scholarly journals Field Assessment of Macronutrients and Nitrogen in Apple Leaves Using a Chlorophyll Meter

2019 ◽  
Vol 29 (3) ◽  
pp. 300-307 ◽  
Author(s):  
Youngsuk Lee ◽  
Hun Joong Kweon ◽  
Moo-Yong Park ◽  
Dongyong Lee
Keyword(s):  
Nutrient Status ◽  
Nutrient Content ◽  
N Content ◽  
Chlorophyll Meter ◽  
Content Assessment ◽  
Growing Period ◽  
Leaf Chlorophyll ◽  
Nutrient Profiles ◽  
Leaf N Content ◽  
Leaf N

Nutrient content assessment of plant tissues is widely performed by farmers to determine the appropriate amount of fertilization to use for their crops. A nondestructive leaf chlorophyll meter is one of the most commonly used devices for performing field assessments of the nutrient status of leaves. However, it is challenging to use a chlorophyll meter to assess the nutritional status of perennial plants, such as the apple (Malus ×domestica) tree, because of the difficulty estimating nitrogen (N) during the entire growing period. We compared the chlorophyll meter readings with leaf nutrient profiles collected from young ‘Arisoo’/M.9 apple trees throughout the growing period. A significant positive correlation between the chlorophyll meter readings and leaf N content was found from May to August during the midseason. Regression analysis indicated that the best sampling time for predicting the foliar N content of apple tress is from late June to late July. This result suggests that a reliable leaf N assessment can be performed in a rapid, nondestructive way in apple orchards.

scholarly journals Effect of Cultivar on Chlorophyll Meter and Canopy Reflectance Measurements in Cucumber

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 509 ◽  
Author(s):  
Romina de Souza ◽  
Rafael Grasso ◽  
M. Teresa Peña-Fleitas ◽  
Marisa Gallardo ◽  
Rodney B. Thompson ◽  
...  
Keyword(s):  
Optical Sensors ◽  
Optical Sensor ◽  
Chlorophyll Concentration ◽  
Vegetation Indices ◽  
Canopy Reflectance ◽  
Cucumis Sativus L ◽  
N Content ◽  
Chlorophyll Meter ◽  
Leaf N Content ◽  
Leaf N

Optical sensors can be used to assess crop N status to assist with N fertilizer management. Differences between cultivars may affect optical sensor measurement. Cultivar effects on measurements made with the SPAD-502 (Soil Plant Analysis Development) meter and the MC-100 (Chlorophyll Concentration Meter), and of several vegetation indices measured with the Crop Circle ACS470 canopy reflectance sensor, were assessed. A cucumber (Cucumis sativus L.) crop was grown in a greenhouse, with three cultivars. Each cultivar received three N treatments, of increasing N concentration, being deficient (N1), sufficient (N2) and excessive (N3). There were significant differences between cultivars in the measurements made with both chlorophyll meters, particularly when N supply was sufficient and excessive (N2 and N3 treatments, respectively). There were no consistent differences between cultivars in vegetation indices. Optical sensor measurements were strongly linearly related to leaf N content in each of the three cultivars. The lack of a consistent effect of cultivar on the relationship with leaf N content suggests that a unique equation to estimate leaf N content from vegetation indices can be applied to all three cultivars. Results of chlorophyll meter measurements suggest that care should be taken when using sufficiency values, determined for a particular cultivar

scholarly journals Use of an Active Canopy Sensor and SPAD Chlorophyll Meter to Quantify Geranium Nitrogen Status

HortScience ◽  
2012 ◽  
Vol 47 (1) ◽  
pp. 45-50 ◽  
Author(s):  
Yun-wen Wang ◽  
Bruce L. Dunn ◽  
Daryl B. Arnall ◽  
Pei-sheng Mao
Keyword(s):  
Green Leaf ◽  
Fertilizer Treatment ◽  
N Content ◽  
Chlorophyll Meter ◽  
N Concentration ◽  
Flower Traits ◽  
Leaf N Content ◽  
N Rates ◽  
N Status ◽  
Leaf N

This research was conducted to investigate the potentials of normalized difference vegetation index (NDVI), a Soil-Plant Analyses Development (SPAD) chlorophyll meter, and leaf nitrogen (N) concentration [% dry matter (DM)] for rapid determination of N status in potted geraniums (Pelargonium ×hortorum). Two F1 cultivars were chosen to represent a dark-green leaf cultivar, Horizon Deep Red, and a light-green leaf cultivar, Horizon Tangerine, and were grown in a soilless culture system. All standard 6-inch (15.24-cm) pots filled with a medium received an initial top-dress application of 5 g controlled-release fertilizer (15N–9P–12K), then plants were supplemented with additional N in the form of urea at 0, 50, 100, or 200 mg·L−1 N every few days to produce plants ranging from N-deficient to N-sufficient. The NDVI readings of individual plants from a NDVI pocket sensor developed by Oklahoma State University were collected weekly until the flowering stage. Data on flower traits, including number of pedicels (NOP), number of full umbels per pot (NOFU), total number of flowers per pot (TNF), number of flowers per pedicel (NOF), and inflorescences diameter (IFD), were collected 3 months after initial fertilizer treatment. After measuring flower traits, pedicels were removed from each pot, and SPAD value, NDVI, and leaf N concentration (g·kg−1 DM) were measured simultaneously. Cultivar and N rate significantly affected all but two flower and one N status parameters studied. The coefficient of determination R2 showed that NOP, NOFU, and TNF traits were more related to the N rates and the status parameters studied for ‘Horizon Tangerine’ than for ‘Horizon Deep Red’. For the latter cultivar, NOP and TNF traits were highly related to NDVI and SPAD values than N rates and leaf N content parameters. Correlation analysis indicated that the NDVI readings (R2 = 0.848 and 0.917) and SPAD values (R2 = 0.861 and 0.950) were significantly related to leaf N content (g·kg−1 DM) between cultivars. However, sensitivity of the NDVI and chlorophyll values to N application rate in geranium was slightly less than leaf N content. Strong correlations (R2 = 0.974 and 0.979, respectively) between NDVI and SPAD values were found within cultivars. The results demonstrated NDVI and SPAD values can be used to estimate N status in geranium. Because the pocket NDVI sensor will be cheaper than the SPAD unit, it has an advantage in determining N content in potted ornamentals.

scholarly journals A novel approach for nitrogen diagnosis of wheat canopies digital images by mobile phones based on histogram

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xin Qi ◽  
Yanan Zhao ◽  
Yufang Huang ◽  
Yang Wang ◽  
Wei Qin ◽  
...  
Keyword(s):  
Neural Network ◽  
Mobile Phones ◽  
Mean Value ◽  
Wheat Cultivars ◽  
N Content ◽  
Color Parameters ◽  
The Neural Network ◽  
The Mean ◽  
Leaf N Content ◽  
Leaf N

AbstractThe accurate and nondestructive assessment of leaf nitrogen (N) is very important for N management in winter wheat fields. Mobile phones are now being used as an additional N diagnostic tool. To overcome the drawbacks of traditional digital camera diagnostic methods, a histogram-based method was proposed and compared with the traditional methods. Here, the field N level of six different wheat cultivars was assessed to obtain canopy images, leaf N content, and yield. The stability and accuracy of the index histogram and index mean value of the canopy images in different wheat cultivars were compared based on their correlation with leaf N and yield, following which the best diagnosis and prediction model was selected using the neural network model. The results showed that N application significantly affected the leaf N content and yield of wheat, as well as the hue of the canopy images and plant coverage. Compared with the mean value of the canopy image color parameters, the histogram could reflect both the crop coverage and the overall color information. The histogram thus had a high linear correlation with leaf N content and yield and a relatively stable correlation across different growth stages. Peak b of the histogram changed with the increase in leaf N content during the reviving stage of wheat. The histogram of the canopy image color parameters had a good correlation with leaf N content and yield. Through the neural network training and estimation model, the root mean square error (RMSE) and the mean absolute percentage error (MAPE) of the estimated and measured values of leaf N content and yield were smaller for the index histogram (0.465, 9.65%, and 465.12, 5.5% respectively) than the index mean value of the canopy images (0.526, 12.53% and 593.52, 7.83% respectively), suggesting a good fit for the index histogram image color and robustness in estimating N content and yield. Hence, the use of the histogram model with a smartphone has great potential application in N diagnosis and prediction for wheat and other cereal crops.

scholarly journals Effects of ontogenetic stage and leaf age on leaf functional traits and the relationships between traits in Pinus koraiensis

2021 ◽  
Author(s):  
Meng Ji ◽  
Guangze Jin ◽  
Zhili Liu
Keyword(s):  
Significant Positive Correlation ◽  
Leaf Age ◽  
Leaf Traits ◽  
Ontogenetic Stage ◽  
Pinus Koraiensis ◽  
Mature Trees ◽  
N Content ◽  
Ontogenetic Stages ◽  
Leaf N Content ◽  
Leaf N

AbstractInvestigating the effects of ontogenetic stage and leaf age on leaf traits is important for understanding the utilization and distribution of resources in the process of plant growth. However, few studies have been conducted to show how traits and trait-trait relationships change across a range of ontogenetic stage and leaf age for evergreen coniferous species. We divided 67 Pinus koraiensis Sieb. et Zucc. of various sizes (0.3–100 cm diameter at breast height, DBH) into four ontogenetic stages, i.e., young trees, middle-aged trees, mature trees and over-mature trees, and measured the leaf mass per area (LMA), leaf dry matter content (LDMC), and mass-based leaf nitrogen content (N) and phosphorus content (P) of each leaf age group for each sampled tree. One-way analysis of variance (ANOVA) was used to describe the variation in leaf traits by ontogenetic stage and leaf age. The standardized major axis method was used to explore the effects of ontogenetic stage and leaf age on trait-trait relationships. We found that LMA and LDMC increased significantly and N and P decreased significantly with increases in the ontogenetic stage and leaf age. Most trait-trait relationships were consistent with the leaf economic spectrum (LES) at a global scale. Among them, leaf N content and LDMC showed a significant negative correlation, leaf N and P contents showed a significant positive correlation, and the absolute value of the slopes of the trait-trait relationships showed a gradually increasing trend with an increasing ontogenetic stage. LMA and LDMC showed a significant positive correlation, and the slopes of the trait-trait relationships showed a gradually decreasing trend with leaf age. Additionally, there were no significant relationships between leaf N content and LMA in most groups, which is contrary to the expectation of the LES. Overall, in the early ontogenetic stages and leaf ages, the leaf traits tend to be related to a "low investment-quick returns" resource strategy. In contrast, in the late ontogenetic stages and leaf ages, they tend to be related to a "high investment-slow returns" resource strategy. Our results reflect the optimal allocation of resources in Pinus koraiensis according to its functional needs during tree and leaf ontogeny.

scholarly journals Variation of nitric oxide emission potential in plants: a possible link to leaf N content and net photosynthetic activity

2014 ◽  
Vol 8 (3) ◽  
pp. 313-320 ◽  
Author(s):  
Juan Chen ◽  
Chao Wang ◽  
Fei-Hua Wu ◽  
Wen-Hua Wang ◽  
Ting-Wu Liu ◽  
...  
Keyword(s):  
Nitric Oxide ◽  
Photosynthetic Activity ◽  
N Content ◽  
Nitric Oxide Emission ◽  
Leaf N Content ◽  
Leaf N

scholarly journals Dissection of hyperspectral reflectance to estimate nitrogen and chlorophyll contents in tea leaves based on machine learning algorithms

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hiroto Yamashita ◽  
Rei Sonobe ◽  
Yuhei Hirono ◽  
Akio Morita ◽  
Takashi Ikka
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Visible Region ◽  
Machine Learning Algorithms ◽  
Hyperspectral Reflectance ◽  
N Content ◽  
Green Leaves ◽  
Leaf N Content ◽  
N Status ◽  
Leaf N

Abstract Nondestructive techniques for estimating nitrogen (N) status are essential tools for optimizing N fertilization input and reducing the environmental impact of agricultural N management, especially in green tea cultivation, which is notably problematic. Previously, hyperspectral indices for chlorophyll (Chl) estimation, namely a green peak and red edge in the visible region, have been identified and used for N estimation because leaf N content closely related to Chl content in green leaves. Herein, datasets of N and Chl contents, and visible and near-infrared hyperspectral reflectance, derived from green leaves under various N nutrient conditions and albino yellow leaves were obtained. A regression model was then constructed using several machine learning algorithms and preprocessing techniques. Machine learning algorithms achieved high-performance models for N and Chl content, ensuring an accuracy threshold of 1.4 or 2.0 based on the ratio of performance to deviation values. Data-based sensitivity analysis through integration of the green and yellow leaves datasets identified clear differences in reflectance to estimate N and Chl contents, especially at 1325–1575 nm, suggesting an N content-specific region. These findings will enable the nondestructive estimation of leaf N content in tea plants and contribute advanced indices for nondestructive tracking of N status in crops.

Variability in physiological responses of Venezuelan cacao to drought

2020 ◽  
Vol 56 (3) ◽  
pp. 407-421 ◽  
Author(s):  
Wilmer Tezara ◽  
Gabriela Pereyra ◽  
Eleinis Ávila-Lovera ◽  
Ana Herrera
Keyword(s):  
Chlorophyll Content ◽  
Water Use ◽  
Isotopic Ratio ◽  
Water Status ◽  
Common Garden ◽  
Photochemical Activity ◽  
Total Soluble Protein ◽  
N Content ◽  
Leaf N Content ◽  
Leaf N

AbstractIn order to assess the response of cocoa trees to drought, changes in water status, gas exchange, leaf carbon isotopic ratio (δ13C), photochemical activity, and leaf N and chlorophyll content during the rainy and dry season were measured in 31 Venezuelan cocoa clones (17 Trinitarios, 6 Criollos, and 8 Modern Criollos) grown in a common garden. Drought caused a 40% decrease in water potential (ψ) in all but the Modern Criollos, and a reduction in net photosynthetic rate (A) and stomatal conductance (gs) without an increase in instantaneous water use efficiency (WUE) in 93% of clones, and an increase in δ13C (long-term WUE) in 74% of clones; these responses suggest differences in tolerance to drought among clones. A positive correlation between A and both gs and leaf N content was found for all genotypes. Leaf N content, chlorophyll content, and photochemical activity were reduced during drought, suggesting that metabolism was also inhibited. The best performance during drought was shown by Modern Criollos with the highest WUE, while five Trinitario clones seemed to be less sensitive to drought, since neither chlorophyll, N, total soluble protein concentration, nor gs changed with drought, indicating that those Trinitario clones, with lower A, have a conservative water use. Modern Criollos showed no reductions in either ψ or gs; A remained unchanged, as did WUE, which was the highest, suggesting that these clones would be more successful in environments with low water availability. Our results indicate large variation in physiological response to drought over a range of parameters, suggesting possible differences in tolerance among clones.

Diffusive limitation to photosynthesis and plant-microbe N competition dominate the urban lawn response to secondary salinization

2020 ◽  
Author(s):  
Dario Liberati ◽  
Ramilla Brykova ◽  
Maria Cristina Moscatelli ◽  
Stefano Moscatello ◽  
Emanuele Pallozzi ◽  
...  
Keyword(s):  
Soil Salinization ◽  
Leaf Mass Per Area ◽  
Salinity Treatment ◽  
Mesophyll Conductance ◽  
N Content ◽  
Secondary Salinization ◽  
Photosynthetic Rates ◽  
Leaf N Content ◽  
The Impact ◽  
Leaf N

<p>Release of de-icing agents is the main cause of increasing soil salinization in urban and rural areas.  Grasses are the dominant vegetation in urban lawns and are exposed to different rates of soil salinization depending on the distance to the paved salt-affected surfaces. The capacity of these ecosystems to maintain C sequestration and nutrient cycling functioning depends on the sensitivity to salinization of the main players: primary producers and their interaction with microbial community.</p><p>In this mesocosm study we aimed to evaluating the impact of soil secondary salinization rates on the functioning of <em>Lolium perenne</em>. Salinization treatments were applied for two months in spring, irrigating the mesocosms with the commonly used de-icing agent NaCl at two concentration, 30 mM (low salinity treatment) and 90 mM (moderate salinity treatment). The leaf physiological  responses of Lolium were assessed monitoring photosynthetic rates (A), stomatal conductance (g<sub>s</sub>)  mesophyll conductance (g<sub>m</sub>), carboxylation capacity (V<sub>cmax</sub>). Quantitative limitation analysis (QLA) was applied to calculate the relative contribution of diffusive and biochemical limitation to photosynthesis under salinization. Productivity was estimated by regular mowing of plants to 4cm height. Finally, plants were harvested and analyzed on leaf mass per area (LMA), leaf N content and <sup>15</sup>N isotope composition. Rhizosphere soil was sampled and analyzed on the activity of enzymes involved in the cycling of C, N, S and P. </p><p>Salinity increased LMA and leaf N, reducing  Lolium aboveground productivity. Photosynthetic rates were almost halved under both salinity treatments. QLA shows that photosynthesis was mainly limited by g<sub>m</sub>, limitation accounting for 68% and 54% of the total limitation in 30mM and 90mM, respectively. g<sub>s</sub> reduction significantly limited photosynthesis only in 90 mM (32% of total limitation), while biochemical limitations (due to a reduction in V<sub>cmax</sub>) remained below 20% of the total limitation in both treatments.</p><p>Mesophyll conductance to CO<sub>2 </sub>depends on leaf anatomical and biochemical traits and is usually negatively related to LMA. The increased LMA observed under salinity treatments suggests that changes in the leaf structure (like increased cell wall thickness) could be responsible for most of the A (and consequently productivity) reduction.  On the other hand, the increased leaf N content is in agreement with the lack of significant reduction in V<sub>cmax</sub>. Accumulation of N compounds in leaves in response to salinization was accompanied by a decline in soil extracellular enzymes involved in N and other cycles. Over-competing of the microbial pool in access to nutrients by vegetation could be suggested in conditions of salinization. Because the belowground biomass was not affected, decline in C losses with salinization could be hypothesize which should balance the shortage in C inputs.     </p><p>In conclusion, salinization mainly limited A through g<sub>m</sub> limitation, probably associated  to the increased LMA. At the same time, altering the capacity of the microbial pool to compete for N,  it increased leaf N, possibly reducing  the impact of biochemical limitation on A and avoiding a further A and productivity decline.</p><p>Experiment was financially supported by the Russian Science Foundation, project No.17-77-20046.</p>

scholarly journals Comparative Nitrogen Uptake and Distribution in Corn and Velvetleaf (Abutilon theophrasti)

Weed Science ◽  
2007 ◽  
Vol 55 (2) ◽  
pp. 102-110 ◽  
Author(s):  
John L. Lindquist ◽  
Darren C. Barker ◽  
Stevan Z. Knezevic ◽  
Alexander R. Martin ◽  
Daniel T. Walters
Keyword(s):  
N Uptake ◽  
Soil Nutrient ◽  
Biomass Accumulation ◽  
Field Studies ◽  
Total Biomass ◽  
N Addition ◽  
N Content ◽  
Area Index ◽  
Leaf N Content ◽  
Leaf N

Weeds compete with crops for light, soil water, and nutrients. Nitrogen (N) is the primary limiting soil nutrient. Forecasting the effects of N on growth, development, and interplant competition requires accurate prediction of N uptake and distribution within plants. Field studies were conducted in 1999 and 2000 to determine the effects of variable N addition on monoculture corn and velvetleaf N uptake, the relationship between plant N concentration ([N]) and total biomass, the fraction of N partitioned to leaves, and predicted N uptake and leaf N content. Cumulative N uptake of both species was generally greater in 2000 than in 1999 and tended to increase with increasing N addition. Corn and velvetleaf [N] declined with increasing biomass in both years in a predictable manner. The fraction of N partitioned to corn and velvetleaf leaves varied with thermal time from emergence but was not influenced by year, N addition, or weed density. With the use of the [N]–biomass relationship to forecast N demand, cumulative corn N uptake was accurately predicted for three of four treatments in 1999 but was underpredicted in 2000. Velvetleaf N uptake was accurately predicted in all treatments in both years. Leaf N content (NL, g N m−2leaf) was predicted by the fraction of N partitioned to leaves, predicted N uptake, and observed leaf area index for each species. Average deviations between predicted and observed corn NLwere < 88 and 12% of the observed values in 1999 and 2000, respectively. Velvetleaf NLwas less well predicted, with average deviations ranging from 39 to 248% of the observed values. Results of this research indicate that N uptake in corn and velvetleaf was driven primarily by biomass accumulation. Overall, the approaches outlined in this paper provide reasonable predictions of corn and velvetleaf N uptake and distribution in aboveground tissues.

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