The quality of short-wave radiation within plant canopies

1969 ◽  
Vol 47 (12) ◽  
pp. 1989-1994 ◽  
Author(s):  
T. B. Daynard
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Plant Communities ◽  
Short Wave ◽  
Wave Radiation ◽  
Leaf Angle ◽  
Visible Radiation ◽  
Area Index ◽  
Plant Canopies

In this paper, a mathematical attempt is made to predict the effects of leaf area index, leaf angle, and leaf spectral properties on changes in the relative composition of short-wave radiant fluxes as they penetrate plant canopies. Results of this theoretical analysis indicate that a sizeable change in the quality of visible radiation will only occur if the canopy is sufficiently dense to intercept at least 98% of the incident flux one or more times. By contrast, a significant increase in the proportion of infrared radiation is predicted within plant communities, even those of a low effective leaf area index. For natural plant communities, the results would indicate a minimal change in the composition of penetrating radiation at solar noon and a maximal change at sunrise or sunset.The implications of these phenomena to plant morphogenesis and to radiation-measuring techniques are discussed.

The effect of planting date and nitrogen management on yield and quality of aromatic rice (Oryza sativa)

2004 ◽  
Vol 142 (2) ◽  
pp. 183-191 ◽  
Author(s):  
M. GHOSH ◽  
B. K. MANDAL ◽  
B. B. MANDAL ◽  
S. B. LODH ◽  
A. K. DASH
Keyword(s):  
Oryza Sativa ◽  
Grain Yield ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Amylose Content ◽  
Aromatic Rice ◽  
Area Index ◽  
Growth Environment ◽  
Yield And Quality

Growth environment and plant nutrition are two important factors influencing growth, yield and quality of aromatic rice (Oryza sativa L.). The present study was conducted at Kalyani, India to determine the effect of two planting dates and four fertilizer levels on different aromatic rice cultivars during the dry seasons of 1995/96 and 1996/97, while nine cultivars were evaluated during the wet seasons of 1996 and 1997. Thermal and photoperiodic conditions significantly influenced the vegetative (leaf area index and light extinction co-efficient) and reproductive (filled spikelets/panicle) growth of the crop. Delayed planting (23 February) significantly reduced the grain yield by 0·88 t/ha, amylose content by 0·5% and duration by 10 days; but increased the summed heliothermal units (17806 v. 18505). Thus, the cultivars became less efficient (27%) in heat use with delay in planting from 2 to 23 February. Relative availability of NH4+-N from urea and Azolla influenced the crop growth (leaf area index [LAI], tiller production and leaf chlorophyll content) and nutrient uptake. Supply of inorganic N either alone or in conjunction with Azolla significantly increased grain yield (18–41%) and protein content (0·1–0·7%) over 15 t/ha of Azolla alone. However, combined application of Azolla and urea lowered the amylose content below that achieved by application of either substance alone. Correlation studies among quality attributes indicated that long-grained varieties had lower head rice recovery (r=−0·69) due to more breakage during milling and greater test weight (r=0·93).

scholarly journals Evaluation of the growth and quality of lettuce (Lactuca sativa L.) in a closed recirculating hydroponic system

2017 ◽  
Vol 35 (2) ◽  
pp. 216-222 ◽  
Author(s):  
Rafael David Fraile-Robayo ◽  
Javier Giovanni Álvarez-Herrera ◽  
Andrea Johana Reyes M. ◽  
Omar Ferney Álvarez-Herrera ◽  
Ana Lucía Fraile-Robayo
Keyword(s):  
Growth Rate ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Calcium Nitrate ◽  
Potassium Nitrate ◽  
Area Index ◽  
Hydroponic System ◽  
Physiological Variables ◽  
Over Time

The production of lettuce in hydroponic systems with a recirculating nutrient solution has been growing, so it is necessary to evaluate the growth and quality of production under this system. Two harvest cycles were evaluated, comparing the behavior of physiological variables and growth rates on lettuce plants in a hydroponic system with a plastic cover. Lettuce plants were planted at 30 days after germination in an NFT hydroponic system. Nutrient solutions were prepared with sources of potassium nitrate, calcium nitrate, urea phosphate, magnesium sulfate and a source of minor nutrifeed. The second cycle had the highest total dry mass and leaf area index (LAI) at 43 days after transplant (dat). The relative growth rate (RGR) declined over time. The absolute growth rate (AGR) presented a sigmoid behavior as a gaussian bell shape; the leaf area index (LAI) increased until 43 dat, with the second cycle presenting the highest value; the net assimilation rate (NAR) decreased over time, with the second cycle having the highest value at 22 dat. The chlorophyll content for this variety was low, with a yellow pigmentation in the plant. The stomatal conductance (SC) in the two cycles at transplant time presented low values caused by the stress leaded by an imbalance in the pH of the solution, when the plants adapted to the system, this value increased.

scholarly journals A Random Forest Algorithm for Retrieving Canopy Chlorophyll Content of Wheat and Soybean Trained with PROSAIL Simulations Using Adjusted Average Leaf Angle

2021 ◽  
Vol 14 (1) ◽  
pp. 98
Author(s):  
Quanjun Jiao ◽  
Qi Sun ◽  
Bing Zhang ◽  
Wenjiang Huang ◽  
Huichun Ye ◽  
...  
Keyword(s):  
Random Forest ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Chlorophyll Content ◽  
Leaf Angle ◽  
Transfer Model ◽  
Growth Monitoring ◽  
Random Forest Algorithm ◽  
Area Index ◽  
Important Indicator

Canopy chlorophyll content (CCC) is an important indicator for crop-growth monitoring and crop productivity estimation. The hybrid method, involving the PROSAIL radiative transfer model and machine learning algorithms, has been widely applied for crop CCC retrieval. However, PROSAIL’s homogeneous canopy hypothesis limits the ability to use the PROSAIL-based CCC estimation across different crops with a row structure. In addition to leaf area index (LAI), average leaf angle (ALA) is the most important canopy structure factor in the PROSAIL model. Under the same LAI, adjustment of the ALA can make a PROSAIL simulation obtain the same canopy gap as the heterogeneous canopy at a specific observation angle. Therefore, parameterization of an adjusted ALA (ALAadj) is an optimal choice to make the PROSAIL model suitable for specific row-planted crops. This paper attempted to improve PROSAIL-based CCC retrieval for different crops, using a random forest algorithm, by introducing the prior knowledge of crop-specific ALAadj. Based on the field reflectance spectrum at nadir, leaf area index, and leaf chlorophyll content, parameterization of the ALAadj in the PROSAIL model for wheat and soybean was carried out. An algorithm integrating the random forest and PROSAIL simulations with prior ALAadj information was developed for wheat and soybean CCC retrieval. Ground-measured CCC measurements were used to validate the CCC retrieved from canopy spectra. The results showed that the ALAadj values (62 degrees for wheat; 45 degrees for soybean) that were parameterized for the PROSAIL model demonstrated good discrimination between the two crops. The proposed algorithm improved the CCC retrieval accuracy for wheat and soybean, regardless of whether continuous visible to near-infrared spectra with 50 bands (RMSE from 39.9 to 32.9 μg cm−2; R2 from 0.67 to 0.76) or discrete spectra with 13 bands (RMSE from 43.9 to 33.7 μg cm−2; R2 from 0.63 to 0.74) and nine bands (RMSE from 45.1 to 37.0 μg cm−2; R2 from 0.61 to 0.71) were used. The proposed hybrid algorithm, based on PROSAIL simulations with ALAadj, has the potential for satellite-based CCC estimation across different crop types, and it also has a good reference value for the retrieval of other crop parameters.

Derivation of Leaf-Area Index from Quality of Light on the Forest Floor

Ecology ◽  
1969 ◽  
Vol 50 (4) ◽  
pp. 663-666 ◽  
Author(s):  
Carl F. Jordan
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Forest Floor ◽  
Area Index

scholarly journals Retrieval of Leaf Area Index by Linking the PROSAIL and Ross-Li BRDF Models Using MODIS BRDF Data

2021 ◽  
Vol 13 (23) ◽  
pp. 4911
Author(s):  
Xiaoning Zhang ◽  
Ziti Jiao ◽  
Changsen Zhao ◽  
Siyang Yin ◽  
Lei Cui ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Large Scale ◽  
Near Infrared ◽  
Canopy Structure ◽  
Leaf Angle ◽  
Infrared Band ◽  
Area Index ◽  
Input Parameters ◽  
Scattering Kernel

Canopy structure parameters (e.g., leaf area index (LAI)) are key variables of most climate and ecology models. Currently, satellite-observed reflectances at a few viewing angles are often directly used for vegetation structure parameter retrieval; therefore, the information content of multi-angular observations that are sensitive to canopy structure in theory cannot be sufficiently considered. In this study, we proposed a novel method to retrieve LAI based on modelled multi-angular reflectances at sufficient sun-viewing geometries, by linking the PROSAIL model with a kernel-driven Ross-Li bi-directional reflectance function (BRDF) model using the MODIS BRDF parameter product. First, BRDF sensitivity to the PROSAIL input parameters was investigated to reduce the insensitive parameters. Then, MODIS BRDF parameters were used to model sufficient multi-angular reflectances. By comparing these reference MODIS reflectances with simulated PROSAIL reflectances within the range of the sensitive input parameters in the same geometries, the optimal vegetation parameters were determined by searching the minimum discrepancies between them. In addition, a significantly linear relationship between the average leaf angle (ALA) and the coefficient of the volumetric scattering kernel of the Ross-Li model in the near-infrared band was built, which can narrow the search scope of the ALA and accelerate the retrieval. In the validation, the proposed method attains a higher consistency (root mean square error (RMSE) = 1.13, bias = −0.19, and relative RMSE (RRMSE) = 36.8%) with field-measured LAIs and 30-m LAI maps for crops than that obtained with the MODIS LAI product. The results indicate the vegetation inversion potential of sufficient multi-angular data and the ALA relationship, and this method presents promise for large-scale LAI estimation.

scholarly journals Tight coupling between leaf area index and foliage N content in arctic plant communities

Oecologia ◽  
2004 ◽  
Vol 142 (3) ◽  
pp. 421-427 ◽  
Author(s):  
Mark T. van Wijk ◽  
Mathew Williams ◽  
Gaius R. Shaver
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Plant Communities ◽  
Tight Coupling ◽  
N Content ◽  
Area Index
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