scholarly journals Patterns of leaf morphology and leaf N content in relation to winter temperatures in three evergreen tree species

2011 ◽  
Vol 56 (5) ◽  
pp. 915-926 ◽  
Author(s):  
Sonia Mediavilla ◽  
Victoria Gallardo-López ◽  
Patricia González-Zurdo ◽  
Alfonso Escudero
Keyword(s):  
Tree Species ◽  
Leaf Morphology ◽  
N Content ◽  
Evergreen Tree ◽  
Winter Temperatures ◽  
Leaf N Content ◽  
Leaf N

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.

Photosynthetic characteristics in relation to leaf traits in eight co-existing pioneer tree species in Central Sulawesi, Indonesia

2004 ◽  
Vol 20 (2) ◽  
pp. 157-164 ◽  
Author(s):  
Dirk Hölscher ◽  
C. Leuschner ◽  
K. Bohman ◽  
J. Juhrbandt ◽  
S. Tjitrosemito
Keyword(s):  
Nitrogen Content ◽  
Tree Species ◽  
Functional Group ◽  
Leaf Size ◽  
Leaf Traits ◽  
Interspecific Variation ◽  
Pioneer Tree Species ◽  
Pioneer Tree ◽  
Leaf N Content ◽  
Leaf N

Tropical pioneer tree species are considered as a functional group characterized by a suite of ecological characteristics such as high light demand and high photosynthetic capacities. This study compared the photosynthetic characteristics of eight co-existing pioneer tree species in 3–4-y-old and about 6-m-tall secondary forest stands in Sulawesi, Indonesia. Its objectives were (1) to determine the range and interspecific variation in six photosynthetic parameters, and (2) to identify morphological and chemical leaf traits that can predict light-saturated net photosynthetic rates (on a leaf area or leaf mass basis, Amax-area or Amax-mass). Species averages of Amax-area in sun leaves ranged between 14.2 and 20.3 μmol m−2 s−1 (mean 17.5) which is high compared with literature data. Among the co-existing species, average leaf size (56–896 cm2) differed by a factor of 16, specific leaf area (SLA, 10.7–21.4 m2 kg−1) and leaf nitrogen content (19.6–33.9 g kg−1) twofold. At the species level, Amax-area was not correlated with leaf N content but decreased significantly with leaf size. Amax-mass showed a higher interspecific variation than Amax-area, and was positively correlated with SLA and leaf N content (slope: 13.4 nmol CO2 g N−1 s−1). Both, Amax-area and Amax-mass were more closely related to leaf morphological attributes than to leaf N. We conclude that the tropical pioneer tree species studied do not form a homogeneous functional group in terms of photosynthetic performance. Rather, a considerable variation in leaf morphology and nitrogen content exists, which also shows up in a substantial variation in Amax-mass and, to a lesser extent, in Amax-area.

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.

scholarly journals Relationship between vegetation indices and agronomic performance of maize varieties under different nitrogen rates

2020 ◽  
Vol 36 (5) ◽  
Author(s):  
Marcela da Silva Flores ◽  
Willian Meniti Paschoalete ◽  
Fabio Henrique Rojo Baio ◽  
Cid Naudi Silva Campos ◽  
Ariane de Andréa Pantaleão ◽  
...  
Keyword(s):  
Plant Height ◽  
Precision Agriculture ◽  
Vegetation Index ◽  
Block Design ◽  
Vegetation Indices ◽  
Agronomic Performance ◽  
N Content ◽  
Maize Varieties ◽  
Leaf N Content ◽  
Leaf N

Precision agriculture is a set of techniques that assist the monitoring of the agronomic performance of the maize crop by using vegetation indices. This study aimed to verify the relationship between vegetation indices, plant height, leaf N content, and grain yield of three maize varieties, grown under high and low N as topdressing. The experiment was carried out at the Fundação de Apoio à Pesquisa Agropecuária de Chapadão (Fundação Chapadão), located in the municipality of Chapadão do Sul, during the 2017/2018 season. The experiment consisted of a randomized block design with four replications, arranged in a 3x2 split-plot scheme. The first factor (plots) corresponded to three open-pollinated maize varieties (BRS 4103, BRS Gorotuba, and SCS 154), and the second factor (subplots) consisted of two N rates applied as topdressing (80 and 160 kg- 1). All the evaluated variables showed varieties x N interaction. Vegetation indices in maize varieties were influenced by the N rate applied as topdressing. Normalized Difference Vegetation Index (NDVI) and Soil-adjusted Vegetation Index (SAVI) showed a higher correlation with plant height. At the same time, Normalized Difference Red Edge (NDRE) had a stronger association with leaf N content.

Sign in / Sign up

Export Citation Format

Share Document