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Chlorophyll meters are used for non-destructive estimation of leaf nitrogen (N). The objective of this study was to evaluate the readings with several chlorophyll meters (SPAD-502, atLEAF, and CCM-300), different sampling sites on leaves, number of leaves used for sampling, and different types of leaf N sampling on estimation of N in leaves of potted poinsettia (Euphorbia pulcherrima) “Prestige Red.” Results showed that all meters gave readings that were correlated for N determination and also were correlated with each other. SPAD and atLEAF showed interaction between different N treatments and different sampling sites on the leaves, while CCM readings were affected by different sampling sites on the leaf. atLEAF readings showed interaction between number of leaves sampled and different N treatments. Thus, during sensor-based leaf N estimation, sampling site on leaf, number of leaves sampled, and stage of plant development should be considered to minimize error.
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Journal of Plant Nutrition
ISSN: 0190-4167 (Print) 1532-4087 (Online) Journal homepage: http://www.tandfonline.com/loi/lpla20
Relationship between chlorophyll meter readings
and nitrogen in poinsettia leaves
Bruce L. Dunn, Hardeep Singh & Carla Goad
To cite this article: Bruce L. Dunn, Hardeep Singh & Carla Goad (2018) Relationship between
chlorophyll meter readings and nitrogen in poinsettia leaves, Journal of Plant Nutrition, 41:12,
1566-1575, DOI: 10.1080/01904167.2018.1459697
To link to this article: https://doi.org/10.1080/01904167.2018.1459697
Published online: 01 May 2018.
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Relationship between chlorophyll meter readings and nitrogen
in poinsettia leaves
Bruce L. Dunn
a
, Hardeep Singh
a
, and Carla Goad
b
a
Department of Horticulture and Landscape Architecture, Oklahoma State University, Stillwater, OK, USA;
b
Department
of Statistics, Oklahoma State University, Stillwater, OK, USA
ARTICLE HISTORY
Received 29 June 2017
Accepted 28 November 2017
ABSTRACT
Chlorophyll meters are used for non-destructive estimation of leaf nitrogen
(N). The objective of this study was to evaluate the readings with several
chlorophyll meters (SPAD-502, atLEAF, and CCM-300), different sampling
sites on leaves, number of leaves used for sampling, and different types of
leaf N sampling on estimation of N in leaves of potted poinsettia (Euphorbia
pulcherrima)Prestige Red.Results showed that all meters gave readings
that were correlated for N determination and also were correlated with each
other. SPAD and atLEAF showed interaction between different N treatments
and different sampling sites on the leaves, while CCM readings were affected
by different sampling sites on the leaf. atLEAF readings showed interaction
between number of leaves sampled and different N treatments. Thus, during
sensor-based leaf N estimation, sampling site on leaf, number of leaves
sampled, and stage of plant development should be considered to minimize
error.
KEYWORDS
greenhouse; nutrient status;
sensor
Introduction
Nitrogen (N) is an essential element for plant growth, and needs to be applied in the correct amount
required by a plant. If applied more than needed by a plant, runoff will lead to environment pollution
as it moves to ground and surface water, whereas too little application of N will lead to lower yield
than crop potential and economical losses (Bullock and Anderson 1998). Besides effecting plant qual-
ity, N concentration of a plant affects pest and disease defense and tolerance to various stresses. The
requirement of N fertilizer rate varies among eld and production practices (Schmitt and Randall
1994). So, researchers are using various devices like chlorophyll meters to collect reectance measure-
ments to assess N status of crops without affecting crop yield and plant quality in a destructive deter-
mination (Rorie et al. 2011).
Chlorophyll, is a good indicator of leaf N concentration (Lohry and Schepers 1988). Modern agri-
cultural farming is interested in fast, non-destructive methods for estimating chlorophyll and N con-
tent, whereas old methods of using organic solvents to estimate leaf chlorophyll and N are still in use
but are time consuming and destructive methods (Murdock et al. 1997). There are non-destructive
hand-held devices available such as the soil plant analysis development (SPAD) and atLEAF sensors,
which can be used to measure chlorophyll content of green leaves (Loh, Grabosky, and Bassuk 2002).
The chlorophyll content meter (CCM) is also one of these devices (Ghasemi et al. 2011). Transmission
of red and near-infrared light through leaves is measured by these chlorophyll meters (Scharf, Brouder,
and Hoeft 2006). Since most leaf N is in proteins associated with chlorophyll, these instruments used
CONTACT Bruce L. Dunn bruce.dunn@okstate.edu 358 Ag Hall, Department of Horticulture and Landscape Architecture,
Oklahoma State University, Stillwater OK 74078-6027, USA.
© 2018 Taylor & Francis Group, LLC
JOURNAL OF PLANT NUTRITION
2018, VOL. 41, NO. 12, 15661575
https://doi.org/10.1080/01904167.2018.1459697
for estimating chlorophyll content can be used to correlate determinations with N content of a leaf
(Paven et al. 2004).
SPAD estimates chlorophyll content of a leaf by measuring transmittance of light through a leaf at
wavelengths of red (650 nm) and near-infrared (940 nm). According to Hawkins et al. (2007), the low-
est limit of wavelength used by SPAD, 650 nm, coincides with the spectral region associated with maxi-
mum chlorophyll activity, whereas the upper limit, 940 nm, compensates for factors such as leaf
thickness and water content. The SPAD sensor has been reported to be correlated with leaf N content
in various eld and ornamental crops such as wheat (Triticum aestivum L.) (Jia et al. 2007), corn (Zea
mays L.) (Blackmer and Schepers 1995; Fox, Piekielek, and Macneal 2001), silver birch (Betula pendula
Roth) (Uddling et al. 2007), geranium (Pelargonium sp. L.) (Dunn, Shrestha, and Goad 2015), and
dianthus (Dianthus chinensis L.) (Basyouni, Dunn, and Goad 2016).
The atLEAF sensor is a recently developed inexpensive alternative for SPAD and measures trans-
mittance of light at wavelength of red (660 nm) and near-infrared (940 nm) (Zhu, Tremblay, and Liang
2012). SPAD and atLEAF report unitless values (Basyouni and Dunn 2013). Basyouni, Dunn, and
Goad (2015,2016) reported the use of atLEAF for estimating N status in poinsettia and dianthus and
concluded that atLEAF was more correlated to leaf N than normalized difference vegetation index
(NDVI). Zhu et al. (2012) reported positive correlations between SPAD and atLEAF for canola (Bras-
sica napus L.), wheat, barley (Hordeum vulgare L.), potato (Solanum tuberosum L.), and corn.
The CCM sensor measures transmittance of light through a leaf at wavelengths of red (635 nm) and
near-infrared (935 nm) (Richardson, Duigan, and Berlyn 2002). The sensor measures a chlorophyll
content index (CCI), which is correlated with chlorophyll content in leaves (Biber 2007). Ghasemi
et al. (2011) reported the use of CCM for estimation of N content and chlorophyll content in Asian
pears (Pyrus serotina Rehd.). Cate and Perkins (2003) reported use of CCM for chlorophyll estimation
in sugar maple (Acer saccharum Marshall). All three devices operate in a similar manner by tting
over the top and bottom of a portion of the leaf to be sampled and have the ability to store, recall, and
average values. Some studies reported no correlation between chlorophyll meters and leaf N content.
For example, non-signicant correlation was reported between SPAD and leaf N for red maple (Acer
rubrum L.) by Sibley et al. (1996). Lack of correlation may be due to a number of factors such as time
of sampling and varying locations on a single leaf (Linder 1980; Dunn and Goad 2015), leaf age (Loh
et al. 2002), water stress (Basyouni, Dunn, and Goad 2015), and leaf thickness (Peng et al. 1992). So,
the objectives of this study were to determine 1) the effect of SPAD, atLEAF, and CCM on leaf sam-
pling positions and number of leaves on the ability to estimate leaf N, 2) the effect of different leaf sam-
pling methods on estimating leaf N, and 3) if SPAD, atLEAF, and CCM are correlated with each other
and leaf N in potted poinsettia.
Materials and methods
Plant material and growth conditions
On 20 August 2014, rooted cuttings of poinsettia Prestige Redwere obtained from SHS Grifn (Lisle,
IL). Cuttings were transplanted into standard (15.2-cm diameter and 1.35-L volume) pots with about
0.35 kg 902 a peat-based medium (Metro Mix, Sun Gro Horticulture, Bellevue, WA) 5 days later. A sin-
gle plant was placed in each pot, and plants were grown in the Department of Horticulture and Land-
scape Architecture Research Greenhouses at Stillwater, OK, under natural photoperiods. Temperature
was set at 21/14C day/night with a photosynthetic photon ux density (PPFD) range of 600 to
1200 mmol m
¡2
s
¡1
at 1200 HR.
Treatment conditions
Plants were divided into treatments of either 150 mg L
¡1
or 250 mg L
¡1
20N-4.37P-16.6K (Jacks Pro-
fessional General Purpose acidic fertilizer, J.R. Peters Inc., Allentown, PA) added with irrigation water.
Pots were drip irrigated at a rate that allowed media saturation and »20% leaching as needed. Plants
JOURNAL OF PLANT NUTRITION 1567
were pinched at a seven internodes height on 8 September 2014, and fungicide (Banrot, Everris NA
Inc., Dublin, OH) was applied. Insecticide (TriStar, Cleary Chemical Corporation, Dayton, NJ) was
used to control whiteies.
SPAD, atLEAF, CCM, plant growth, and leaf N correlation determination
Individual plants were scanned from the same ten pots per treatment using a SPAD-502 chlorophyll
meter (SPAD-502, Konica Minolta, Japan), atLEAF chlorophyll meter (FT Green LLC, Wilmington,
DE), and CCM-300 chlorophyll meter (Opti-Sciences, Inc., Hudson, NH) every week (total of six rat-
ing dates) in the morning starting 46 days after planting (DAP). For each pot, SPAD, atLEAF, and
CCM measurements were taken from one, three, or ve mature leaves from the middle to upper level
of the plant either at the leaf tip, leaf blade not including the midrib, or leaf base not including the mid-
rib. Leaf foliar analysis consisted of collecting either ten fully developed leaves with petioles from a sin-
gle plant per treatment, ten fully developed leaves without petioles from a single plant per treatment,
ten leaves with petioles from three different plants per treatment and bulked, ten leaves without
petioles from three different plants per treatment and bulked, ten leaves from ve different plants per
treatment and bulked using only the tip portion (top »1.5 cm), ten leaves from ve different plants
per treatments using only the blade portion (middle »2.02.5 cm), ten leaves from ve different plants
per treatments using only the base portion with petioles (bottom »2.0 cm), and ten leaves from ve
different plants per treatments using only the base portion without petioles (bottom »2.0 cm) for total
leaf N per sampling treatment weekly. Leaf samples were analyzed for total N content (g kg
¡1
DM) by
the Soil, Water and Forage Analytical Laboratory (SWFAL) at Oklahoma State University, using a Car-
bon and Nitrogen Analyzer (TruSpec LECO Corporation, St. Joseph, MI). At the end of the study, data
was collected on plant height (from the top of the pot to the highest point) and width (average of two
perpendicular measurements), and shoot weight (stems cut at media level) then dried for 2 days at
52.2C from the same ten plants weekly.
Statistics
Pots were arranged in a completely randomized design (CRD) with ten single pot replications. SPAD,
atLEAF, and CCM variables were analyzed using linear mixed models for repeated measures. Fixed
effects in the analysis included the fertilizer treatment, sampling location on the leaf for the sensor
position, the number of leaves sampled per plant, and DAP. Post hoc analyses of the means were con-
ducted using least signicant difference (LSD) pairwise comparisons. Correlation analyses of SPAD,
atLEAF, and CCM readings at the three sampling locations with the eight different leaf N sampling
methods were also computed for each fertilizer treatment level. All tests of signicance were performed
at the 0.05 level except correlations and main effects which were at the 0.05, 0.01, and 0.001 level. Data
analysis was generated using SAS/STAT software, version 9.4 (SAS Inc., Cary NC).
Results
Leaf sensor locations and sampling dates
For either SPAD or atLEAF, a signicant interaction occurred between number of weeks for sampling
and sampling location within the leaves (tips, middle, and base), but not for CCM (Table 1). In all three
leaf locations, SPAD and atLEAF readings increased with increasing DAP, but atLEAF reading at 81
DAP was lower as compared to reading on 74 DAP for all sites on leaf. However, SPAD showed the
greatest readings if leaves were sampled at 81 DAP, a result that was different than all other sampling
dates (Table 2). atLEAF readings for leaves sampled after 74 DAP, except 81 DAP, were greatest, and
were different than atLEAF readings at other sampling dates and were lowest when leaves were sam-
pled after 46 DAP for either SPAD or atLEAF (Table 2). For every sampling date and sampling loca-
tion, atLEAF readings were greater than SPAD readings (Table 2).
1568 B. L. DUNN ET AL.
atLEAF, number of leaves sampled, and fertilizer treatment
For atLEAF, a signicant interaction occurred between treatments of fertilizer and number of leaves
sampled (Table 1). For fertilizer treatment of 150 mg L
¡1
, atLEAF readings were greatest if three
mature leaves were sampled, a value that was not signicantly different than atLEAF readings from
one or ve mature leaves of a plant (Table 3). For fertilizer treatment of 250 mg L
¡1
, atLEAF readings
were greatest if one or ve leaves were sampled; however, there was no difference between three and
ve leaves (Table 3).
CCM, sampling dates, and fertilizer treatment
For CCM, a signicant interaction occurred between treatments of fertilizer and sampling date
(Table 1). For fertilizer treatment of 150 mg L
¡1
, the CCM readings were greatest for leaves sampled
81 DAP, a value that was different than CCM readings at all other dates of sampling, whereas for fertil-
izer treatment of 250 mg l
¡1
, the CCM readings were greatest for leaves sampled at 74 and 81 DAP, for
which readings were different from CCM reading at all other sampling dates (Table 4). Lowest CCM
readings occurred for leaves sampled at 53 DAP for both fertilizer treatments (Table 4).
Leaf sensors, leaf locations, and fertilizer treatments
CCM was affected by location of leaf sampling, and SPAD was affected by treatment of fertilizer
(Table 1). CCM readings were greater if leaves were sampled from the middle of leaf blade not
Table 1. Test of results using three different optical sensors, two different fertilizer treatments, three leaf sampling methods, over a
six-week period, using different sampling locations within a leaf on poinsettia Prestige Redin 2014.
SPAD-502 atLEAF CCM-300
Treatment (TRT)
z
 
NS
Leaf (LF)
y
NS NS NS
Week (WK)
x
  
Sampling location (SL)
w
  
TRT £LF NS
NS
TRT £WK NS NS
WK £SL

NS
z
Treatments of either 150 mg L
¡1
or 250 mg L
¡1
20N-4.37P-16.6K (Jacks ProfessionalÒGeneral Purpose acidic fertilizer, J.R. Peters Inc.,
Allentown, PA).
y
Means signicant or nonsignicant (NS) at
P<0.05,

P<0.01, and

P<0.0001. Sensor readings were taken from one, three, or
ve mature leaves from the middle to upper level of the plant.
x
Sensor readings were taken every week (total of six rating dates) in the morning starting 46 days after planting.
w
Sensor readings were taken either at the leaf tip, from the middle of the leaf not including the midrib, or toward the base of the leaf
not including the midrib.
Table 2. Effects of SPAD and atLEAF sensor readings on leaf sampling location over six weekly sampling days after planting (DAP)
using poinsettia Prestige Red.
Sampling location
z
46 DAP 53 DAP 60 DAP 67 DAP 74 DAP 81 DAP
SPAD (unitless)
Leaf tip 45.3h
y
46.5gh 49.3f 50.1def 50.7de 52.1bc
Leaf blade 46.3gh 49.4ef 50.7d 50.9cd 52.5b 53.8a
Leaf base 46.2gh 47.4g 49.8def 51.0cd 52.4b 53.9a
atLEAF (unitless)
Leaf tip 49.7i 51.8g 53.3ef 54.3de 55.5bc 55.3bc
Leaf blade 50.1i 52.8f 52.9f 54.9cd 56.8a 56.0ab
Leaf base 50.5hi 51.5gh 52.9f 54.6cd 56.3ab 56.0ab
z
Sensor readings were taken either at the leaf tip, blade not including the midrib, or toward the base of the leaf not including the
midrib.
y
Means within a sensor followed by same letter are not signicantly different by LSD.
JOURNAL OF PLANT NUTRITION 1569
including the midrib and were signicantly different from leaf tip and base readings (Table 5). SPAD
readings were greater in the 250 mg L
¡1
fertilizer treatment and were signicantly different than those
in the 150 mg L
¡1
treatment (Table 5).
Leaf N, fertilizer treatment, sampling method, and sampling date
Leaf N was affected by treatment of fertilizer, leaf N sampling method, and sampling date
(Table 6). Leaf N was greater in plants treated with 150 mg L
¡1
of fertilizer than in plants
treated with 250 mg L
¡1
of fertilizer. Among different sampling methods of leaf N, leaf N was
greatest with samples collected from the leaf tip and leaf blade, but did not differ from samples
collected from a single plant with petioles, three plants with no petioles, or three plants with
petioles. For different sampling dates, leaf N was greatest if samples were collected 74 DAP and
was different from all other sampling dates (Table 6). Lowest leaf N was in leaves collected 46
DAP.
Correlation (r) for sampling methods and sensors at different leaf locations
For treatment of 150 mg L
¡1
of fertilizer, N concentration of leaves from ve plants using only the leaf
base without petioles was correlated with SPAD readings from the leaf tip (0.915) and leaf blade
Table 3. Effects of two Jacks fertilizer (20N-4.37P-16.6K) rates and number of leaves sampled for atLEAF optical sensor using poinset-
tia Prestige Red.
No. of leaves
z
atLEAF (unitless) atLEAF (unitless)
150 mg L
¡1
250 mg L
¡1
1 52.7b
y
54.8a
3 53.4ab 53.7bc
5 53.0b 54.2ab
z
Sensor readings were taken from one, three, or ve mature leaves from the middle to upper level of the plant.
y
Means within a column followed by same letter are not signicantly different by LSD.
Table 4. CCM-300 sensor values among two Jacks fertilizer (20N-4.37P-16.6K) rates over six weekly sampling days after planting (DAP)
using poinsettia Prestige Red.
Relative chlorophyll content (mg m
¡2
)-
Fertilizer rate 46 DAP 53 DAP 60 DAP 67 DAP 74 DAP 81 DAP
150 (mg L
¡1
) 434.9g
z
322.3h 558.6cde 554.0e 574.3bcd 593.8a
250 (mg L
¡1
) 467.3f 332.4h 556.9de 556.4de 576.2abc 588.5ab
z
Means within a row followed by same letter are not signicantly different by LSD.
Table 5. Main effects of leaf sampling location for CCM-300 sensor given as relative chlorophyll content and two Jacks fertilizer (20N-
4.37P-16.6K) rates for SPAD using poinsettia Prestige Red.
Leaf location and fertilizer rate Sensor value
(mg m
¡2
)
Leaf tip
z
505.3b
y
Leaf blade
z
514.8a
Leaf base
z
508.8b
SPAD
150 (mg L
¡1
) 49.2b
y
250 (mg L
¡1
) 50.7a
z
Sensor readings were taken either at the leaf tip, from the middle of the leaf not including the midrib, or toward the base of the leaf
not including the midrib.
y
Means within a column followed by same letter are not signicantly different by LSD.
1570 B. L. DUNN ET AL.
(0.954), while atLEAF readings from the leaf tip (0.874) and leaf base (0.874) were correlated (Table 7).
No correlation of any sampling method was found with CCM at any leaf location. For treatment of
250 mg L
¡1
of fertilizer, N concentration of leaves without petioles from a single plant was correlated
with atLEAF reading from the leaf blade with petioles and atLEAF readings from the leaf tip (Table 7).
N concentration of leaves from ve plants using only the leaf blade was correlated with atLEAF read-
ings from the leaf tip and blade (Table 7). All three sensors were correlated with each other for all sam-
pling locations for either fertilizer treatments. In fertilizer treatment of 150 mg L
¡1
,rvalue ranged
from 0.564 to 0.997, whereas for fertilizer treatment of 250 mg L
¡1
,rvalue ranged from 0.570 to 0.998
(Table 8).
Table 6. Main effects of Jacks fertilizer (20N-4.37P-16.6K), leaf nitrogen sampling method, and sampling date on poinsettia Prestige
Red.
Fertilizer rate (mg L
¡1
)

z
Leaf N Leaf N sampling method

y
Leaf N Days after planting

Leaf N
150 6.5a
x
Leaf tip from ve plants 6.7a 46 6.1d
250 6.3b Leaf blade from ve plants 6.7a 53 6.3bc
Leaf base no petiole from ve plants 6.2c 60 6.4bc
Leaf base with petiole from ve plants 5.9d 67 6.1cd
Single plant no petiole 6.4bc 74 7.0a
Single plant with petiole 6.4abc 81 6.5b
Three plants no petiole 6.5abc
Three plants with petiole 6.4abc
z
Main effects signicant at p0.001 (

).
y
Sampling method consisted of collecting either ten fully developed leaves with petioles from a single plant per treatment, ten fully
developed leaves without petioles from a single plant per treatment, ten leaves with petioles from three different plants per treat-
ment and bulked, ten leaves without petioles from three different plants per treatment and bulked, ten leaves from ve different
plants per treatment and bulked using only the leaf tip (top »1.5 cm), ten leaves from ve different plants per treatments using only
the leaf blade (middle »2.02.5 cm), ten leaves from ve different plants per treatments using only the leaf base with petioles (bot-
tom »2.0 cm), and ten leaves from ve different plants per treatments using only the leaf base without petioles (bottom »2.0 cm) for
total leaf N per sampling treatment weekly.
x
Means (nD10) within a column followed by the same letter are not signicantly different by LSD.
Table 7. Pearson correlation (r) matrix for measured sensor parameters and leaf nitrogen sampling methods for poinsettia Prestige
Redacross six sampling dates. (nD6).
150 mg L
¡1
20-10-20 Jacks fertilizer
Leaf nitrogen
sampling methods
SPAD
tip
z
SPAD
blade
SPAD
base
atLEAF
tip
z
atLEAF
blade
z
atLEAF
base
z
CCM
tip
CCM
blade
CCM
base
Single plant no petioles 0.550
y
0.653 0.447 0.746 0.596 0.723 0.513 0.514 0.504
Single plant with petioles 0.456 0.578 0.182 0.531 0.343 0.493 0.069 0.128 0.142
Three plants no petioles 0.777 0.810 0.546 0.730 0.556 0.711 0.279 0.351 0.374
Three plants with petioles 0.617 0.630 0.396 0.606 0.121 0.646 0.571 0.633 0.668
Leaf tip from ve plants 0.544 0.616 0.242 0.555 0.199 0.551 0.238 0.316 0.344
Leaf blade from ve plants 0.730 0.781 0.428 0.667 0.341 0.662 0.256 0.346 0.385
Leaf base no petioles from ve plants 0.915
0.954

0.704 0.872
0.571 0.874
0.514 0.581 0.618
Leaf base with petioles from ve plants 0.159 0.289 0.176 0.370 0.078 0.389 0.518 0.480 0.491
250 mg L
¡1
20-10-20 Jacks fertilizer
Single plant no petioles 0.125 0.633 0.418 0.742 0.895
0.792 0.578 0.570 0.525
Single plant with petioles 0.672 0.757 0.574 0.841
0.702 0.646 0.649 0.645 0.654
Three plants no petioles ¡0.229 0.326 ¡0.038 0.515 0.690 0.403 0.180 0.153 0.105
Three plants with petioles ¡0.210 0.267 ¡0.195 0.402 0.550 0.120 ¡0.138 ¡0.180 ¡0.213
Leaf tip from ve plants 0.018 0.517 0.111 0.683 0.785 0.521 0.331 0.301 0.266
Leaf blade from ve plants 0.320 0.801 0.288 0.841
0.864
0.806 0.688 0.648 0.625
Leaf base no petioles from ve plants 0.019 0.541 0.059 0.651 0.727 0.630 0.514 0.477 0.441
Leaf base with petioles from ve plants 0.239 0.236 ¡0.007 0.340 0.227 ¡0.004 ¡0.054 ¡0.074 ¡0.056
z
Sensor readings taken from the leaf tip, leaf blade excluding the midrib, and leaf base.
y
Pearson correlation (r) signicant at p0.05 (
), p0.01 (

), or p0.001 (

).
JOURNAL OF PLANT NUTRITION 1571
Discussion
In general, SPAD and atLEAF readings increased with time of plant growth. Basyouni, Dunn, and
Goad (2015), using two cultivars of poinsettias, also noted that sensor readings increased over time,
meaning that chlorophyll or N concentrations increased with stage of growth of the crop. Khoddamza-
deh and Dunn (2016) reported an increase in SPAD and atLEAF readings over time in chrysanthemum
(Chrysanthemum sp. L.), and Swiader and Moore (2002) reported that SPAD readings increased with
sampling dates for pumpkins (Cucurbita pepo L.). Ghosh (1973) and Neilsen et al. (1995) reported that
with increase in age of apple (Malus sp. Mill.) leaves within a growing season, SPAD readings increased
and was not due to an increase in N content but may have been due to an increase in leaf thickness
(Wooge and Barden 1987; Campbell et al. 1990). Results of Minotti, Halseth, and Sieczka (1994) con-
tradicted our ndings as a decrease in SPAD readings was reported as potato plants aged.
Chapman and Barreto (1997) reported that at least four leaves per plot are needed, with several
observations per leaf for sensor-based N estimation. Perry and Davenport (2007) also reported that
single-leaf measurement using a chlorophyll meter was not an accurate method for N estimation.
CCM showed greater readings at 81 DAP in fertilizer treatment of 150 mg L
¡1
, while in fertilizer treat-
ment of 250 mg L
¡1
greater readings were at 74 and 81 DAP (Table 4). In both fertilizer treatments,
CCM readings were greatest at the maximum number of DAP, which may be due to effect of different
growth stage on chlorophyll or N accumulation. Ziadi et al. (2010) reported that chlorophyll meter
reading were affected by growth stages, and elongation stage was the best stage for estimating nutri-
tional status in wheat. Some other studies reported correlation of CCM with leaf N concentration
across sampling dates (Cate and Perkins 2003; Ghasemi et al., 2014), but our results showed that CCM
was not correlated with leaf N with any sampling method at all leaf sampling locations.
Dunn and Goad (2015) reported that SPAD readings were affected by leaf sampling location and
were greatest if the leaf tip or middle of leaf was sampled in ornamental cabbage (Brassica oleracea L.).
Yuan et al. (2016) also reported two-third position on the fourth fully expanded leaf of rice (Oryza sat-
iva L.) as the best position for sensor-based estimation of leaf N. Chapman and Barreto (1997) recom-
mended an area lying between about 40% and 70% from the leaf base to the tip for sensor-based N
estimation in maize (Zea mays L.). This result is similar to our results as CCM also was affected by the
Table 8. Pearson correlation (r) matrix for measured sensor parameters for poinsettia Prestige Redacross six sampling dates and two
different Jacks fertilizer (20N-10P-20K) rates. (nD18).
150 mg L
¡1
20-10-20 Jacks fertilizer
SPAD tip
z
SPAD blade SPAD base atLEAF tip
z
atLEAF blade
z
atLEAF base
z
CCM tip CCM blade CCM base
SPAD tip 0.908

y
0.883

0.870

0.800

0.878

0.783

0.792

0.774

SPAD blade 0.876

0.931

0.842

0.946

0.658
0.666
0.665
SPAD base 0.844

0.849

0.892

0.802

0.801

0.785

atLEAF tip 0.905

0.961

0.661

0.661

0.658

atLEAF blade 0.920

0.599

0.590
0.564
atLEAF base 0.669

0.680

0.671

CCM tip 0.997

0.992

CCM blade 0.792

250 mg L
¡1
20-10-20 Jacks fertilizer
SPAD tip 0.892

0.914

0.884

0.778

0.803

0.736

0.744

0.757

SPAD blade 0.831

0.873

0.860

0.794

0.577
0.581
0.591

SPAD base 0.846

0.804

0.810

0.687

0.707

0.724

atLEAF tip 0.915

0.940

0.718

0.733

0.730

atLEAF blade 0.894

0.570
0.579
0.580
atLEAF base 0.763

0.781

0.781

CCM tip 0.998

0.994

CCM blade 0.998

z
Sensor readings taken from the leaf tip, leaf blade excluding the midrib, and leaf base.
y
Pearson correlation (r) signicant at p0.05. Not signicant (NS), p0.05 (
), p0.01 (

), or p0.001 (

).
1572 B. L. DUNN ET AL.
leaf sampling location and showed greatest readings when the leaf blade was sampled. Dunn et al.
(2018) also reported that SPAD readings were affected by phosphorus and potassium concentration
present in the fertilizer. Loh et al. (2002) also reported differences in SPAD readings due to the effect
of nutrients other than N. Results of Loh et al. (2002) supported our results as SPAD readings were
greater for fertilizer treatment of 250 mg L
¡1
, while leaf N was higher in fertilizer treatment of 150 mg
L
¡1
. These results mean SPAD readings were also affected by fertilizer concentrations.
Khoddamzadeh and Dunn (2016) reported that leaf N concentration for two cultivars of chrysan-
themum were greatest at 38 days after treatment (DAT), which corresponds to our results that leaf N
concentration was highest at 74 DAP (35 DAT). It was also reported that leaf N concentration
increased with increasing fertilizer rate, which was in contrast to our results as leaf N was greatest in
the lowest fertilizer rate of 150 mg L
¡1
. Richardson and Hardgrave (1992) noted that higher rates of
fertilizer also produce more rapid growth in plants and as a result have lower plant N levels.
Perry and Davenport (2007) suggested that an individual leaf measurement was not an accurate
method for N estimation in apple. This result corresponds to our results as SPAD and atLEAF readings
at different leaf locations were correlated with leaf N if leaves were collected from ve different plants
rather than from one plant. Leaf N was also greater if leaf N was measured in the leaf tip or leaf blade
of ten leaves from ve different plants, whereas leaf N was signicantly lower when samples were col-
lected from ve different plants with petiole and without petiole and samples collected from a single
plant without petiole. Our results contradict Ecke et al. (2004) as SPAD and atLEAF readings were cor-
related with leaf samples not consisting of a petiole, though the recommendation is to send a leaf sam-
ple with petioles for foliar analysis for poinsettias. Leaf collections with or without petioles for leaf N
concentration varies, as Wang et al. (2004) detached leaves from petioles for leaf analysis in peace lily
(Spathiphyllum wallisii Regel).
Basyouni, Dunn, and Goad (2015) reported correlation of SPAD, atLEAF, and NDVI with each
other for two poinsettia cultivars Prestige Redand Freedom Red.Their results support our results
that SPAD, atLEAF, and CCM readings were correlated with each other for every sampling location on
a leaf and for both fertilizer treatments. In contrast, Khoddamzadeh and Dunn (2016) reported no cor-
relation of atLEAF with SPAD, NDVI, and leaf N for two cultivars of chrysanthemum. Zhu, Tremblay,
and Liang (2012) also reported correlation between SPAD and atLEAF for ve different agronomic
crops grown in different environments.
Conclusion
Based on this study, different leaf sampling locations and sampling dates affected sensor readings in the
estimation of chlorophyll or N in leaves. Sensor readings increased with increasing plant age and corre-
sponded to an increase in N content over time. Readings were greatest if leaf N was sampled from the
leaf blade. SPAD was affected by different fertilizer treatments and was greater in 250 mg L
¡1
fertilizer
rate. SPAD, atLEAF, and CCM were correlated with each other for different leaf locations. CCM was
not correlated with leaf N for any sampling method, and thus cannot be recommended for leaf N esti-
mation of poinsettia Prestige Red.Leaf N was best correlated with SPAD sensor reading from the
leaf blade if N was sampled using the leaf base of ve leaves without petioles. As supported by other
studies (Barreto 1997), the middle of leaf can be recommended as the best place for leaf N estimation.
However, it is important to consider that sensor-based N estimation also is affected by some environ-
mental conditions like light, temperature, as well as leaf thickness, leaf location, cultivar, plant age, and
nutrients other than N (Xiong et al. 2015; Minotta and Pinzauti 1996). Future research should look to
develop crop and cultivar specic linear models for different chlorophyll meters, which should consider
factors affecting sensor readings to minimize error in estimating N on basis of chlorophyll meters.
Funding
This work was supported by the USDA National Institute of Food and Agriculture, Hatch project and the Division of
Agricultural Sciences and Natural Resources at Oklahoma State University.
JOURNAL OF PLANT NUTRITION 1573
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JOURNAL OF PLANT NUTRITION 1575
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In many cases evaluation of chlorophyll and nitrogen content in plants need to destructive methods, more time and organic solvents. Application of chlorophyll meters save time and resources. The aim of this study was estimating of chlorophyll and nitrogen content in Asian pear leaves using non-destructive method and rapid quantification of chlorophyll by chlorophyll content meter (CCM-200). This study was conducted on 8 years old Asian pear trees during June 2008 in Tehran, Iran. To develop our regression model, the chlorophyll meter data were correlated with extracted chlorophyll and nitrogen content data obtained from DMSO and Kejeldal methods, respectively. The results showed that, there was positive and linear correlation between CCM-200 data and chlorophyll a (R=0.7183), chlorophyll b (R=0.8523), total chlorophyll (R=0.90), and total nitrogen content (R=0.76) in Asian pear leaves. Thus, it can be concluded that, CCM-200 can be used in order to predict both chlorophyll and nitrogen content in Asian pear leaves.
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Nitrogen (N) is an important component of proteins and chlorophyll, and has been correlated with optical sensors as a means to determine N status during crop production. In this experiment, chrysanthemum ‘Amico Bronze’ and ‘Jacqueline Yellow’ had initial controlled-release fertilizer rates of 0, 5, 10, 15, or 20 g. Normalized Difference Vegetation Index (NDVI), Soil Plant Analytical Development (SPAD), and atLEAF sensor readings were taken at 10, 17, 24, 31, 38, and 45 days after adding initial fertilizer treatments (DAT). NDVI was correlated with leaf N concentration at all sampling dates except 17 DAT. Values for NDVI increased linearly up to 31 DAT for all treatments then plateaued at 45 DAT. Values for SPAD were only correlated with leaf N at 24 DAT, whereas, NDVI was correlated as early as 10 DAT. The atLEAF sensor was not correlated with leaf N at any sampling date. With weeks combined, correlation analysis showed correlations among leaf N and fertilizer rates, fertilizer rates and SPAD, and SPAD with NDVI and atLEAF. Thirty-one days after initial fertilizer treatment, 10 pots per treatment per cultivar were supplemented as following: 15 g supplemented to the 0 g treatment, 10 g to the 5 g treatment, and 5 g to the 10 g treatment at 31 DAT. With supplemented fertilizer treatments (SFTs), NDVI increased weekly until 45 DAT for ‘Amico Bronze’, while SPAD values did not increase in any treatments. The greatest atLEAF values occurred with 10 (+5) g and 0 (+15) g N in both cultivars. All sensor readings were only taken on leaves without any flowers. The greatest number of flowers, plant height, and shoot dry weight occurred with 10 (+5) g of additional N, but no differences occurred between 5 (+10) g and 0 (+15) g for height and shoot dry weight. No correlations existed between fertilizer rates, SPAD, NDVI, and leaf N for SFT in either cultivar. In summary, results indicated that NDVI values correlated greater (P ≤ 0.05 and P ≤ 0.01) with leaf N than SPAD and atLEAF chlorophyll sensors. Supplemental fertilizer application improved plant quality in terms of number of flowers, plant height, and shoot dry weight for all treatments, indicating that SFT could be used to correct N deficiency during crop production; however, not in combination with nondestructive sensor readings because of inconsistencies in the ability of all three sensors to separate among fertilizer treatments during a short production schedule. © 2016 American Society for Horticultural Science. All rights reserved.
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Optical sensors are a fast and nondestructive new technology used to estimate plant chlorophyll content by measuring leaf reflectance or absorbance of light. The objective of this study was to evaluate the reliability of normalized difference vegetative index (NDVI) values calculated by the GreenSeeker™ hand held sensor as an indirect indicator of dianthus (Dianthus chinensis L.) N status, and investigate nutrient supplementation on deficient ‘Telstar™ White’ and ‘Telstar™ Red Picotee’ plants. Pots were supplemented with 0, 5, 10, 15, and 20 g of 15N-3.9P-10K controlled release fertilizer (CRF). Soil and plant analysis development (SPAD) chlorophyll meter, GreenSeeker™ NDVI sensor, and atLEAF meter readings were recorded for four consecutive weeks. At 49 d after planting (DAP), the 0 and 5 g treatments were found deficient and half of the pots were supplemented with extra fertilizer for treatment correction (C 0 and C 5, respectively). The SPAD and atLEAF readings showed stronger correlation to actual leaf N concentration compared with the GreenSeeker™. The GreenSeeker™ readings were less correlated with leaf N concentration at early stages of establishment due to the plants’ small size and background noise, as well as at later stages of establishment due to anthesis. Dianthus quality responses generally increased as fertilizer rates increased. The additional correction treatment showed a significant improvement in C 5 and no significant improvement on C 0, indicating that the correction treatment was beneficial for dianthus when initial amount of fertilizer was applied.
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The Soil Plant Analysis Development (SPAD) chlorophyll meter is one of the most commonly used diagnostic tools to measure crop nitrogen status. However, the measurement method of the meter could significantly affect the accuracy of the final estimation. Thus, this research was undertaken to develop a new methodology to optimize SPAD meter measurements in rice (Oryza sativa L.). A flatbed color scanner was used to map the dynamic chlorophyll distribution and irregular leaf shapes. Calculus algorithm was adopted to estimate the potential positions for SPAD meter measurement along the leaf blade. Data generated by the flatbed color scanner and SPAD meter were analysed simultaneously. The results suggested that a position 2/3 of the distance from the leaf base to the apex (2/3 position) could represent the chlorophyll content of the entire leaf blade, as indicated by the relatively low variance of measurements at that positon. SPAD values based on di-positional leaves and the extracted chlorophyll a and b contents were compared. This comparison showed that the 2/3 position on the lower leaves tended to be more sensitive to changes in chlorophyll content. Finally, the 2/3 position and average SPAD values of the fourth fully expanded leaf from the top were compared with leaf nitrogen concentration. The results showed the 2/3 position on that leaf was most suitable for predicting the nitrogen status of rice. Based on these results, we recommend making SPAD measurements at the 2/3 position on the fourth fully expanded leaf from the top. The coupling of dynamic chlorophyll distribution and irregular leaf shapes information can provide a promising approach for the calibration of SPAD meter measurement, which can further benefit the in situ nitrogen management by providing reliable estimation of crops nitrogen nutrition status.
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Chlorophyll meters are widely used to guide nitrogen (N) management by monitoring leaf N status in agricultural systems, but the effects of environmental factors and leaf characteristics on leaf N estimations are still unclear. In the present study, we estimated the relationships among SPAD readings, chlorophyll content and leaf N content per leaf area for seven species grown in multiple environments. There were similar relationships between SPAD readings and chlorophyll content per leaf area for the species groups, but the relationship between chlorophyll content and leaf N content per leaf area, and the relationship between SPAD readings and leaf N content per leaf area varied widely among the species groups. A significant impact of light-dependent chloroplast movement on SPAD readings was observed under low leaf N supplementation in both rice and soybean but not under high N supplementation. Furthermore, the allocation of leaf N to chlorophyll was strongly influenced by short-term changes in growth light. We demonstrate that the relationship between SPAD readings and leaf N content per leaf area is profoundly affected by environmental factors and leaf features of crop species, which should be accounted for when using a chlorophyll meter to guide N management in agricultural systems.
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Greenhouse production of geraniums is popular for sales in the spring, and monitoring plant nutrition is important for high quality plants. The objective of this study was to evaluate if nondestructive handheld sensors could be used to quantify nitrogen (N) status in Pelargonium × hortorum 'Maverick Red' using controlled release fertilizer (CRF). Fertilizer treatments of 0, 4, 8, 10, or 12 g of 16N-9P-12K were topdressed on greenhouse grown plants. Individual plants were scanned from 10 pots per treatment for Normalized Difference Vegetative Index (NDVI) and Soil-Plant Analyses Development (SPAD) over eight different sampling dates starting 7 days after fertilizer treatment application (DAT). Height, width, number of flowers, number of umbels and leaf N concentration were also recorded. Linear and quadratic trends were seen for both NDVI and SPAD. Plant height and width was highest in the 12 g treatment, but was not different than the 8 g or 10 g treatments. Number of flowers was highest in the 10 g treatment, but was not different from the 8 g and 12 g treatments. Number of umbels was not significantly different among fertilizer treatments, but all were greater than the control. For all measurement dates, a correlation was seen for fertilizer rate and leaf N concentration. Neither sensor showed correlations with leaf N concentration at 7 DAT or 14 DAT; however, both were correlated with each other and leaf N concentration starting 28 DAT. Results from this study indicated that 8 g CRF produced the best quality plants. Both NDVI and SPAD can be used to predict N status in potted geraniums grown with CRF, but consistency in sample collection and sampling time may be necessary to correlate the values with N status.
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Greenhouse production of Gaillardia is becoming increasingly popular for potted production due to growing interests in drought tolerant plant material. The objective of this study was to see if nondestructive handheld sensors could be used to monitor nitrogen (N) status in Gaillardia aristata 'Arizona Apricot'. Topdressed fertilizer treatments of 0, 4, 8, 10, or 12 g of controlled release fertilizer (CRF) 16N-3.9P-10K were added to greenhouse grown plants. Individual plants were scanned from 10 pots per treatment for Normalized Dijference Vegetative Index (NDVI) and Soil-Plant Analyses Development (SPAD) over eight dijferent sampling dates starting 7 days after fertilizer treatment application (DAT). Height, width, leaf N concentration, and number of panicles were also recorded. Linear, cubic, and quadratic trends were seen for NDVI and SPAD. Plant height was greatest in the 10 g treatment, but was not dijferent than any other treatment. Plant width was greatest in the 12 g treatment, but was not dijferent from the 4 g and 10 g treatments. Number of panicles was highest in the 12 g treatment, but was not dijferent from the 10 g fertilizer treatment. Neither sensor showed correlations with leaf N concentration 7 DAT; however, the NDVI sensor showed the earliest correlation with leaf N concentration starting 14 DAT. Both sensors were correlated with each other at 35, 42, and 56 DAT. Results from this study indicate that 10 g CRF was sujficient for plant growth and flowering. Both sensors can be used to predict N status in potted Gaillardia; however, consistency in sample collection and sampling time may be necessary to correlate values with N status.
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Studies were made of morphological and physiological characteristics of leaves developed on two different types of fruiting shoot of apple, namely long terminal extensions and spurs borne on 5–7-year-old spur systems. Leaves of the long shoots had more highly developed palisade parenchyma, better light absorbing capacity and higher rates of photosynthesis than the spur leaves. The chlorophyll content of the leaves was apparently correlated with leaf thickness, and the time of maximum accumulation of chlorophyll coincided with the time when fruit buds differentiated at the shoot apices. The presence of fruits stimulated photosynthetic activity of the leaves.
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We report three N rate experiments conducted on a gravelly loam soil to assess the N status of potato ( Solanum tuberosum L.) using a Minolta SPAD-502 chlorophyll meter. Highly significant linear and quadratic trends were obtained for the regression of N rate on marketable tuber yields and SPAD readings. SPAD readings were taken at four times during the growing season and decreased as plants aged. Based on regression analysis, the early season SPAD readings, associated with N rates giving maximum marketable tuber yields, ranged from 49 to 56 units depending on year, variety, and location. Potato variety significantly affected SPAD values in eight of the 12 situations where readings were obtained. Precision in interpretation was improved when the highest N rates were considered “reference strips” to standardize the SPAD readings across varieties and growing seasons. Our results suggest that field SPAD readings can readily identify severe N deficiency in potatoes, have the potential to identify situations where supplementary sidedressed N would not be necessary, but would be of limited value for identifying situations of marginal N deficiency unless reference strips are used.