Brown and graduate student Sebastian Saa are developing predictive models for leaf sampling nitrogen and other major nutrients.  Sampling models for leaves on either fruiting or non-fruiting spurs are under investigation. Initial results show that samples in April can predict July nitrogen leaf content and the percentage of trees below the July critical value. For instance, one model suggests that leaf nitrogen content above 3.3 percent in April will result in more than 95 percent of all trees being above 2.2 percent in July. These data will be further validated in 2012. Unfortunately, K concentration in leaves has been highly variable and not well correlated to yield, making leaf sampling difficult to interpret in this study.

Research is also looking at ways to help growers deal with variability in leaf sampling and the research aims to develop improved protocols for more meaningful interpretation. Nutrients vary greatly in the field and the approach of taking just a few samples from a large orchard does not accurately measure this variability. For instance, research indicates accurate N composite samples can be taken in April (43 days after bloom, +/- 6 days).  Depending on sample area and accuracy desired, the composite for one analysis will come from 18 to 28 trees, at least 90 feet apart, sampling at least eight leaves per tree at the 5- to 7-foot level.

Brown said the ultimate goal will be to help growers fold updated information into management decisions based on a nutrient budget being developed by Brown’s research associate Saiful Muhammad that hits the Four R’s to optimize production and minimize environmental impacts in fertilizer management.

For more information and access to research posters and annual reports related to almond nitrogen research, go to and choose Air Quality and Water Quality.

This is the second in a series on nitrogen fertilization in almonds. Part 1 is here.