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Linseed Stripper Simulation Trial


In order to gain some information and experience in harvesting decisions when using a stripper on linseed in New Zealand the Biological Husbandry Unit (BHU) was asked to simulate the use of a stripper on the New Zealand linseed cultivar ‘Hinau’. 

Materials and Methods

5 replicates of a single sowing rate (60kg/ha rows 0.10m apart) of the linseed cultivar ‘Hinau’ (tsw 4.72g) was sown on 23 December 2003 using a cone seeder.  The area sown was in spring wheat the previous season and had not had any fertiliser inputs since then.

Crop progress was monitored and a photographic record kept.  Harvesting began when one of the plots showed some browning of the stem immediately below the boll.  This occurred on 16 April 2004.  The area harvested was a 0.200m length of row from five rows giving a total harvested area of 0.10m2.  Plant stems were counted for each of the rows harvested within the harvest area.  Ten stems had individual bolls scored for maturity and bird/insect damage.  Bolls were then manually stripper from stems using a kitchen fork.

The weight of the stripped material was recorded and the material the oven dried until ‘crisp’ at 40°C.  Dry weights were recorded and the seed manually threshed and dressed for each plot.  Yield from each plot/harvest event was weighed and kept for future oil yield and quality assessment.


Change in drymatter content over time

The first harvest was undertaken on 16 April 2004, 115 days after sowing.  As the harvests progressed with increasing crop maturity over the following month the dry matter content (DM) of the manually stripped material increased steadily.  The final harvest event had a higher moisture content (i.e. a lower %DM) than the previous harvest, probably due to recent rain (this event occurred sooner after rain than was desirable due to a forecast for further rain the following day).

The changes in %DM over time are shown for the 5 plots and the mean of these in Figure 1, below.

Figure 1:          Changes in %DM stripper simulated material with sequential harvesting of the linseed cultivar ‘Hinau’.


From the perspective the least amount of moisture (i.e. highest %DM) in the stripped material the dates of 7 and 10 May were optimum (136 and 139 days after sowing). 

Yield of seed

While the seed yield varied quite widely between plots within sample harvest events and within plots between sample harvesting events, seed yield was remarkably consistent at around 20g per 0.1m2 or 2T per hectare.  This is illustrated in Figure 2, below

Figure 2           Yield of dry linseed from each sampling event


Seed yield as a % of fresh weight of material stripped

As can be seen from Figure 3 the maximum % of the fresh weight (FW) achieved by any plot was approximately 55%, while the average for the maximum %DW time line (7 and 10 May) was between 40 and 50%.  This has implications for the harvesting, drying, dressing and storing logistics for this stripped linseed which will be different to those for the windrowed and headed linseed.

Figure 3           Linseed seed dry weight as a % of the material harvested during the linseed stripper simulation


Changes in visual cues to crop maturity over time

Figure 4 shows the changes in the % of each of four categories that bolls were placed in to rank the maturity of the crop.

Figure 4           The % of bolls ranked as green, yellow, brown or damaged for some of the sampling events during the linseed stripper simulation.


This graph has a corresponding set of digital prints for visual comparisons


The visual cues, the water content of the ‘harvested’ material and the seed % of ‘harvested’ material all concur with the optimal harvest date being on or about 07/05/04.  harvesting sooner than this has implications for transport, drying and dressing seed.

With the inclusion of information on oil yield and oil quality another layer of information will be available for harvest timing decision support.


While it is not possible come to definitive conclusions regarding when to harvest with a stripper, valuable lessons have been learned to support the decision making process.