Adrian Hunt is a crop scientist at Plant and Food Research.
He recently completed a PhD at the University of Tasmania, investigating Pre-Harvest and Post-Harvest factor effects on the quality of onion bulbs exported to Europe for counter seasonal supply. He now works across the vegetable and arable sectors to improve yield, profitability and environmental outcomes.
Together with colleagues Joanna Sharp, Paul Johnstone and Bruce Searle, Adrian has been investigating the value proposition for variable rate fertiliser application.
The technology to deliver variable rate fertiliser in an automated manner has advanced substantially in recent years. This has been aided by new or adapted spreading technologies coupled with location awareness using GPS (Global Positioning System). It is now technically possible to distribute fertilisers in a wide range of spatial patterns within a paddock, however the value proposition of variable rate fertiliser application is not thoroughly understood.
The Plant and Food team looked at the difference in productivity, profitability and potential environmental impact of a range of spatial management scales.
Based on a sampling grid of 105 points in a Hawke’s Bay paddock and used mineral N and a N mineralisation assay to quantify the underlying variability in N processes/cycling within the paddock they “grew” both irrigated and unirrigated maize in the crop simulation model APSIM Next Generation for the 105 sampling locations for 35 growing seasons, using long term weather data.
Adrian will present this work and the results at the LandWISE 2017 Conference in Havelock North.
Anthony (Tony) Davoren is a Director of Aqualinc with responsibility for the HydroServices business unit that provides irrigation and environmental management services; soil moisture, and water level and water meter monitoring.
Tony’s expertise in and knowledge of soils and hydraulic properties, irrigation systems and design, and crop water demand has been applied and enhanced over the last 35 years working in these fields.
Tony says several questions need to be asked and honest answers or solutions given:
Are we and you ready?
What do we need?
Is automating irrigation management wise or the right solution?
Are we or you ready?
When considering automating irrigation management, both the provider and the user must be an “innovators”; i.e. they must be in the top 2.5% of the industry. It may be that some “early adopters”, the next 13.5% of the industry, might be ready for the technology and its application to automate irrigation management.
What do we need?
Because it will be the innovators who adopt and field prove any technologies, these technologies must be robust and proven with a sound scientific backing. Innovators will identify the financial benefits of the automation, which needs:
Well-designed irrigation systems
High uniformity irrigation systems
Well maintained irrigation systems
Precise soil moisture and/or crop monitoring systems
Interface “model” to irrigation controller
Are these all in place?
Is automation wise or the right solution?
Tony established HydroServices providing on-farm irrigation management services based on in situ soil moisture measurements in Canterbury, Pukekohe, Waikato, Gisborne, Hawkes Bay, Manawatu, Wairarapa and Central Otago. During this he provided specialist soil moisture monitoring for Foundation for Arable Research, LandWISE, Crown Research Institutes, Regional Councils, Clandeboye Dairy Factory and others.
Tony completed his PhD in Engineering Science at Washington State University, Pullman, USA.
The NZ Soil Management Field Days offer a two day field aimed at all areas of crop production that needs to cultivate the soil.
The two Days aim to bring together a broad selection of machinery companies keen to demonstrate their products both new and existing.Also present will be new technology looking to improve our understanding of the soil and better ways to control weeds and disease.
Catering on site will be available for the two days with coffee and hot food. Upon registration the first 250 entrants will receive a free event hat.
On the first afternoon FAR will give three presentations on:
Research outcomes for soil management and environmental issues
Cultivation techniques long term trial Northern Crop research site
Soil quality results from focus on potatoes project and then these will be repeated in in the morning of the second day.
Once again many thanks to all the main sponsors and exhibitors and to Sundale Farms for the use of the site.
This is an opportunity to see new technology and techniques from a broad base of suppliers from throughout New Zealand.
The Pukekohe area has a unique 12 months of the year growing potential, a wide variety of crops grown, and some of the biggest grower operations in the country. Within New Zealand there are many companies with new ideas and great equipment which don’t get seen.
Special note to suppliers and potential sponsors
Contact the organisers to ask any questions, they are hoping to accommodate as many companies as possible and expect growers from all over the country to come.
Now in year two of our OnionsNZ SFF project, we have trials at the MicroFarm and monitoring sites at three commercial farms in Hawke’s Bay and three more in Pukekohe.
2015-16
A summary of Year 1 is on our website. A key aspect was testing a range of sensors and camera systems for assessing crop size and variability. Because onions are like needles poking from the ground, all sensors struggled especially when plants were small. This is when we want to know about the developing crop, as it is the time we make decisions and apply management.
By November our sensing was more satisfactory. At this stage we captured satellite, UAV, smartphone and GreenSeeker data and created a series of maps.
We used the satellite image to create canopy maps and identify zones. We sampled within the zones at harvest, and used the raltioship between November canopy and February yield to create yield maps and profit maps.
Yield assessments show considerable variation, limits imposed by population, growth of individual plants, or both
We also developed relationships between photographs of ground cover, laboratory measurements of fresh weight and leaf area and the final crop yield.
In reviewing the season’s worth of MicroFarm plot measurements and noticed there were areas where yield reached its potential, areas where yield was limited by population (establishment), some where yield was limited by canopy growth (development) and some by both population and development.
This observation helped us form a concept of Management Action Zones, based on population and canopy development assessments.
Management Action Zones – If population is low work for better establishment next season. If plants are small see if there is something that can be done this season
2016-17
Our aims for Year 2 are on the website. We set out to confirm the relationships we found in Year 1.
This required developing population expectations and determining estimates of canopy development as the season progressed, against which field measurement could be compared.
We had to select our “zones” before the crop got established as we did a lot of base line testing of the soil. So our zones were chosen based on paddock history and a fair bit of guess work. Really, we need to be able to identify zones within an establishing or developing crop, then determine what is going on so we can try to fix it as quickly as possible.
In previous seasons we experimented with smartphone cameras and image processing to assess canopy size and relate that to final yields. We are very pleased that photographs of sampling plots processed using the “Canopeo” app compare very well with Leaf Area Index again this season.
Through the season we tracked crop development in the plots and using plant counts and canopy cover assessments to try and separate the effects of population (establishment) and soil or other management factors.
We built a web calculator to do the maths, aiming for a tool any grower or agronomist can use to aid decision making. The web calculator was used to test our theories about yield prediction and management zones.
ASL Software updated the “CoverMap” smartphone application and we obtained consistent results from it. The app calculates canopy ground cover and logs data against GPS position in real time. Because we have confidence that ground cover from image processing is closely related to Leaf Area Index we are working to turn our maps into predictions of final yields.
Maps of canopy cover created from the CoverMap smartphone application show significant variability across the paddock. Canopy increase is seen over time in two maps created a week apart
The current season’s MicroFarm crop is certainly variable. Some is deliberate: we sat the irrigator over some areas after planting to simulate heavy rain events, and we have a poorly irrigated strip. We know some relates to different soil and cover crop histories.
But some differences are unexpected and so far reasons unexplained.
Wide variation within the area new to onions does not follow artificial rain or topographic drainage patterns. This photo is of the area shown far right in the cover maps above.
Together with Plant and Food Research we have been taking additional soil samples to try and uncover the causes of patchiness.
We’ve determined one factor is our artificial rain storm, some crop loss is probably runoff from that and some is historic compaction. We’ve even identified where a shift in our GPS AB line has left 300mm strips of low production where plants are on last year’s wheel tracks!
But there is a long way to go before this tricky crop gives up its secrets.
This project is in collaboration with Plant and Food Research and is funded by OnionsNZ and the MPI Sustainable Farming Fund.
A desire to reduce soil compaction and avoid high and inefficient use of chemicals and energy inspired Steve Tanner and Aurelien Demaurex to found eco-Robotix in Switzerland.
Their solution is a light-weight fully solar-powered weeding robot, a 2 wheel drive machine with 2D camera vision and basic GPS. Two robotic arms position herbicide nozzles or a mechanical device for precision weed control.
Steve Tanner lab testing the exoRobotix vision and robotic weed control system
The ecoRobotix design philosophy is simplicity and value: avoiding batteries cuts weight, technology requirements and slashes capital costs. It is a step towards their vision of cheap autonomous machines swarming around the farm.
Bought by small farms, Naio Technologies’ Oz440 is a small French robot designed to mechanically weed between rows. The robots are left weeding while the farmer spends time on other jobs or serving customers. Larger machines for vegetable cropping and viticulture are in development.
Prototypes V1, V2 and V3; precursors to the Naio Oz440 show the steps in a robot’s development
Naio co-founder Gaetan Severac notes Oz440 has no GPS, relying instead on cameras and LiDAR range finders to identify rows and navigate. These are small machines with a total price similar to a conventional agricultural RTK-GPS system, so alternatives are essential.
Tech companies have responded and several “RTK-GPS” systems are now available under $US1000. Their accuracy and reliability is not known!
Thorvald an example of research collaboration: Norwegian University robot being automated at University of Lincoln show the common design of four wheel steer and four wheel drive
Broccoli is one of the world’s largest vegetable crops and is almost entirely manually harvested, which is costly. Leader Tom Duckett says robotic equipment being developed at the University of Lincoln in England is as good as human pickers at detecting broccoli heads of the right size, especially if the robot can pick through the night. With identification in hand, development is now on mechanical cutting and collecting.
In 1996, Tillett and Hague Technologies demonstrated an autonomous roving machine selectively spraying individual cabbages. Having done that, they determined that tractors were effective and concentrated on automating implements. They are experts in vision systems and integration with row and plant identification and machinery actuation, technology embedded in Garford row crop equipment.
Parrish Farms has their own project adapting a Garford mechanical to strip spray between onion rows. Nick Parrish explained that Black Grass control was difficult, and as available graminicides strip wax off onions boom spraying prevents use of other products for up to two weeks.
Route planning to avoid hazards and known obstacles
Laser range finder to sense objects and define them as obstacles
Wide area safety curtain sensing ground objects at 2m
Dead man’s handle possibly via smartphone
Collapsible bumper as a physical soft barrier that activates Stop
Big Red Buttons anyone close can see and use to stop the machine
Machines that are small, slow and light minimise inertia
“Hands free hectare” is Harper Adams University’s attempt to grow a commercial crop using open source software and commercially available equipment in an area no-one enters.
Harper Adams research to develop a robotic strawberry harvester is notable for the integration of genetics for varieties with long stalks, a growing system that has plants off the ground, and the robotic technologies to identify, locate and assess the ripeness of individual berries and pick them touching only the peduncle (stalk).
So what have I learned about farm robotics?
People believe our food production systems have to change
Farm labour is in short supply throughout the western world
Machines can’t get bigger as the soil can’t support that
Robotics has huge potential but when
Safety is a key issue but manageable
There is huge investment in research at universities, but also in industry
It’s about rethinking the whole system not replacing the driver
There are many technologies available, but probably not the mix you want for your application.
As Simon Pearson at the National Centre for Food Manufacturing says, “It’s a Frankenstein thing, this agrobotics. There are all sorts of great bits available but you have to seek them out and stitch them together yourself to make the creature you want.”
Dan’s travel was supported by a Trimble Foundation Study Grant
The Arawhata Catchment Integrated Storm Water Management project is drawing to a close, the majority of work is done but farm follow-ups continue. The aim of the project was to reduce crop loss from ponding and minimise erosion of soil to Lake Horowhenua.
We completed OptiSurface drainage analyses for 26 Levin properties covering 450ha of intensive vegetable cropping. OptiSurface calculates flood patterns and erosion risk and creates cut & fill maps for GPS levelling. An example is shown in our earlier post “Mapping for Drainage”.
Drainage and Erosion Management Plans were developed for each block. The plans identify drainage problem areas and erosion risks and recommend management strategies to respond.
Individual farms have done significant work to prevent erosion and reduce crop damage. Farmer actions to reduce sediment runoff and ponding include realigning bed direction, levelling, grassed headlands and drains and swales and sediment traps.
Stages in headland redevelopment
Original design used narrow headlands subject to pugging in wet weather with high risk of slumping soil into vegetation-free drainsHeadland lowered to ensure adequate drainage from furrows. Vegetation being encouraged to protect drain from sediment inflowsLand-shaping created a much wider headland for a greater vegetation buffer between cultivated land and drainsCompleted headland with its well-established vegetated buffer filtering sediment from drainage water
Now farms are required to have consent in this catchment, the Drainage and Erosion Management Plans are a useful component of the overall Farm Nutrient Management Plans required.
Setting out a line of catch trays to test fertiliser application uniformityDriving over a line of catch trays
We ran a number of workshops from Waikato to Ashburton reaching a wide range of farmers and industry people. Information, training handouts and how-to YouTube video clips are on the LandWISE website. See www.fertspread.nz for the on-line calculator and field recording sheets.
We are grateful for strong support from Miles Grafton and Ian Yule at Massey University.
This project was co-funded by the Foundation for Arable Research (FAR), the Fertiliser Association (FertResearch) and MPI Sustainable Farming Fund.
The crop at the MicroFarm is showing increasing variability. The cause of some is understood, essentially excessive water pre-germination. But in some poor performing areas the causes have yet to be determined.
The effect of our artificially applied rain event pre-emergence is clearly evident in late November.
The lasting effect of a heavy (artificial) rain event pre-emergence (right panel) shows low population and poor growth compared to areas without heavy rain (left panel)
However, we also see other areas that have poor crop development that are outside the area irrigated to create the artificial rain event.
Wide variation within the area new to onions does not follow artificial rain or topographic drainage patterns.
Sharp differences in crop growth are evident in the new onion ground. Some parts that were heavily irrigated to simulate heavy rain show reasonable development. Areas that were not irrigated also show good development, but in some patches total crop loss.
Investigations of soil physical properties in these different areas are underway.
After identifying areas within paddocks that had yields limited by different probably causes, we conceived the idea of Management Action Zones (MAZs).
Yield assessments show considerable variation, limits imposed by population, growth of individual plants, or both
Some areas showed that yield was limited by plant number: establishment was poor. Others had the expected population, but low biomass: the plants were small due to some other limiting factor.
If we can identify zones easily, and determine the causes, we should be able to target a management response accordingly. So for this season, we set out a revised research aim.
What we want to know:
Can we successfully determine a management action zone in a field?
Why do we need to know this?
Develop a tool to increase uniformity and yield outcomes
Develop a tool to evaluate management practices and crop productivity
If we want to successfully determine a management action zone in a field then there are two main steps to achieve in this year’s work:
Confirm the relationship between digital data and crop model parameters
Does the relationship stay constant over time and sites?
How early in growth can a difference be detected?
Can the relationship be used to show a growth map across a field?
Develop an approach to gather information and ways to input and display results, initially using a website approach.
Can we integrate a plant count and yield information to start developing a management action zone?
How should this be put together in a way growers can start to use to gather information about their crops?
At the MicroFarm, we established six research zones based on paddock history and excessive wetness at establishment.
We have three paddock histories: two years of onion production with autumn cover crops of Caliente mustard, two years of onion production with autumn cover crops of oats, and no previous onion crops planted after previous summer sweetcorn and autumn sown rye grass. In each of these areas, we deliberately created sub-zones by applying about 45mm of spray irrigation as a “large rain event”.
Artificial heavy rain event applied after planting and before emergence
The impact of the artificial rainstorm is evident on images taken at the end of November.
The lasting effect of a heavy (artificial) rain event pre-emergence (right panel) shows low population and poor growth compared to areas without heavy rain (left panel)
We’ve aimed at a population of 580,000 plants/ha. With 8 rows in our 1.82m wide beds, we have seed at 72mm spacing in the row.
G& J Steenkamer sowing our onion crop.
After last harvest the beds, but not wheel tracks, were ripped to 450mm depth. Autumn planted Caliente and oat cover crops were mulched and incorporated in late June and the ground left fallow. Prior to sowing it was hoed and rolled.
Rain after planting had only minor impact, with a little soil capping in some areas.
Adrian Hunt is a crop scientist at Plant and Food Research.
Anthony (Tony) Davoren is a Director of Aqualinc with responsibility for the HydroServices business unit that provides irrigation and environmental management services; soil moisture, and water level and water meter monitoring. 
Now in year two of our 
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