Newsletter

May 2017

 

FarmERP Highlights May 2017

 
Proud moment for Team FarmERP
 
 
 

FarmERP bags Maxell Award-2017 for Excellence in Innovation

 
   
 

Maxell Award for Excellence in Innovation 2017 presented to FarmERP - an innovative solutions for agriculture in India and abroad at hands of the great man Mr.Sam Pitroda. FarmERP fostering the way ahead to Digital Green Revolution.

 
  To know more, visit http://www.maxellfoundation.org/winner-17.html
 
 

FarmERP for Exporters Highlights

 
    Farmers data management –
              Good Agricultural Practices

 
    Crop advisory
 
    Field/ Arrival quality checks
 
    MRL test reports
 
    Harvesting records
 
    Packhouse and Cold storage
               information management

 
   Exports documentation
 

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  www.farmerp.com

 
 

April 2017 Newsletter

   
 

Success Stories

A Leading grape exporter from India chooses
FarmERP

INTRODUCTION
The client is one of the leading exporters in India. They are mainly into export of Grapes to various countries. The company was incorporated in 2000 to better serve the Farm Equipment Sector’s extensive base of rural customers.

The company currently works with more than 2500 farmers from the Nashik, Sangli, Latur and Solapur regions of Maharashtra for grape production and export operations. It not only procures fresh produce from farmers, but also provides end to end extension services – including agronomy, certification, grading and packaging, etc.

The company enables farmers to produce the best quality grapes and gives them access to international markets.
CHALLENGE
With 15 pack houses across four locations the client struggled in maintaining unified pack house operations. Keeping the Fruit quality and MRL compliance and maintaining the quality standards of grapes for exporting to EU and Middle east was one for the challenges faced by the client.

Inventory management and traceability of stock in each level on process across multiple pack houses and higher post-harvest losses and reconciliation were additional issues.

“A need for consistent ERP that drive down costs and meet volume needs”

They required a comprehensive platform where the pack house process and all its stakeholders like CHA and MRL labs will come together for seamless Packhouse operation and export.  
 

Focus Area – BIG DATA

 
     
   
 

FarmERP Focus Area – Big Data

Big data Analytics is a revolutionary concept of collecting, organizing and analysing huge amount data – Big data to discover data patterns and present it in ready to use form. Big Data analytics has the potential to help companies improve operations and make faster, more intelligent decisions. This data, when captured, formatted, manipulated, stored, and analysed can help a company to gain useful insight to increase revenues, get or retain customers, and improve operations.

Big data is poised to revolutionise the Agriculture sector. With the combination of data analytics, Sensors, drones, telematics devices, automated irrigation systems and weather stations, big data making a way to foster Digital Green Revolution. Big Data application may lead users to accurate selection of appropriate agri-inputs, tracking prices of markets, analysing irrigation spells, commodity futures analysis. Sensors can provide the information on soil condition, fertilizer requirements and water availability. Drones can patrol fields and alert farmers about the crop status. Telematics device on tractors can help in determining the usage of the attached equipment. Individual plants can be monitored for nutrients and growth rates. By collecting and Analysing the data generated by these devices, Big Data can bring in the right information to take informed decisions in adverse climatic conditions which will assist in determining the best crops to plant, considering both sustainability and profitability.

How Big data in FarmERP will help your business lead?
  • Improved and faster decision making
  • Predict the suitable farming conditions
  • Enhanced and adaptive capacity of farming systems to climate change
  • High end complex data analysis
  • Reduce yield estimation gap