Yield Benchmarking
Yield Benchmarking is the practice of measuring the performance of a field or farm by comparing it against a certain standard. Sugarcane farmers can benchmark their yields against a simulated yield potential by using our CANESIM software.
It’s important to remember that the yield estimates reflect yield potential as determined by climatic conditions, soil properties, crop information and irrigation information. It assumes ideal crop management and no pest, disease and nutrient limitations. Hence, simulated yields are often higher than actual yields produced commercially.
However, yield differences from one season to another, or between soil types, or between crop cycles etc., could provide valuable information to understand variations in actual yield. Large discrepancies could indicate possible agronomic limitations to sugarcane production.
There are three CANESIM applications available:
Aresti Paraskevopoulos
Mycanesim Lite
This is available both as a web-based and mobile phone application. It is a sugarcane simulation tool linked to the Canesim model and the full online SASRI weather database for simulating crop growth and water use for limited sets of inputs. Applications include cane yield, cane quality and water use benchmarking and limited yield forecasting.
Mycanesim
This is a web-based sugarcane simulation tool linked to the full online SASRI weather and soil water data base for simulating crop growth and water use for registered users. Applications include cane yield, cane quality and water use benchmarking, real-time irrigation scheduling and yield forecasting.
Crop Forecasting
The CANESIM crop forecasting system produces monthly forecasts of yield for the current season for 48 climate zones and 14 mill supply areas. It is available to registered users.
Note: SASRI has access to several automatic and manual weather stations across the sugar industry. All information gathered is stored in a weather database at SASRI. This information can be extracted in the form of maps, graphs or reports from the SASRI WeatherWeb.