Leaf analysis is currently the best method of determining the nutrient status of fruit trees.  One limitation of leaf sampling is the possible contamination by foliar sprays or other chemicals.  A few fungicides also contain nutrients.  For example, Ziram contains Zn and Kumulus contains sulphur.  If any spray has been applied to the leaves collected for leaf analysis, results could be invalid.  To reduce contamination, most foliar sprays, except calcium, are finished in orchards by June with leaf samples collected later in the growing season.  The exception to this would be spring Zn sprays that do not wash off the leaves easily.  Maintaining a consistent nutrient program and sample timing from year to year, allows annual results to be used despite contamination issues since nutrient trends can be monitored for the orchard.  Hanson (nd) recommends leaf tissue analysis on a 2-5 year cycle or more frequently in young plantings since nutrient status changes faster.

Tables 1, 2, 3 and 4 summarize the optimal ranges of essential nutrients for apple, cherry, peach and pear tree leaf tissue, respectively.  The values were obtained from various sources in North America (BC Tree Fruit; Crassweller, 2018; Hanson, nd; Sallato, 2018; Walsh & Seinhilber, 2005).  The values given are fairly consistent among the various sources.  In order to compare leaf tissue values, care must be taken in sampling leaves which is discussed next.

Table 1. Optimal nutrient ranges for apple trees

^a Optimum range for soft varieties, e.g. Golden Delicious and Macintosh.

Table 2. Optimal nutrient ranges for cherry trees

Table 3. Optimal nutrient ranges for peach trees

Table 4. Optimal nutrient ranges for pear trees

Leaf Tissue Sampling

Since different nutrients have varying mobility in fruit trees, their content in leaves will depend on timing and location.  A standard procedure for sampling needs to be followed if the values are to be compared with standard values in the literature.   Leaf samples should be taken from late July to early August to compare to the standard values for tree fruits.  Samples can be taken at other times during the growing season but, in this case, comparative samples should be obtained from both the area of concern and a “good” area to assess results. 

A sample consists of composite leaves from multiple trees within a comparable block within the orchard and should not represent more than 10 acres.  Since leaf mineral content is also affect by other factors than just timing and location, take each sample from trees of the same variety of the same age group on the same rootstock and of the same vigour in similar soil and management conditions.  The leaves are selected from the middle third of the terminal growth (this year’s growth) (Figure 1).  Select terminal growth which is growing upward and outward in an angle between 30° and 60° degrees. If the block to be sampled has a large number of trees, randomly select 50 leaves in a cross-section of the orchard (1 -2 leaves per tree); if the block is small, select 2 - 3 leaves from each tree for a total of 50 leaves.  Follow a pattern suitable for the block of trees. Use the X-pattern wherever possible (Figure 2). Do not take leaves from the outside trees on the border of a block or from trees within two rows of any roads.  Never sample damaged leaves.

Leaf samples are then air dried or dried at 65°C before being ground to get a homogeneous sample.  The dried samples are then weighed out for analysis.  Wet or dry ashing preparation methods are required for some instrumental analyses such as ICP-OES (inductively coupled plasma optical emission spectrometry).

Figure 1. Sampling diagram for leaves.

Figure 2. X pattern for sampling leaves in a block

Leaf chlorophylls in relation to nutrient assessment in fruit trees 

The photosynthetic pigment chlorophylls are enriched in leaf chloroplasts and exist in different forms in terrestrial plants. Adequate chlorophyll content in leaves is critical for maintaining the function of photosystems, which consequently influences the abundance and allocation of photosynthates that are essential to fruit development, tree growth and resilience. Leaf chlorosis. i.e., the loss of chlorophyll that results in yellow, pale or white leaf color, can indicate phytotoxicity, or, the decline in tree health triggered by various environmental cues including biotic pressures such as insect feeding and fungal infection, and abiotic stresses such as water deficit, waterlogging, abnormal soil pH, imbalance or deficiency in soil nutrient elements.

Chlorophyll a (C₅₅H₇₂MgN₄O₅) is the most widely distributed form in fruit trees. Deficiency in N and Mg can lead to chlorosis as these two elements are in the composition of the structure of chlorophylls (Taiz and Zeiger 2012). Iron, K, Mn and Zn can also cause leaf chlorosis, as they are involved in chlorophyll synthesis. The symptoms of deficiency of these mineral nutrients differ in visual characteristics and progression patterns of chlorosis (Table 1) (Barker and Pilbeam 2015). For example, Fe deficiency manifests in the youngest or terminal leaves first, and Zn deficiency impacts both new and old growth;  other deficiencies tend to start in older foliage. Deficiency in K, Mg, Fe and Zn is characteristic of interveinal yellowing, in contrast to the whole-leaf yellowing under N deficiency. Abnormally high level of chlorophylls, on the other hand, may imply over-fertilization. Therefore, chlorophyll assessment is often used during the initial diagnosis for nutrient disorders. In addition to the estimation on leaf greenness by visual inspection, instrumental measurement can be conducted to quantify chlorophyll content and chlorosis intensity. MC-100 (Apogee Instruments, Inc., Logan, UT, United States), SPAD 502 (Konica Minolta, Inc., Tokyo, Japan), CCM 200 (Opti-Sciences Inc., Hudson, NH, United States), CL-01 (Hansatech Instruments Ltd., Norfolk, United Kingdom) and atLEAF+ sensor (FT Green LLC, Wilmington, DE, United States) are among the commonly used hand-held chlorophyll meters. These instruments can instantaneously estimate the chlorophyll level in absolute unit of µmol per m² of leaf area, or in relative unit such as Chlorophyll Content Index (CCI) and Soil Plant Analysis Development (SPAD), based on the ratio of radiation transmittance or optical absorbance at dual wavelengths with one being strong chlorophyll absorbing and the other being near infrared (Uddling et al. 2007, Parry et al. 2014, Padilla et al. 2018). Typically, models should be developed for different species and cultivars, to accurately represent the leaf morphological and spectral traits. Leaf growth stage and position in canopy also influence chlorophyll content. Fully expanded leaves tend to have higher chlorophyll content than developing leaves, and leaves in shade higher than directly sunlight leaves. To assess the chlorophyll level of a tree, instrumental measurement is usually conducted on at least 10 fully expanded and directly sunlit leaves that are typical of the tree. More replications can increase the accuracy of the estimation. The optimal range of chlorophyll varies amongst tree crop species and cultivars. For example, the chlorophyll concentration in healthy leaves of Ambrosia apple is usually around 450 µmol m^-2 in August, as measured using the generic apple model of MC-100 chlorophyll meter; in Lapins cherry, leaves with normal photosynthesis capacity usually contain the chlorophyll concentration no less than 100 - 120 µmol m^-2 as measured using the cherry model of the same device. As chlorosis can be caused by multiple nutrient deficiencies, the usage of chlorophyll meter to identify a specific type of nutrient deficiency is limited. For example, although chlorophyll level is correlated with N level, and chlorophyll meters have been shown as a rapid and non-destructive diagnostic tool to assess leaf N status (Pole et al. 2013, Lee et al. 2019), the chlorosis-N deficiency analysis can be complicated by Fe deficiency that is commonly found in fruit trees (Morales et al. 1998), by sampling time during the growing season, and by foliar characteristics of scion cultivars (Neilsen et al. 1995). In an apple study by Lee et al. (2019), the best correlation was found from late June to late July. Starch accumulation in leaves in some cultivars such as Honeycrisp apple underlies zonal chlorosis; under such circumstance, the leaf chlorotic symptom is irrelevant to N deficiency. When chlorophyll content falls out of the optimal range, visual assessment on the patterns of chlorosis (Table 1) and other foliage symptoms such as interveinal or marginal discoloring, curling, stunted growth, scorched margin, withering and defoliation, can facilitate the initial identification of types of nutrient deficiency.On a larger-scale, recent advances in multispectral high resolution imagery of unmanned aerial system (Elarab et al. 2015) and in remote sensing imaging (Lu and Peng 2015, Li et al. 2018) provide new methods for the estimation of leaf chlorophyll level based on leaf reflectance spectra, and are becoming an available tool for precision nutrient management.

Table 5. Common nutrient deficiencies associated with leaf chlorosis, necrosis and discoloration.