Apple and pear production is vulnerable to climate change and research is underway to help understand the affects and find ways to reduce any negative impacts.

This project aims to broadly answer the following questions:

  1. What are the potential impacts of a changing climate on apple and pear production systems in Australia?
  2. What are some of the options for adaptation to reduce risk and take advantage of potential opportunities?

Apple and pear production systems are sensitive to temperature throughout the growth cycle. These crops are dependent on a dormant period which requires accumulation of chill during the autumn and winter to promote bud burst and flowering. During the subsequent fruit growth phase, fruit size and quality are affected directly by climate, through temperature-driven impacts on growth processes, colour development and sunburn damage.

This project will collect flowering, yield and fruit quality data for a number of commercial apple and pear varieties from three pome fruit growing regions in Australia (Stanthorpe, Qld; Tatura, Vic; Manjimup, WA). Initially, the data will be used to help understand the relationships between:

  • temperature and flowering time and quality, and
  • temperature and fruit yield and quality.

From this information, the potential impacts of projected changes in climate will  be determined. The effectiveness of different types of netting, as well as  variety selection will be assessed as potential adaptation options.

Regional Chill Accumulation

Cumulative Chill Portions 2013 and 2014

Video lecture: Dealing with seasonal climate risk and extreme weather events (15 min 44 sec)

Dealing with seasonal climate risk & extreme weather events - Dr Ian Goodwin & Dr Rebecca Darbyshire

Dealing with seasonal climate risk and extreme weather events, a presentation by Dr Ian Goodwin, Agriculture Victoria, at the Regional Innovation Forum - ‘Delivering innovation through the horticulture supply chain’ Horticulture Centre of Excellence, Tatura May 2016

Transcript: Dealing with seasonal climate risk & extreme weather events - Dr Ian Goodwin & Dr Rebecca Darbyshire

Just first up, I'd like to acknowledge my co author up there, Rebecca Darbyshire. She did most of the modelling and risk analysis work that I'll present. So what I'm going to do is provide a bit of a snapshot of some of the results from these two national projects that we're looking at climate change, the response of fruit trees to climate change. Specifically I'll focus on talking about chill, chill requirements, flowering and sun damage.

So, just a little bit about each of these projects. The first one there, Crossing the Thresholds, was funded by the Department of Agriculture and Water Resources as part of the, what was called the Fill in the Research Gap initiative. The project was led by the University of Melbourne. Sigfrido was the project leader. Sigfrido Fontes is going to talk after me. And partners in that project, collaborators DAF Queensland DAF Western Australia, and Tasmanian Institute of Agriculture. The second project was funded by Hort Innovation through the Apple and Pear levies. Our project leader there was Heidi Parks, and it was she works for Queensland DAF. And down at the bottom a whole lot of logos there of all those collaborators involved in both, both those projects.

The sites where we well, first of all, some of these sites we were to, collected some field data on, on, on phenology. We also managed to get historical data sets on, on phenology, in other words, you know, flower event, flower timing and budburst flower timing and harvest dates, for example. And also we use those sites that are listed up there for our projections. In other words, what effect climate change, increasing temperature might have on the events of chill requirements, flowering sunburn damage, for example and we also did some analysis of yield as well.

So first of all, I'll talk a bit about, give you a snapshot of some results on winter chill. So, these are the models that, that we use to, to do the, these are climate models, so, they're not models that we actually develop ourselves, we're more interested in the models that can predict you know, flower timing and yield, for example. These are, as I said climate models, and what you know, Rebecca actually went through a pretty lengthy process, because there's a whole lot of these climate models out there, and what she did was actually select the most appropriate for the analysis that we want to do in terms of risk. So she picked on what she describes as the best model. This one here and this is a low emission scenario. And this is what she called a worst model. In other words, the model that would, was suggesting, the greatest increases in, in temperature. and a high emissions scenario.

So, the figures here are just to show two sites, Tatura and Huonville in Tasmania. We've got along the bottom axis here our historical, in other words a 30 year average of our chill and then the predicted 2030, 2050 and 2090. And each one of these, well this bar here is actually a historical range of till for Tatura.

And so it ranges from 76.8 to 90.1 chill portions, and what the, these models are predicting is overall a pretty much a decline as we would expect in our chill from obviously increasing temperature. So, the blue bar is our best case scenario and the red bar is our worst case. So, by the time we get to 2090, we've had this dramatic in the worst case situation. In other words, the, the greatest warming that we get and the highest emissions. We've basically gone from, the range of 76.8 to 90.1 down to 38.1 to 50. 9. Similarly, of course, same sort of trend in in Huonville. So that's, you know, climate based, that's weather and the actual calculations of chill from that weather data. So what does that tell us? What we wanted to look at is, of course, what's the risk for our fruit industries in terms of that, that reduction in chill. So, this figure here is to try and demonstrate that risk for a whole lot of different sites, those dots on the map of Australia.

And in this particular example, it's for Lapin cherries, Lapins, and to, well, we've got down the bottom here, historical 2 30, 2 50 and two 90 again. And so the different colours denote the risk, the risk of actually not getting sufficient chill. So in other words our low risk is saying that in nine out of 10 years, we'll actually get sufficient chill to adequately, you know, get good flowering and good fruit set in production. So in other words, all these green, solid hatch solid areas down here there's really, you know, very low risk from climate change on, chill requirements. So, take for example Tatura here, you can see that historically no problem, of course. And then once we move into 2030, there's still, you know, a low risk of chill having an impact on flowering. Once we get to 2050, what we find is that there's two, two of the, there's the worst case and best case scenarios built into this. So the background colour, the yellow, is basically this medium risk, and that's associated with the worst case scenario, and the hashed are associated with the best case scenario. So there's a range, in other words, to Tatura, from a medium to low risk by 2050. Once we get to 2090 at Tatura, with Lappins, we start getting into a high risk and a worst case scenario, and a medium risk with respect to a best case scenario.

So we did that, as I said, for a whole lot of different cultivars where we could actually get from the literature what their chill requirements were. And if anyone wants more of this information, we've got appropriate references available.

So moving on to flowering Again, a snapshot of some of the results. So of course what we wanted to do with to look at the effect of climate change on flowering was to have a pretty good model to be able to predict flower timing. And as you all, well, you know, all fruit growers are aware that there's a pretty big variation in the range of flower timing. And this is some data for Crips Pink, and these are different sites down here you know, ranging from, Western Australia, Queensland New South Wales, South Australia, Tasmania, Victoria. And you can see the range in, so this is historical data, this is the range in full bloom for Applethorpe, for example. So, it's quite a bit. And down here we've got Donnybrook, this is the range for Donnybrook. The important thing to note here is that’s sites like Batlow, Lenswood, Yarra Valley, Tatura and Applethorpe, even though there's a range in data, the, the mean of these is not that dissimilar. It's only the Donnybrook Western Australia, Manjimup in Western Australia, these two points down here, where we start seeing quite a difference in the time of flowering. And interestingly it's consistently later at those Western Australian sites. At any rate, what we wanted to try to do was come up with a model to be able to predict full bloom timing, so that then we can do an analysis of future climates on flower timing.

In the literature, this was published by a lady, Catherine Pope, in about 2014 on almond. And this was a new development in terms of modelling flower timing, and it's called the Chill Overlap Model. And basically, what happens with the Chill Overlap Model, you've got this minimum chill requirement here, okay, as you go up here. This is a model, this is a just a presentation of the model itself without any data in it. But this is our minimum chill requirement up here. And once you go once, you're getting more chill as you go along this axis here, what happens is that the heat requirement for flowering, in other words, when you met chill, the historic the way that people have previously done is there's like a two step process. You get chilling and then you get heat and the tree's flower. What this is saying is that there's that overlap. So once you get past that minimum chill requirement, you still start, still keep accumulating chill, and what happens is the heat requirement starts to go down, right? So as you go along this, that's more chill. Once you've met that chill requirement, your heat requirement, you know, you go up here, your heat requirements becoming less. So we applied that to a whole lot of Pink Lady data or Crips Pink data that we had across all the all these sites in southern Australia and into Queensland, and it fits extremely well. Down here we've got our, this is actually data from Batlow, and these, all this data here is incorporating those sites from Queensland to Western Australia. So this provided us with a model that we thought was reasonably good at predicting our flower timing, and we could use that for our projections. So we did that well, as I said before, Rebecca did that and this is trying to present some of that data on the effect of 2030, 2050 and 2090, the effect on flower timing. So the analysis, what it comes out with, and this is again based on that the Pink Lady data, the Pink Lady data that we have, so this is for Pink Lady you can see that in 2030 there's little change at these sites. So, these triangles and squiggles, the triangles, basically if they're pointing up, means that there's a delay in flowering. If they're pointing down, it means that flowering is earlier. Whereas the squiggle is that there's no effect. So, overall, at these sites, and also the size of the triangle denotes the strength of the change as well. But by 2030, we've come to basically the conclusion there's little change in flower timing. By 2050 we're starting to see a delay at these sites, apart from Batlow, which goes the opposite way. And then again, 2090 it's stronger, a delay in flowering, with the exception still being Batlow, it being a much colder site.

Sun damage. So, what we also wanted to look at is the third component of this was the results I'll present is just a little bit on the effects of climate change on sun damage. So we did a lot of observations of fruit surface temperature in, in netted and non netted orchards, and we came up with an approximation of when damage is likely to occur based on air temperature.

So, and that's because air temperature is what you can access in terms of you know, future climates. So, what we came up with is in a non netted orchard to get browning and air temperature of about 34.1 degrees, could approximate a fruit surface temperature that was, greater than 46 degrees Celsius and which would cause browning. Similarly necrosis, you know, in a non netted orchard, 37.9 air temperature, and that was going to cause fruit surface temperature that was a above the 52 degrees threshold for necrosis to occur. And so when we applied that to our projections of what might happen in the future, this is trying to demonstrate the number of days when those air temperature reached, or reached those thresholds for both netted and non netted orchard. So we've got the historical here, this is for January by the way, number of days in January, so historically in a, in an unnetted orchard, you're likely we get on average about six days that are above that air temperature threshold to cause sun damage. In a netted orchard, that drops down to about two, this is Tatura by the way, 2030, these of course start going up. And, in terms of, the projections out to 2090, we're getting 12, 13 days in an unnetted orchard. And the effect of netting is to reduce that down to about five days. Huonville, Tasmania, well, they'll even start to get some risk of sun damage in non netted orchards once you start getting out to 2030.

In conclusion, so, first of all, winter chills expected to decline. Some regions will not meet crop specific chill requirements. The chill overlap model is quite a good predictor of flower timing. And we've shown that with the data we've collected for Crisp Pink. Overall, flower timing will be delayed, but that's not really going to occur out until 2050 and 2090. And the last two dot points there is that air temperature can be used to approximate the risk of sun damage, and of course netting, these results will substantially reduce that risk now but also into the future. Thanks.

A global evaluation of apple flowering phenology models for climate adaptation

ScienceDirect article S0168192317301284

This study presents the first evaluation of apple flowering phenology models using data from 14 sites across the globe. The dataset includes large variability in growing climates, a prerequisite to investigate phenology models for use in climate change applications. Two flowering stages, early and full, were investigated allowing for unique model evaluation based on both statistical performance and biological assumptions. Two overarching phenology models (Sequential and Chill Overlap) and two sub-models of chill (Dynamic and Triangular) and heat (GDH and Sigmoidal) were tested. Flowering times from the different sites illustrated the differing effects of contrasting winter and spring temperatures. Sites with similar springtime temperatures, but different winter temperatures, had different flowering patterns (warmer winter sites flowered later). Across all analyses, results from the Chill Overlap model were better than those from the Sequential model. Of the Chill Overlap models, those fitted with the Triangular or Dynamic chill model and the GDH heat sub-model performed well statistically and met the assumptions of the model across both flowering stages. The mild sites in the analysis were least well represented, regardless of model selection. This global evaluation demonstrated that flowering modelling in temperate fruit trees would progress through appropriate choices of overarching model, sub-models and parameters.

Project Details

Project leader: Dr Heidi Parkes,

Delivery partners: DAFF QLD, Ag Vic, DAF WA

This project was funded by Horticulture Australia Limited, the Apple & Pear (R&D) levy, DAFF QLD, Ag Vic & DAF WA.