What Could a “Formidable” El Niño Mean for New Zealand Avocado Growers?
Recommended reading: What Could a “Formidable” El Niño Mean for New Zealand Avocado Growers?
Avoscene June 2026
Phillip West, Research Manager, NZ Avocado
New Zealand meteorologists are warning that winter 2026 may mark the beginning of a potentially significant El Niño event, with some climate models suggesting it could become one of the stronger events seen in recent decades. El Nino and La Nina have been described as drivers of weather. A bit like our son driving the tractor on the orchard vs our daughter; both with very different driving styles. So, what might we expect? Perhaps a different route to were we’re going but definitely a few different things to keep an eye on to stay on track.
Recommended reading is an online article from Earth Sciences New Zealand, titled “From our forecasters: Winter 2026 may see the start of a formidable El Niño event”.
For New Zealand, El Niño years often bring patterns with high pressure systems more likely sitting over Australia and low-pressure systems more likely over New Zealand. This results in south-westerly and westerly airflow being more common often leading to reduced rainfall across the upper North Island and eastern regions. South-westerlies can be associated with colder temperatures but rather than Niwa forecasting a cold winter they think it is more likely that we may have a cold month or short periods of cold, but winter temperatures are expected to remain near average overall.
Forecasts are not certainties
Importantly, meteorologists stress that ENSO is only one driver of New Zealand weather patterns. Not every El Niño event behaves the same way, and local weather conditions can still vary considerably between regions and orchards.
However, the current forecast models show a strong consensus that El Niño conditions are likely to develop during winter 2026, with more than a 60% probability of the event becoming “strong” by spring.
That means now is a good time for growers to think proactively rather than reactively.
Key questions growers may want to ask now
- Is irrigation infrastructure operating at full efficiency, or will it be by spring?
- What soil moisture resilience actions are available if it looks like Spring/Summer are going to be dry? E.g. mulch availability, irrigation.
- Are shelter systems adequate for stronger/different wind exposure, particularly to the west and southwest?
While no forecast is perfect, understanding the potential implications of El Niño may help growers make earlier and more informed management decisions for the season ahead. Stay informed and educated so you can make your own decisions of what is appropriate for your own orchard.
Machine learning predicting ‘on’ and ‘off’ seasons
Recommended Reading: Machine learning predicting ‘on’ and ‘off’ seasons
Avoscene March 2026
Phillip West, Research Manager, NZ Avocado
Artificial Intelligence (AI) seems to be the buzz word at the moment with promise of huge efficiency gains, new business opportunities and potentially replacing some roles. Where’s the application for avocados you may ask? A case study out of South Africa provides an exciting example relating to crop estimation without a single person needing to set foot in an orchard.
AI or aspects of it allow large sets of data to be sifted through to find helpful information. In this example, freely available satellite imagery and weather variables were assessed to identify the variables associated with predicting ‘on’ or ‘off’ cropping. The model built with these variables accurately predicted ‘on’ and ’off’ cropping 88% of the time.
Why is this helpful for growers? Understanding if an orchard is in a on or off season is a critical aspect in crop estimation. The fact it can be collected at a block level without anyone needing to visit the orchard means there is huge labour savings and crop estimates could start to be collected at a national level almost at the click of a button. There are some limitations, including the need to have historic yield information to train the models but once the model is built, feeding additional seasons data into the model should improve accuracy over time.
Beyond the direct application of this work, it highlights the potential of AI to analyse large sets of variables to identify the factors that are most relevant to a particular outcome. The outcome could easily be fruit quality in market or orchard yields. Both of which we have started to look at using machine learning as well as crop estimation.
Free satellite imagery and some simple weather variables were used to build a model that could accurately predict ‘on’ and ‘off’ cropping 88% of the time.
Some of the most important variables identified were the bearing index (a measure of swing in yield from one season to another), yield in the year prior, vapour pressure deficit (VPD) maximum and minimum temperatures in winter and over flowering and canopy reflectance indices associated with tree canopy characteristics. An alternate bearing block is more likely to stay alternate and a low yield is likely to be followed by a higher yield the following season. Interestingly a high average maximum temperature in June was associated with blocks more likely to go into an ‘on’ season. High VPD or drying air was also associated with ‘on’ seasons. Cooler temperatures through July and through flowering were associated with ‘off’ seasons.
We have been working with Moshiur on assessing satellite-based crop estimation in New Zealand with some promising results. We will publish an update once the season has finished and we have reconciled production data for orchards in the 2025-26 season.
The recommended reading article is available online:
Rahman, M., Robson, A., Bekker, T. (2025). Machine learning approaches for assessing avocado alternate bearing using Sentinel-2 and climate variables—A case study in Limpopo, South Africa. Remote Sensing, 17, 3935
Lessons from California — Optimising Irrigation in Avocado Orchards
Recommended Reading: Lessons from California — Optimising Irrigation in Avocado Orchards
Avoscene December 2025
Phillip West, Research Manager, NZ Avocado
[stand first] Irrigation comes with very real electricity costs and often an additional cost of the water itself. And while irrigation is a cost it is also essential for fruit sizing, nutrient uptake and tree health, making its precise management important for an orchards bottom line.
When trying to optimise irrigation, it can pay to look to regions where water is far more expensive and strictly regulated. A recent study from California, “Quantifying evapotranspiration and crop coefficients of California ‘Hass’ avocado affected by various environmental and plant factors” by Montazar and colleagues (2025), provides valuable insights for any grower wanting to get more from every litre of water.
California’s avocado industry faces severe pressure from high water costs, salinity, and limited supply — challenges that force growers to refine irrigation. The research team measured actual crop water use and developed updated crop coefficient (Kc) values for ‘Hass’ avocados across five regions. They found that orchard water use varied widely with slope, canopy cover, soil type, and local climate — ranging from about 700 mm to just over 1,000 mm per season. Teruko Kaneko did some similar work in New Zealand and found water use varied between regions and with different crop loading. NZ Avocado use the crop factors Teruko developed to calculate the soil moisture updates shared regularly via Avoconnect.
This study reinforces a simple truth: water demand is variable from orchard to orchard. By using soil moisture monitoring to understand how much water trees actually use and how this changes through the season, growers can fine-tune irrigation schedules to save costs, avoid stress, and produce consistent, high-quality fruit.
Both recommended readings are available online
Montazar, A., Faber, B., Corwin, D., Pourreza, A., & Snyder, R. L. (2025). Quantifying evapotranspiration and crop coefficients of California ‘Hass’ avocado affected by various environmental and plant factors. Agricultural Water Management, 313, 109481.
Kaneko, T. (2020). ‘Hass’ avocado tree water use and the effects of water stress on fruit development. PhD thesis, University of Waikato, New Zealand.