[it only] after the fact."
For the last eight years, Robinson has collected data from thinning trials involving McIntosh, Gala, and Red Delicious varieties that were sprayed every three days during bloom with two spray combinations of MaxCel (benzyladenine) and carbaryl, and napthaleneacetic acid and carbaryl. In analyzing the thinning work and years of weather data, he found that tree sensitivity to the chemical thinners relates to temperature, sunlight, and the size of fruit at the time of application.
"The sensitivity of the tree (amount of thinning you get) relates to the temperatures preceding application, but more importantly, temperatures three to five days after application," Robinson said, adding that thinning is also very much affected by sunlight levels. "You can cause tremendous fruit drop just by shading the trees."
Robinson has used electronic fruit sensors in his trials to monitor fruit growth on a daily basis. Generally, modest growth occurred in the morning, with more growth in the afternoon, and then a slow down at night. Chemical thinners were applied to the fruit with sensors to learn how temperatures influenced fruit drop.
From his studies, he has learned that weather can affect thinning in several ways:
• Dark, cloudy weather of more than one day reduces the carbohydrate supply, resulting in greater natural drop and greater response to chemical thinning.
• High night-time temperatures greater than 65°F increase carbohydrate demand, thereby increasing natural drop and chemical thinning response.
• Very high daytime temperatures, greater than 85°F, increase carbohydrate demand and result in excessive thinning.
• Very cool temperatures, less than 65°F, reduce fruit carbohydrate demand, resulting in poor thinning response.
Robinson credits Cornell’s Alan Lakso for channeling years of data into a predictive computer model for apple thinning that considers many factors—temperature, photosynthesis, available sunlight, carbohydrate supply and demand. Though the data from the thinning trials involved in the modeling has been collected for many years, more individual growers in New York are installing their own weather stations that record temperatures and sunlight, enabling them to utilize a predictive computer model.
The thinning model was tested in two orchards during 2008—in eastern and western New York. For the eastern orchard, the model predicted a massive carbohydrate deficit before bloom due to warm temperatures after bud break. Without leaves at bud break to produce photosynthesis, the trees would have to draw on their own reserves. Bloom was earlier than normal, Robinson noted. "But by the time of petal fall, the carbohydrate deficit was closer to zero," he said.
At the time for the first thinning application, the weather forecast for eastern New York was favorable for carbohydrate conditions, he said. "The model indicated that growers would need to thin aggressively because they wouldn’t have any help from a carbohydrate deficit. By and large, it worked, and growers had a good crop."
However, the weather forecast for western New York during the same time span called for a week of cloudy weather, which would produce a carbohydrate deficit in the trees. "I told the growers not to be too aggressive with their thinning rates."
Daily thinning index
Robinson believes the model can help predict weather-induced carbohydrate deficits, which will help predict natural fruit drop.
"And, with the input of weather data, it can help us predict the sensitivity of the tree to chemical thinners," he said. "I think the model will allow us to make an estimate of the efficacy of petal fall thinners and help determine if we have to come back with a spray when fruit is ten millimeters in diameter."
With good weather forecasts, the model should be able to help predict what’s likely to happen in the next five to ten days, he said, adding that growers can then predict what response is likely from the thinner they put on.
"But the weakest part of the model is the ‘good’ weather forecast. We don’t always get accurate forecasts," he said.
Robinson and other Cornell scientists are working with researchers in other apple-producing areas, such as Michigan, to validate the model. He’s hopeful that the pool of data will lead to the development of a daily thinning index that could be published on Web sites.
"The daily thinning index would be a guide so growers would have a little less worry in the springtime and more confidence in what they’re doing," he said. "But it will not make chemical thinning perfect—there will still be variability in the response to thinning. But hopefully, it will help growers be able to predict what’s happening in the orchard."