The Smart Tools for Orchard Drainage project has completed key steps to prepare and implement inter-row land levelling. Terrain analysis has provided a clear indication that a gentle gradient could be developed along the inter-row with minimal soil movement. However, the effects of reducing ponding through slight land shaping would be substantial for management and health and safety in the orchard.

Orchard Contour Mapping

LiDAR data from Hawke’s Bay Regional Council and Gisborne District Council were used to assess the feasibility of inter-row land levelling in the orchard blocks of interest. LiDAR (light detection and ranging) is a type of airborne optical sensing that is used to generate a model of the earth’s surface. It let us create contour maps and look at ground profiles (Figure 1).

The inter-row profiles were used as a ‘first look’ to estimate the fall across the orchard and provide an indication of the approximate amount of soil to be shifted to remove and prevent areas of ponding.

We also surveyed using ground-based vehicles (quad bike or tractor) with RTK GPS (Figure 2). This system has a vertical accuracy of approximately 20 mm. Corrected elevation data were recorded along the inter-rows using WM-Drain. These data were also used to create accurate interrow profiles.

The comparison of the different methods of generating profiles has given confidence that LiDAR is useful for an initial block analysis.

Ponding maps

Two of the orchards were visited after a significant rain event (30+ mm over a weekend). Locations of ponding were collected using the ESRI Collector smartphone app and an EOS Arrow SBAS GPS with a horizontal accuracy of 30-40cm. The interrows at one orchard were covered by Extenday, which meant the areas of shallow ponding were difficult to identify (Figure 6).

A drainage analysis created in Optisurface was used as a base map to display ponding locations (Figure 7). After this rain event, the majority of areas of ponding appeared to be located within areas identified by the drainage analysis as areas where ponding would occur.  

The ponding locations were also compared to the interrow profiles. Although no formal analysis was completed, many of the ponding spots appear to match dips in the profiles (Figure 9).

Rut depth measurements

The key measurement for monitoring the effectiveness of the different drainage treatments will be the formation of ruts. A sled has been specifically designed to measure and record the depth of ruts and the location within the orchard blocks, see Figure 10.

The sled uses a linear transducer to measure the difference in height between the bottom of the wheel ruts and the ground surface between the wheel tracks. The location is recorded using the SBAS positioning system with an EOS Arrow 100 GPS with a horizontal accuracy of approximately 0.3-0.4m. The data was recorded on a smartphone using an app, Rut-O-Meter. Points are recorded approximately every 0.2m depending on travel speed as the sled was towed by a quadbike along orchard rows.

The average rut depth (of the left and right wheel tracks) throughout the trial block was measured prior to the soil being cultivated. An example of the rut depth along an orchard row and the corresponding elevation profile are presented in  Figure 11.

A map from the rut measurements is shown in Figure 12. Deeper ruts are darker blue. Pale yellow is no rutting or the inter-row is lower than the wheel tracks. This compares well with the OptiSurface generated ponding map of the block (Figure 13).

Figure 13: OptiSurface drainage and ponding analysis from RTK survey of the trial block

Conclusions

• Analysis of LiDAR data and ground based RTK elevation data has shown that land levelling should be possible with minimal soil movement.
• The ground based RTK survey, with the GPS antenna on a 2m pole has proven that the connection is not interrupted through dense tree canopies.
• The use of the SBAS system, a cell phone and EOS Arrow GPS receiver allows information to be recorded against individual trees, with an accuracy of 30-40cm, even in dense tree canopy.
• The ponding areas identified in the orchard after a significant rain event appear to show a relationship to the OptiSurface drainage analysis.
• The Rut-O-Meter mapping shows good agreement with the other surveys

Project work by Page Bloomer Associates for NZ Apples and Pears Inc and MPI Sustainable Farming Fund

The MPI Sustainable Farming Fund “Smart Tools to Improve Orchard Drainage” project was initiated in response to extreme weather conditions experienced by pipfruit growers in the late season (March – June) harvest of 2017. It is co-funded by New Zealand Apples and Pears Inc.

A survey conducted over 3 weeks in November and December of 2018 covered 2,238 hectares of pipfruit growing orchards. Conducting the survey with growers via face-to-face interviews produced a greater number and depth of answers, however certain details were still difficult to obtain. Many growers were hesitant to provide or lacked confidence in estimations of the extent and area of wheel rut damage as a result of poor drainage.

To help with consistent assessments, we created a four panel photo scale of drainage issues found in orchards (see below). Growers interviewed considered the scale realistic and relevant. They felt able to correctly match problems areas in their blocks to the photos, but differed in their assessments of how much of a problem it might be.

The key impacts on operations identified by the survey were predominantly categorised into three areas; tree health, access, and labour. Almost all orchardists surveyed believed that poor drainage was contributing to poor tree health (either visibly or evident through low yield) or causing tree deaths (up to 10% in one extreme example). Many orchardists remarked on wheel ruts resulting in staff injuries (due to ladder slips in mud, tripping, or the impact of driving over uneven surfaces). Labour availability was also affected in severe cases where orchard ponding and ruts were the reason some contracting groups did not want to work at those sites. In all cases where extreme damage was present, access for sprayers, and tractors hauling harvest bins was impeded, and occasionally impossible. This meant that costs were incurred as a result of delaying harvest windows, slowing the pace of operations, and risking greater levels of disease at an already busy time of year.

Situational factors common among the orchards studied included:

• Frequent passes by heavy orchard machinery for many months of the year (7 – 11)
• Low spots in the in the inter-row were the worst affected
• Shaded canopies associated with 3D training and mature plantings

The area affected was 44% of the area surveyed (1,479 ha).

Tree Health

Tree health suffers as a result of poor drainage and water-logging of the soil. This was evident in the Motueka and Richmond site visits, where trunk diameter was clearly smaller to the untrained eye in low spots where ponding and wheel ruts were severe. The same observations were made during site visits in Nelson and Hawke’s Bay.

Other important comments included a noticeably lower yield from trees where drainage problems were evident, and some bins where mud had covered fruit during harvest resulted in a greater number of fruit rots in post-harvest storage. One grower also mentioned that the fruit on Fuji varieties developed russet in the worst affected areas.

Access to the orchard is critical at certain times to complete operational tasks. Where an orchard has particularly severe drainage problems the wheel ruts may be so extreme that tractor or sprayer axles drag through the mud, meaning that they are stuck or unable to enter the block. This has led to some orchardists hiring helicopters to apply fungicides when application during a specific time window is crucial. This is an expensive exercise, and is unable to be utilised for insecticide sprays, as the application method is not effective at reaching the internal area of the canopy. The mud and ruts from poor drainage make harvesting difficult and time consuming as tractors require towing (by another or multiple tractors) out of the mud when they become stuck.