Dataset Information

Parameterization of the vertical distribution of leaf area index (LAI) in rice (Oryza sativa L.) using a plant canopy analyzer.

ABSTRACT: Monitoring the vertical distribution of leaf area index (LAI) is an effective method for evaluating canopy photosynthesis and biomass productivity. In this study, we proposed a novel method to characterize LAI vertical distribution non-destructively by utilizing LAI-2200 plant canopy analyzer, followed by the application of statistical moment equations. Field experiments were conducted with 5 rice cultivars under 2 fertilizer treatments in 2013 and with 3 rice cultivars under 3 plant density treatments in 2014. LAI readings obtained by a plant canopy analyzer for non-destructive stratified measurements were relatively consistent with LAI estimations using the stratified clipping method for every cultivar and treatment. The parameters calculated using the statistical moment equations numerically showed the changes in LAI vertical distribution with plant growth up to the heading stage. The differences in the parameters also quantified the effect of cultivar, fertilizer, and plant density treatments. These results suggest that the non-destructive stratified measurements and the statistical moments evaluated in this study provide quantitative, reliable information on the dynamics of LAI vertical distribution. The method is expected to be utilized by researchers in various research fields sharing common interests.

SUBMITTER: Hirooka Y

PROVIDER: S-EPMC5913339 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Parameterization of the vertical distribution of leaf area index (LAI) in rice (Oryza sativa L.) using a plant canopy analyzer.

Hirooka Yoshihiro Y Homma Koki K Shiraiwa Tatsuhiko T

Scientific reports 20180423 1

Monitoring the vertical distribution of leaf area index (LAI) is an effective method for evaluating canopy photosynthesis and biomass productivity. In this study, we proposed a novel method to characterize LAI vertical distribution non-destructively by utilizing LAI-2200 plant canopy analyzer, followed by the application of statistical moment equations. Field experiments were conducted with 5 rice cultivars under 2 fertilizer treatments in 2013 and with 3 rice cultivars under 3 plant density tre ...[more]

PMID: 29686403

Similar Datasets

Project description:Accurate estimations of the vertical leaf nitrogen (N) distribution within a rice canopy is helpful for understanding the nutrient supply and demand of various functional leaf layers of rice and for improving the predictions of rice productivity. A two-year field experiment using different rice varieties, N rates, and planting densities was performed to investigate the vertical distribution of the leaf nitrogen concentration (LNC, %) within the rice canopy, the relationship between the LNC in different leaf layers (LNCLi, i = 1, 2, 3, 4), and the relationship between the LNCLi and the LNC at the canopy level (LNCCanopy). A vertical distribution model of the LNC was constructed based on the relative canopy height. Furthermore, the relationship between different vegetation indices (VIs) and the LNCCanopy, the LNCLi, and the LNC vertical distribution model parameters were studied. We also compared the following three methods for estimating the LNC in different leaf layers in rice canopy: (1) estimating the LNCCanopy by VIs and then estimating the LNCLi based on the relationship between the LNCLi and LNCCanopy; (2) estimating the LNC in any leaf layer of the rice canopy by VIs, inputting the result into the LNC vertical distribution model to obtain the parameters of the model, and then estimating the LNCLi using the LNC vertical distribution model; (3) estimating the model parameters by using VIs directly and then estimating the LNCLi by the LNC vertical distribution model. The results showed that the LNC in the bottom of rice canopy was more susceptible to different N rates, and changes in the LNC with the relative canopy height could be simulated by an exponential model. Vegetation indices could estimate the LNC at the top of rice canopy. R705/(R717+R491) (R2 = 0.763) and the renormalized difference vegetation index (RDVI) (1340, 730) (R2 = 0.747) were able to estimate the parameter "a" of the LNC vertical distribution model in indica rice and japonica rice, respectively. In addition, method (2) was the best choice for estimating the LNCLi (R2 = 0.768, 0.700, 0.623, and 0.549 for LNCL1, LNCL2, LNCL3, and LNCL4, respectively). These results provide technical support for the rapid, accurate, and non-destructive identification of the vertical distribution of nitrogen in rice canopies.

Project description:Knowledge about herbivores and their parasitoids in forest canopies remains limited, despite their diversity and ecological importance. Thus, it is important to understand the factors that shape the herbivore-parasitoid community structure, particularly the effect of vertical gradient. We investigated a quantitative community dataset of exposed and semiconcealed leaf-chewing larvae and their parasitoids along a vertical canopy gradient in a temperate forest. We sampled target insects using an elevated work platform in a 0.2 ha broadleaf deciduous forest plot in the Czech Republic. We analyzed the effect of vertical position among three canopy levels (first [lowest], second [middle], and third [highest]) and tree species on community descriptors (density, diversity, and parasitism rate) and food web structure. We also analyzed vertical patterns in density and parasitism rate between exposed and semiconcealed hosts, and the vertical preference of the most abundant parasitoid taxa in relation to their host specificity. Tree species was an important determinant of all community descriptors and food web structure. Insect density and diversity varied with the vertical gradient, but was only significant for hosts. Both host guilds were most abundant in the second level, but only the density of exposed hosts declined in the third level. Parasitism rate decreased from the first to third level. The overall parasitism rate did not differ between guilds, but semiconcealed hosts suffered lower parasitism in the third level. Less host-specific taxa (Ichneumonidae, Braconidae) operated more frequently lower in the canopy, whereas more host-specific Tachinidae followed their host distribution. The most host-specific Chalcidoidea preferred the third level. Vertical stratification of insect density, diversity, and parasitism rate was most pronounced in the tallest tree species. Therefore, our study contradicts the general paradigm of weak arthropod stratification in temperate forest canopies. However, in the network structure, vertical variation might be superseded by variation among tree species.

Dataset Information

Parameterization of the vertical distribution of leaf area index (LAI) in rice (Oryza sativa L.) using a plant canopy analyzer.

Publications

Parameterization of the vertical distribution of leaf area index (LAI) in rice (Oryza sativa L.) using a plant canopy analyzer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets