Prediction of leaf nitrogen from early season samples and development of field sampling protocols for nitrogen management in Almond (Prunus dulcis [Mill.] DA Webb)

Protocols for leaf sampling in deciduous tree crops are commonly executed too late in the season and do not adequately consider field variability to be effectively used to guide N management. The goal of this study was to develop improved sampling strategies to optimize nitrogen management in deciduous tree crops. Leaf nutrient concentration from individual trees in four mature commercial orchards was collected (n =1148) for three consecutive seasons to develop nitrogen prediction models and to estimate the distribution of N values in orchards in July. Spatial variance analysis was used to determine optimal sampling strategies. Leaf nitrogen concentration in summer can be predicted (r(2) = 0.9) from the leaf N and B concentration in spring with the sum of K, Ca, and Mg equivalents. Mean field leaf nutrient concentration can be obtained by collecting one pooled sample per management zone composed of 30 trees each of which are at least 30 m apart. Using these methods the percentage of trees with leaf N above the recommended July critical value can be predicted accurately. Optimized methods for sample collection and models to predict mid-season leaf N from early season samples can be used to improve N management in deciduous tree crops.