Harvest maturity & scheduling

Which parcels should be harvested first and when?

Accurate prediction of optimal harvest dates is important to maximize crop yields as maturity approaches. Yield loss occurs if harvest occurs in advance of, or is delayed – both scenarios are undesirable. If the crops are harvested prematurely, high residual moisture makes it prone to mildew and other pests during storage. The harvest quality then deterioates, leading to a serious decrease in yield. If cereals are harvested too late, the quality declines severely (Xu et al. 2019, Zude et al. 2002, Mutanga et al. 2013, Meng et al. 2013).

Optimising the harvest date is vital for most farm managers and farmers – and it is predominant, in Europe, India or Africa.  It allows us to set up a harvest schedule for each crop type, thus, also mitigating difficulties in manpower and machinery availability, logistics and storage as well as providing important statistics about the location and origin of the crop (where will the crops be harvested first?).


To provide a practical solution to all these implications, we developed a harvest maturity and scheduling service. It uses spectral indices sensitive to crop senescence to rank all parcels on a desired date (during the ripening stage, at the end of the season) according to their harvest readiness and even allows a forecast. The benefits of such service are obvious:

  • Understanding crop maturity status
  • Determine harvest order of fields 
  • Optimising harvest scheduling
  • Optimising yield
  • Prediction of quality (with crop specific calibration data)
  • Reducing costs for laboratory measurements
  • Improve yield prediction

Product: Harvest Maturity Ranking

Our harvest maturity ranking is based on a maturity index. By applying a ranking function the order of fields will be determined. This level of products works without prediction and gives you the possibility to analyse the current index developments.
The maturity index is based on the Chlorophyll Index Red-Edge (CIRE) as it is scientifically proven to correlate very well with the ripening and maturity stages of the respective crops. During maturation the index shows a characteristic slope. It is assumed that the increase of chlorophyll breakdown occurring in the third period is triggered when the climacteric rise of the fruit respiration rate appears. Therefore, spectral analysis in the red edge range can be used as a fast and non-destructive tool for determining the optimum harvest dates (Zude et al. 2002).

Product: Harvest Scheduling & Maturity Determination

This product allows you to determine the time difference of fields in days for reaching same maturity. This gives you an exact schedule for each field once the optimum maturity stage has been determined. To predict the optimum maturity stage of the crop in advance predictive modelling is applied. This model may vary from variety to variety. Thus crop specific calibration data has to be provided by the customer. 


References:

  1. Jin Xu, Jihua Meng, Lindi J. Quackenbush, Use of remote sensing to predict the optimal harvest date of corn, Field Crops Research, Volume 236, 2019, Pages 1-13, ISSN 0378-4290, https://doi.org/10.1016/j.fcr.2019.03.003.
  2. Manuela Zude and B. Herold, Optimum Harvest Date Determination for Apples Using Spectral Analysis, Gartenbauwissenschaft, 67 (5). S. 199–204, 2002, ISSN 0016–478X
  3.  S. Mutanga, C. Schoor, P. Olorunju, T. Gonah and A. Ramoelo, „Determining the Best Optimum Time for Predicting Sugarcane Yield Using Hyper-Temporal Satellite Imagery,“ Advances in Remote Sensing, Vol. 2 No. 3, 2013, pp. 269-275. doi: 10.4236/ars.2013.23029.
  4. Meng J.H., Dong T., Zhang M., You X., Wu B. (2013) Predicting optimal soybean harvesting dates with satellite data. In: Stafford J.V. (eds) Precision agriculture ’13. Wageningen Academic Publishers, Wageningen

Link: Harvest Maturity API Documentation