pradesh, south India.

The farm is a healthy mix of agriculture, horticulture, floriculture and animal husbandary. Apart from their own farms, viswamatha farms has created natural farming farmers group to cater to the growing requirement of quality products.

Viswamatha farms owns Ongole breed cows and country chicken for farm yard manure. The Cows & country chicken are stress free and free to roam and graze in the fields. 

 

 

Natural Farming Practices Used By Viswamatha Farms

Viswamatha farms enrich the soil nutrients by using jeevamruth which is a fermented microbial culture. It provides nutrients but most importantly acts as catalytic agent that promotes the activities of micro-organism in the soil as well as increases earth worms activity. During 48 hours of fermentation process the aerobic and anaerobic bacteria present in the cow dung and cow urine multiply as they eat up organic ingradient (pulse flour mixed in the jeevamruth) in the jeevamruth. A handful of undisturbed soil from the field bunds also added to jeevamruth as inoculate of native spices of microbes and organism.

 

Jeevamruth also helps to prevent fungal and bacterial plant diseases.

Insects and pests are managed by using specially prepared mixtures called as neemastram, agniastram, brahastram, dasaparni kashayam. These mixtures involve cow dung, cow urine, neem leaves, neem pulp, green chillies and other herbs as required to manage the pests and diseases.

Impact of Natural Farming Methods in Combination With Remote Sensing in the Previous Season

Viswamatha Farms harvested their major crop Red Gram in the month of February, 2020. The images below attached are of the red gram plants in the Viswamatha farms nearly after one month of harvesting.

The images shown below are of the farm nearby to Viswamatha farms which was using the contemporary methods of farming (not natural farming) and also harvested red gram from their field at the same. The images are of one month after the harvesting was done.

As we can clearly see, the red gram plants in the neighboring field of Viswamatha farms are completely dead and dry, whereas the same are still live and healthy in Viswamatha farms even after one month.

Natural Farming in Combination With Remote Sensing

In parallel to the natural farming practices, Viswamatha farms has also been referring to the satellite data provided by Farmonaut through our platform (available on android, iOS as well as web app) to take field level actions and minimize the efforts even further.

Viswamatha Farms is one of our most important users and as quoted by Mr. G.K. Rao of Viswamatha Farms:

“We are bringing awareness on progressive farmers and asking them to use your services for the crop monitoring”

By using satellite data provided by us, farmers can:

1. Reduce Chemical/Fertilizer consumption by applying them only in the locations where crop health is not good.

2. Reduce Labour costs by directing the labours only in those field areas where crop health is critical.

3. Reduce irrigation water wastage by applying proper irrigation only in those locations where plant water stress is low.

4. Increase overall yield.

For any queries and collaborations, please feel free to contact us on: [email protected] or +91-6366026267.