In Situ Measurement of Pecan Leaf Nitrogen Concentration using a Chlorophyll Meter and Vis-near Infrared Multispectral Camera

Knowledge of foliar nitrogen (N) concentration is important in pecan [Carya illinoinensis (Wang.) K. Koch] management protocols. Lower cost and/or rapid methods to determine foliar N are desirable and may result in improved management strategies as well as enable precision agricultural practices to be deployed in pecan production. This study investigates using a portable chlorophyll meter and Vis-NIR camera to rapidly determine pecan foliar N in situ. Relationships of SPAD values from a chlorophyll meter (Minolta SPAD 502Plus) and vegetative indices calculated from camera image data to foliar N determined by chemical analysis were investigated. SPAD readings were taken monthly from May through October on ‘Pawnee’, ‘Kanza’, and ‘Maramec’ pecan cultivars in Oklahoma in 2010. Images of the same ‘Pawnee’ and ‘Kanza’ trees were collected in September and October of 2010 with a truck-mounted multispectral camera using ambient light. Correlation of foliar N to SPAD values was poor in May for all cultivars but distinct significant linear relationships were found for ‘Maramec’ and ‘Pawnee’ for each of the other months tested with R ranging from 0.40 to 0.87. Data from ‘Kanza’ had significant relationships in June and October with R of 0.39 and 0.72, respectively. Normalized difference vegetative index (NDVI) and reflectance data extracted from Vis-NIR camera images were significantly correlated to foliar N in both months of the study on ‘Pawnee’ but only in September for ‘Kanza’. The various relationships had R between 0.21 and 0.51. Nitrogen management in pecan orchards is important for tree health, optimizing yield, and managing alternate bearing (Conner and Worley, 2000; Smith et al., 2007; Wood et al., 2004). Overapplication of N wastes resources and can cause environmental harm. Availability of N depends not only on fertilizer application rate, type, and time of application, but also on a variety of cultural practices and environmental conditions, including soil nutrients and properties, weather and climate, irrigation practices, tree condition, orchard floor management, and nut production (McDonald et al., 1991; Soria-Ruiz et al., 2007; Ye et al., 2008). Soil tests and leaf analysis are used to measure N; however, leaf analysis is widely used commercially in pecan to assess N concentration during the growing season because it provides a direct measurement of nutrient status in the tree. The traditional practice for measuring N levels in a pecan orchard consists of handharvesting specific leaves that are then dried and sent to a laboratory for chemical analysis. This process takes considerable time and is typically used to guide the subsequent year’s fertility program rather than adjusting N in the current year. Generally only a subset of the trees in an orchard is tested to reduce cost. A sensor that provides an immediate indication of pecan foliar N in the field would be desirable if it provides adequate performance at a reasonable cost. Such a sensor would also be a key component to enable precision agriculture practices in pecan production. Much of the N in a leaf is partitioned in chlorophyll; thus, a sensor that measures chlorophyll can often be used to quantify the amount of N in a leaf (Filella et al., 1995). The basis for most optical sensing of N in leaves is based on chlorophyll’s spectral response to light. Chlorophyll absorbs blue and red light (l 450 and 650 nm, respectively) and reflects near infrared (NIR) light (l greater than 750 nm). The intensity of transmitted and/or reflected light at these wavelengths can be used to form empirical relationships, which estimate chlorophyll concentration and, consequently, N concentration in a leaf (Richardson et al., 2002). A SPAD meter (Konica Minolta, Osaka, Japan) is a handheld device that measures light intensity at wavelengths of 650 and 940 nm transmitted through a 2 · 3-mm area of a leaf clamped in the instrument. The SPAD meter calculates a unitless value between 1 and 100 that has been shown to be positively correlated to leaf chlorophyll concentration. Regression analysis can then be used to predict foliar N from SPAD readings (Markwell et al., 1995). Originally developed for rice, SPAD meters have found use on a variety of field and tree crops for predicting N concentrations (Chang and Robison, 2003; Gianquinto et al., 2004; Neilsen et al., 1995; Perry and Davenport, 2007; Simorte et al., 2001; van den Berg and Perkins, 2004; Wood et al., 1992). Reflectance measurements of Vis-NIR light have also been used to estimate chlorophyll and N status of plants. NDVI is the most widely used measurement and is computed from the intensity of reflected red and NIR light using the following equation: NDVI = (INIR – Ired)/(INIR + Ired). Empirical relationships of NDVI to chlorophyll concentration and N status have been developed for many crops (Hansen and Schjoerring, 2003; Jones et al., 2007; Ma et al., 1995; Plant et al., 2000; Reyniers and Vrindts, 2006). NDVI can be calculated from remotely acquired multispectral digital camera image data or from closeproximity sensors. Remote imaging systems generally measure reflected ambient light, whereas some close-proximity sensors collect reflected light that originates from the sensor itself (Jones et al., 2007). In both cases, the intensity of incident light is required to accurately determine relative intensity of the reflected light to control sensor error. At high levels of biomass, NDVI tends to becomes less sensitive to chlorophyll concentration because reflected red light intensity from leaves asymptotically approaches a minimum. In plant systems where chlorophyll levels are high, vegetative indices (VIs) that include green reflectance may have better performance predicting foliar N than NDVI. Gitelson et al. (1996) compared NDVI to green-NDVI (GNDVI) obtained from satellite images of Norway maple (Acer platanoides L.) and horse chestnut (Aesculus hippocastanum L.) trees and found GNDVI resulted in more accurate predictions of chlorophyll content Received for publication 2 Apr. 2012. Accepted for publication 3 May 2012. To whom reprint requests should be addressed; e-mail [email protected]. HORTSCIENCE VOL. 47(7) JULY 2012 955 MISCELLANEOUS