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1
Moatshe, O. G., V. E. Emongor, T. V. Balole, and S. O. Tshwenyane. "Safflower genotype by plant density on yield and phenological characteristics." African Crop Science Journal 28, s1 (October 2, 2020): 145–63. http://dx.doi.org/10.4314/acsj.v28i1.11s.
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Safflower (Carthamus tinctorius L.) is a temperate plant grown in arid and semi-arid regions of the world, and is the most drought tolerant oilseed crop. The objective of this study was to evaluate the effect of genotype and plant density on growth, phenology and yield of safflower. Treatments included five safflower genotypes and six plant densities laid out in a randomised block design. Increasing plant density from 62,500 to 100,000 plants ha-1 significantly (P < 0.05) increased leaf area index (LAI), leaf area duration (LAD), total leaf chlorophyll content (Tchl) and net assimilation rate (NAR) at all phenological stages in both winter and summer. For all genotypes, the highest LAI, LAD, Tchl, NAR, total dry matter accumulation (TDM) and seed yield resulted at a plant density of 100,000 plants ha-1. Maximum LAI, LAD, NAR and Tchl were observed at 50% flowering, compared to other phenological stages in all genotypes and plant densities. In general, genotype ‘Sina’ at 100,000 plants ha-1 significantly (P < 0.05) had the highest LAI, LAD, Tchl, TDM and seed yield compared to other genotypes and plant densities in both summer and winter.
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Fuentes, Sigfredo, Anthony R. Palmer, Daniel Taylor, Melanie Zeppel, Rhys Whitley, and Derek Eamus. "An automated procedure for estimating the leaf area index (LAI) of woodland ecosystems using digital imagery, MATLAB programming and its application to an examination of the relationship between remotely sensed and field measurements of LAI." Functional Plant Biology 35, no. 10 (2008): 1070. http://dx.doi.org/10.1071/fp08045.
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Leaf area index (LAI) is one of the most important variables required for modelling growth and water use of forests. Functional–structural plant models use these models to represent physiological processes in 3-D tree representations. Accuracy of these models depends on accurate estimation of LAI at tree and stand scales for validation purposes. A recent method to estimate LAI from digital images (LAID) uses digital image capture and gap fraction analysis (Macfarlane et al. 2007b) of upward-looking digital photographs to capture canopy LAID (cover photography). After implementing this technique in Australian evergreen Eucalyptus woodland, we have improved the method of image analysis and replaced the time consuming manual technique with an automated procedure using a script written in MATLAB 7.4 (LAIM). Furthermore, we used this method to compare MODIS LAI values with LAID values for a range of woodlands in Australia to obtain LAI at the forest scale. Results showed that the MATLAB script developed was able to successfully automate gap analysis to obtain LAIM. Good relationships were achieved when comparing averaged LAID and LAIM (LAIM = 1.009 – 0.0066 LAID; R2 = 0.90) and at the forest scale, MODIS LAI compared well with LAID (MODIS LAI = 0.9591 LAID – 0.2371; R2 = 0.89). This comparison improved when correcting LAID with the clumping index to obtain effective LAI (MODIS LAI = 1.0296 LAIe + 0.3468; R2 = 0.91). Furthermore, the script developed incorporates a function to connect directly a digital camera, or high resolution webcam, from a laptop to obtain cover photographs and LAI analysis in real time. The later is a novel feature which is not available on commercial LAI analysis softwares for cover photography. This script is available for interested researchers.
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Parker, Geoffrey G., and Donna J. Tibbs. "Structural Phenology of the Leaf Community in the Canopy of a Liriodendron tulipifera L. Forest in Maryland, USA." Forest Science 50, no. 3 (June 1, 2004): 387–97. http://dx.doi.org/10.1093/forestscience/50.3.387.
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Abstract We measured the vertical dynamics of leaf area in a tall, tulip poplar (Liriodendron tulipifera)-dominated, deciduous forest on the Maryland coastal plain over three growing seasons (one intensively) using nondestructive, ground-based observations. Leaf area index (LAI) and leaf area density (LAD) were calculated by vertical level, time, and species; the time-integrated duration of leaf display (leaf area extent, LAE) was estimated by species and vertical level. In this stand LAI rises rapidly in the spring, declines slightly during the growing season, and then rapidly in the fall. In the intensively studied year, total LAI peaked at 7.1 m2m-2 LAE was 1259 m2m-2day, and the length of the canopy season (time from half-maximum LAI at leaf-out to the half-maximum at decline) was 191 days. The maximum growing season LAI, the date of leaf emergence, and the LAE differed among years, ranging 0.61 m2m-2, 14 days, and 261 m2m-2day, respectively. However, the timing of leaf fall was more consistent, ranging only 6 days. Each species differs in its height distribution, density, and timing of foliar display. In the canopy, leaf number, area, and duration are the bases of species importance; these differ substantially by species from typical importance values derived from stem-based attributes (density, basal area, biomass). FOR. SCI. 50(3):387-397.
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ZHONG, X., S. PENG, J. E. SHEEHY, R. M. VISPERAS, and H. LIU. "Relationship between tillering and leaf area index: quantifying critical leaf area index for tillering in rice." Journal of Agricultural Science 138, no. 3 (May 2002): 269–79. http://dx.doi.org/10.1017/s0021859601001903.
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A field study was conducted at the International Rice Research Institute (IRRI), Philippines during the dry seasons of 1997 and 1998 under irrigated conditions. The objectives of this study were to quantify the critical leaf area index (LAIc) at which tillering stops based on the relationship between tillering rate and LAI, and to determine the effect of nitrogen (N) on LAIc in irrigated rice (Oryza sativa L.) crop. Results showed that the relative tillering rate (RTR) decreased exponentially as LAI increased at a given N input level. The coefficient of determination for the equation quantifying the RTR-LAI relationship ranged from 0·87 to 0·99. The relationship between RTR and LAI was affected by N input level, but not by planting density. The N input level had a significant effect on LAIc with a high N input level causing an increase in LAIc. Tillering stopped at LAI of 3·36 to 4·11 when N was not limiting. Under N limited conditions LAIc reduced to as low as 0·98. Transplanting spacing and number of seedlings per hill had little effect on LAIc. Results from this study suggest that LAI and plant N status are two major factors that influence tiller production in rice crops. The possibility that LAI influences tillering by changing light intensity and/or light quality at the base of the canopy where tiller buds and young tillers are located is discussed.
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Cai, LingHan, Yuan Zhao, Zhuojue Huang, Yang Gao, Han Li, and Man Zhang. "Rapid Measurement of Potato Canopy Coverage and Leaf Area Index Inversion." Applied Engineering in Agriculture 36, no. 4 (2020): 557–64. http://dx.doi.org/10.13031/aea.13875.
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Highlights This article calculates the canopy coverage (Cc) and inverts it to the leaf area index (LAI) of the collected images through a portable device such as a mobile phone, which is convenient for researchers. The Lab color model has been used for plant area extraction, which has achieved good results. Steps such as weed removal make the algorithm more universal. The inversion results of LAI based on canopy coverage has high accuracy, which indicates that it can be used for LAI calculation. Abstract . Canopy coverage (Cc) and leaf area index (LAI) are important parameters for qualitative and quantitative descriptions of plant growth trends. Meanwhile, LAI can be reflected by Cc. Therefore, it is of great significance to observe Cc and establish the relationship between Cc and LAI for monitoring the growth of plants. In July 2019, in Shang Zhuang experimental field of China Agricultural University, 30 potato canopy images were taken vertically by camera, and the actual LAI data of the corresponding images were measured and recorded by LAI-2200C. Image extraction algorithms of different models, such as ExG, ExGR, NDIGR, and Lab color space extraction model are evaluated and compared. After that, estimating the parameters of the logarithmic model of LAI-Cc by minimizing errors, evaluating the inversion model by Hold-Out. Besides, the result shows Cc can be calculated efficiently by using Lab color space extraction model. In the training set, the average value of R2 between the predicted LAI and the actual LAI reaches 0.940, and the RMSE reaches 0.144. In the test set, the average value of R2 reaches 0.937, the RMSE reaches 0.197. And the average time consumption of the entire process is 2.989 s on an image. It suggests that the study can provide a basis for dynamic monitoring of potato and other crops. Keywords: Canopy coverage (Cc), Leaf area index (LAI), Image processing, Potato, Rapid measurement.
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Cai, LingHan, Yuan Zhao, Zhuojue Huang, Yang Gao, Han Li, and Man Zhang. "Rapid Measurement of Potato Canopy Coverage and Leaf Area Index Inversion." Applied Engineering in Agriculture 36, no. 4 (2020): 557–64. http://dx.doi.org/10.13031/aea13875.
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Highlights This article calculates the canopy coverage (Cc) and inverts it to the leaf area index (LAI) of the collected images through a portable device such as a mobile phone, which is convenient for researchers. The Lab color model has been used for plant area extraction, which has achieved good results. Steps such as weed removal make the algorithm more universal. The inversion results of LAI based on canopy coverage has high accuracy, which indicates that it can be used for LAI calculation. Abstract . Canopy coverage (Cc) and leaf area index (LAI) are important parameters for qualitative and quantitative descriptions of plant growth trends. Meanwhile, LAI can be reflected by Cc. Therefore, it is of great significance to observe Cc and establish the relationship between Cc and LAI for monitoring the growth of plants. In July 2019, in Shang Zhuang experimental field of China Agricultural University, 30 potato canopy images were taken vertically by camera, and the actual LAI data of the corresponding images were measured and recorded by LAI-2200C. Image extraction algorithms of different models, such as ExG, ExGR, NDIGR, and Lab color space extraction model are evaluated and compared. After that, estimating the parameters of the logarithmic model of LAI-Cc by minimizing errors, evaluating the inversion model by Hold-Out. Besides, the result shows Cc can be calculated efficiently by using Lab color space extraction model. In the training set, the average value of R2 between the predicted LAI and the actual LAI reaches 0.940, and the RMSE reaches 0.144. In the test set, the average value of R2 reaches 0.937, the RMSE reaches 0.197. And the average time consumption of the entire process is 2.989 s on an image. It suggests that the study can provide a basis for dynamic monitoring of potato and other crops. Keywords: Canopy coverage (Cc), Leaf area index (LAI), Image processing, Potato, Rapid measurement.
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Vose, James M., and H. Lee Allen. "Leaf Area, Stemwood Growth, and Nutrition Relationships in Loblolly Pine." Forest Science 34, no. 3 (September 1, 1988): 547–63. http://dx.doi.org/10.1093/forestscience/34.3.547.
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Abstract The relationships among loblolly pine (Pinus taeda L.) stand leaf area index (LAD, stemwood volume growth (m3/ha/yr), and growth efficiency (m3stemwood/ha/yr/LAI) were examined in three nitrogen (N) by phosphorus (P) fertilization field trials. Prior to fertilization, stockinglevels and nitrogen limitations varied for the three stands. LAI increased significantly (up to 60%) following N fertilization on the two N deficient stands. Phosphorus additions did not affect LAI. Stemwood growth was positively and linearly related to LAI across treatments and stands. Variationsin LAI across stands reflected the differences in stocking and N availability. On average, a unit of LAI produced 7.3 m3stemwood/ha/yr. Growth efficiency was not affected by fertilization on two of the three stands. A decrease in growth efficiency at a projected LAI above 3.5 resultedfrom an asymptotic relationship between stemwood growth and LAI on a stand that was fully stocked and highly responsive to N fertilization. The use of LAI as an index of stocking is proposed because LAI integrates tree size, stand density, and site resource supply. In addition, it is proposedthat the deviation of a stand's current LAI from the maximum supportable LAI based on fixed site factors (e.g., water, temperature) may provide a good measure of a stand's potential responsiveness to fertilization. For. Sci. 34(3):547-563.
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Toepp, Stephen L., Claudia V. Turco, Ravjot S. Rehsi, and Aimee J. Nelson. "The distribution and reliability of TMS-evoked short- and long-latency afferent interactions." PLOS ONE 16, no. 12 (December 14, 2021): e0260663. http://dx.doi.org/10.1371/journal.pone.0260663.
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Short-latency afferent inhibition (SAI) and long-latency afferent inhibition (LAI) occur when the motor evoked potential (MEP) elicited by transcranial magnetic stimulation (TMS) is reduced by the delivery of a preceding peripheral nerve stimulus. The intra-individual variability in SAI and LAI is considerable, and the influence of sample demographics (e.g., age and biological sex) and testing context (e.g., time of day) is not clear. There are also no established normative values for these measures, and their reliability varies from study-to-study. To address these issues and facilitate the interpretation of SAI and LAI research, we pooled data from studies published by our lab between 2014 and 2020 and performed several retrospective analyses. Patterns in the depth of inhibition with respect to age, biological sex and time of testing were investigated, and the relative reliability of measurements from studies with repeated baseline SAI and LAI assessments was examined. Normative SAI and LAI values with respect to the mean and standard deviation were also calculated. Our data show no relationship between the depth of inhibition for SAI and LAI with either time of day or age. Further, there was no significant difference in SAI or LAI between males and females. Intra-class correlation coefficients (ICC) for repeated measurements of SAI and LAI ranged from moderate (ICC = 0.526) to strong (ICC = 0.881). The mean value of SAI was 0.71 ± 0.27 and the mean value of LAI was 0.61 ± 0.34. This retrospective study provides normative values, reliability estimates, and an exploration of demographic and testing influences on these measures as assessed in our lab. To further facilitate the interpretation of SAI and LAI data, similar studies should be performed by other labs that use these measures.
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Yang, Xueqin, Xiuzhi Chen, Jiashun Ren, Wenping Yuan, Liyang Liu, Juxiu Liu, Dexiang Chen, et al. "A gridded dataset of a leaf-age-dependent leaf area index seasonality product over tropical and subtropical evergreen broadleaved forests." Earth System Science Data 15, no. 6 (June 27, 2023): 2601–22. http://dx.doi.org/10.5194/essd-15-2601-2023.
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Abstract. The quantification of large-scale leaf-age-dependent leaf area index has been lacking in tropical and subtropical evergreen broadleaved forests (TEFs), despite the recognized importance of leaf age in influencing leaf photosynthetic capacity in this biome. Here, we simplified the canopy leaves of TEFs into three age cohorts (i.e., young, mature, and old, with different photosynthesis capacities; i.e., Vc,max) and proposed a novel neighbor-based approach to develop the first gridded dataset of a monthly leaf-age-dependent leaf area index (LAI) product (referred to as Lad-LAI) at 0.25∘ spatial resolution over the continental scale during 2001–2018 from satellite observations of sun-induced chlorophyll fluorescence (SIF) that was reconstructed from MODIS and TROPOMI (the TROPOspheric Monitoring Instrument). The new Lad-LAI products show good performance in capturing the seasonality of three LAI cohorts, i.e., young (LAIyoung; the Pearson correlation coefficient of R=0.36), mature (LAImature; R=0.77), and old (LAIold; R=0.59) leaves at eight camera-based observation sites (four in South America, three in subtropical Asia, and one in the Democratic Republic of the Congo (DRC)) and can also represent their interannual dynamics, validated only at the Barro Colorado site, with R being equal to 0.54, 0.64, and 0.49 for LAIyoung, LAImature, and LAIold, respectively. Additionally, the abrupt drops in LAIold are mostly consistent with the seasonal litterfall peaks at 53 in situ measurements across the whole tropical region (R=0.82). The LAI seasonality of young and mature leaves also agrees well with the seasonal dynamics of the enhanced vegetation index (EVI; R=0.61), which is a proxy for photosynthetically effective leaves. Spatially, the gridded Lad-LAI data capture a dry-season green-up of canopy leaves across the wet Amazonian areas, where mean annual precipitation exceeds 2000 mm yr−1, consistent with previous satellite-based analyses. The spatial patterns clustered from the three LAI cohorts also coincide with those clustered from climatic variables over the whole TEF region. Herein, we provide the average seasonality of three LAI cohorts as the main dataset and their time series as a supplementary dataset. These Lad-LAI products are available at https://doi.org/10.6084/m9.figshare.21700955.v4 (Yang et al., 2022).
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Liang, Boyi, Hongyan Liu, Xiaoqiu Chen, Xinrong Zhu, Elizabeth L. Cressey, and Timothy A. Quine. "Periodic Relations between Terrestrial Vegetation and Climate Factors across the Globe." Remote Sensing 12, no. 11 (June 3, 2020): 1805. http://dx.doi.org/10.3390/rs12111805.
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In this paper, cross-spectrum analysis was used to verify the agreement of periodicity between the global LAI (leaf area index) and climate factors. The results demonstrated that the LAI of deciduous forests and permanent wetlands have high agreement with temperature, rainfall and radiation over annual cycles. A low agreement between the LAI and seasonal climate variables was observed for some of the temperate and tropical vegetation types including shrublands and evergreen broadleaf forests, possibly due to the diversity of vegetation and human activities. Across all vegetation types, the LAI demonstrated a large time lag following variation in radiation (>1 month), whereas relatively short lag periods were observed between the LAI and annual temperature (around 2 weeks)/rainfall patterns (less than 10 days), suggesting that the impact of radiation on global vegetation growth is relatively slow, which is in accord with the results of previous studies. This work can provide a benchmark of the phenological drivers in global vegetation, from the perspective of periodicity, as well as helping to parameterize and refine the DGVMs (Dynamic Global Vegetation Models) for different vegetation types.
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Yan, Guangjian, Hailan Jiang, Jinghui Luo, Xihan Mu, Fan Li, Jianbo Qi, Ronghai Hu, Donghui Xie, and Guoqing Zhou. "Quantitative Evaluation of Leaf Inclination Angle Distribution on Leaf Area Index Retrieval of Coniferous Canopies." Journal of Remote Sensing 2021 (April 12, 2021): 1–15. http://dx.doi.org/10.34133/2021/2708904.
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Both leaf inclination angle distribution (LAD) and leaf area index (LAI) dominate optical remote sensing signals. The G-function, which is a function of LAD and remote sensing geometry, is often set to 0.5 in the LAI retrieval of coniferous canopies even though this assumption is only valid for spherical LAD. Large uncertainties are thus introduced. However, because numerous tiny leaves grow on conifers, it is nearly impossible to quantitatively evaluate such uncertainties in LAI retrieval. In this study, we proposed a method to characterize the possible change of G-function of coniferous canopies as well as its effect on LAI retrieval. Specifically, a Multi-Directional Imager (MDI) was developed to capture stereo images of the branches, and the needles were reconstructed. The accuracy of the inclination angles calculated from the reconstructed needles was high. Moreover, we analyzed whether a spherical distribution is a valid assumption for coniferous canopies by calculating the possible range of the G-function from the measured LADs of branches of Larch and Spruce and the true G-functions of other species from some existing inventory data and three-dimensional (3D) tree models. Results show that the constant G assumption introduces large errors in LAI retrieval, which could be as large as 53% in the zenithal viewing direction used by spaceborne LiDAR. As a result, accurate LAD estimation is recommended. In the absence of such data, our results show that a viewing zenith angle between 45 and 65 degrees is a good choice, at which the errors of LAI retrieval caused by the spherical assumption will be less than 10% for coniferous canopies.
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CAO, XIAOYAN, and MICHAEL DOLG. "PSEUDOPOTENTIAL STUDIES ON THE ELECTRONIC STRUCTURE OF LANTHANUM MONOHALIDES LaF, LaCl, LaBr, AND LaI." Journal of Theoretical and Computational Chemistry 04, spec01 (January 2005): 583–92. http://dx.doi.org/10.1142/s0219633605001660.
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Relativistic energy-consistent small-core lanthanide pseudopotentials of the Stuttgart–Köln variety and corresponding valence basis sets have been used for the investigation of the ground state (1Σ+) lanthanum monohalides LaF , LaCl , LaBr , and LaI . The molecular constants were derived from coupled-cluster calculations, taking into account corrections for atomic spin-orbit splitting as well as basis set superposition errors. With the exception of the binding energies for LaI the theoretical values for LaF (Re = 2.034 Å, De = 6.73 eV , ωe = 574 cm -1), LaCl (Re = 2.517 Å, De = 5.11 eV , ωe = 339 cm -1), LaBr (Re = 2.664 Å, De = 4.47 eV , ωe = 236 cm -1), and LaI (Re = 2.891 Å, De = 3.65 eV , ωe = 186 cm -1) show good agreement with the experimental data. The calculated binding energy (3.65 eV) for LaI is in-between the two conflicting estimated experimental data (2.97 eV, 4.29 eV).
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Hashimoto, Naoyuki, Yuki Saito, Shuhei Yamamoto, Taro Ishibashi, Ruito Ito, Masayasu Maki, and Koki Homma. "Relationship between Leaf Area Index and Yield Components in Farmers’ Paddy Fields." AgriEngineering 5, no. 4 (October 9, 2023): 1754–65. http://dx.doi.org/10.3390/agriengineering5040108.
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Estimation of rice yield components is required to optimize cultivation management in fields. The leaf area index (LAI) can be a parameter for this estimation, but it has not been evaluated in farmers’ fields. In this study, we analyzed the relationship between the LAI and yield components using data collected over a five-year period in farmers’ fields for the cultivar Hitomebore. Leaf area dynamics (LAD) were parameterized by fitting a growth function to the time-series data of LAI measured using a canopy analyzer. The contribution of LAD to yield components was analyzed using multiple regression. The LAIs at five points during the growing season (effective integrated temperatures of 200, 400, 600, 800, and 1000 °Cd) were calculated using the growth function and the relationship between them and the yield components were analyzed using linear regression. The results of the multiple regression analysis showed that all function parameters significantly affected the yield components at the 5% probability level, with the greatest contribution from the LAI. The LAI at effective integrated temperatures of 400 to 600 °Cd significantly affected most of the yield components. However, the correlation coefficients between the LAI and yield components were not high (R = 0.18–0.61). The LAIs at almost all periods significantly affected the grain number per panicle and 1000-grain weight at the 5% probability level. These results suggest that the LAI could be used for monitoring trends in yield components, while further research on the development of accurate estimation methods is needed.
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Cifuentes, Renato, Dimitry Van der Zande, Christian Salas-Eljatib, Jamshid Farifteh, and Pol Coppin. "A Simulation Study Using Terrestrial LiDAR Point Cloud Data to Quantify Spectral Variability of a Broad-Leaved Forest Canopy." Sensors 18, no. 10 (October 8, 2018): 3357. http://dx.doi.org/10.3390/s18103357.
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In this analysis, a method for construction of forest canopy three-dimensional (3D) models from terrestrial LiDAR was used for assessing the influence of structural changes on reflectance for an even-aged forest in Belgium. The necessary data were extracted by the developed method, as well as it was registered the adjacent point-clouds, and the canopy elements were classified. Based on a voxelized approach, leaf area index (LAI) and the vertical distribution of leaf area density (LAD) of the forest canopy were derived. Canopy–radiation interactions were simulated in a ray tracing environment, giving suitable illumination properties and optical attributes of the different canopy elements. Canopy structure was modified in terms of LAI and LAD for hyperspectral measurements. It was found that the effect of a 10% increase in LAI on NIR reflectance can be equal to change caused by translating 50% of leaf area from top to lower layers. As presented, changes in structure did affect vegetation indices associated with LAI and chlorophyll content. Overall, the work demonstrated the ability of terrestrial LiDAR for detailed canopy assessments and revealed the high complexity of the relationship between vertical LAD and reflectance.
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Jiang, Hanyang. "Selected Plays of Stan Lai by Stan Lai (review)." Asian Theatre Journal 40, no. 2 (September 2023): 430–34. http://dx.doi.org/10.1353/atj.2023.a912924.
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ORLANDO, F., M. MANCINI, R. MOTHA, J. J. QU, S. ORLANDINI, and A. DALLA MARTA. "Modelling durum wheat (Triticum turgidum L. var. durum) grain protein concentration." Journal of Agricultural Science 155, no. 6 (December 14, 2016): 930–38. http://dx.doi.org/10.1017/s0021859616001003.
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SUMMARYThe goal of the present study was to improve the CERES-wheat model simulation of grain protein concentration (GPC) for winter durum wheat and to use the model as a basis for the development of a GPC Simplified Forecasting Index (SFIpro). The performances of CERES-wheat, which is one of the most widespread crop simulation models, with (i) its standard GPC routine and (ii) a novel equation developed to improve the model GPC simulation for durum wheat, were assessed through comparison with field data. Subsequently, CERES-wheat was run for a 56-year period in order to identify the most important status and forcing variables affecting GPC simulation. The number of dry days during the early growth stages and the leaf area index (LAI; green leaf area per unit ground surface area) at heading stage (LAI5) were identified as the main variables positively correlated with CERES-wheat predicted GPC, and so included in the SFIpro. At validation against observed data SFIpro was found to perform differently on the basis of observed plant LAI. In fact, SFIpro was able to forecast GPC variability for intermediate values of LAI5 ranging from 1 to 2, while it totally failed when LAI5 was outside this range (LAI5 < 1 or LAI5 > 2). The results suggest that the relationship between LAI and GPC is not linear and that the model assumptions for GPC simulation in CERES-wheat are only partially confirmed, being valid for an intermediate range of LAI.
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Jung, Hyun-Suk, Yoosoo Chang, and Seungho Ryu. "Response to Lai." American Journal of Gastroenterology 114, no. 6 (June 2019): 998–1000. http://dx.doi.org/10.14309/ajg.0000000000000273.
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Cash, Brooks D., Brian E. Lacy, Philip S. Schoenfeld, Leonard S. Dove, and Paul S. Covington. "Response to Lai." American Journal of Gastroenterology 114, no. 7 (July 2019): 1177–78. http://dx.doi.org/10.14309/ajg.0000000000000312.
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EKE-OKORO, O. N., O. U. OKEREKE, and J. E. OKEKE. "Effect of stake sizes on some growth indices and yield of three cassava cultivars (Manihot esculenta)." Journal of Agricultural Science 137, no. 4 (December 2001): 419–26. http://dx.doi.org/10.1017/s0021859601001320.
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The effects of five stake weights (50, 63, 75, 88 and 100 g) of three cassava cultivars (TMS 30572, TMS 91934 and NR 8083) on the growth and yield of cassava were studied for 2 years (1992/93 and 1993/94) in Nigeria. The leaf area index (LAI), crop growth rate (CGR), net assimilation rate (NAR), leaf area duration (LAD), harvest yield and harvest index (HI) were dependent on the weight of stake planted and were greatest at the stake weight of 88 g (875 kg/ha) irrespective of cassava cultivar. Variations in LAI, LAD and HI of stake weights between 75 and 100 g were non-significant. The profusely branching cassava cultivars, TMS 30572 and NR 8083, achieved greater LAI, CGR, NAR and LAD relative to the sparsely branching cultivar, TMS 91934. The significant growth and yield differences among the stake weights with the optimum at a stake weight of 88 g (875 kg/ha) indicates the need to adopt this stake weight for sustainable and improved growth and yield in cassava production.
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Singh, Jagjeet, Maharani Din, K. N. Agrawal, Bikram Jyoti, A. K. Roul, and Vikas Pagare. "Assessment of morphological attributes of Guava tree for design of a novel tunnel spraying system." Environment Conservation Journal 25, no. 1 (February 5, 2024): 1–9. http://dx.doi.org/10.36953/ecj.23882628.
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The morphological attributes play a significant role in determining the level of applied insecticide by the existing spraying system. Therefore, this attempt was made to assess the various morphological attributes of guava tree such as leaf size, leaf area, leaf area index (LAI) and leaf area density (LAD). In this study, two leaf area estimation techniques (grid count method and Image processing technique based on ImageJ software) were compared and also estimate LAI and LAD for ten trees. An average leaf area was registered 29.56 cm2 and R2 value (0.98) for predicting leaf area by image processing technique. The LAI and LAD varied from 0.69 to 2.17 m2/m2 and 0.53 to 1.89 m2/m3, respectively. In addition, minimum and maximum LAD (mean ± SD) for zone wise ranged from 0.07 ± 0.06 m2/m3 to 2.73 ± 1.43 m2/m3, respectively. The study findings provide an opportunity to deal with large volume of leafs for leaf area estimation and would also help in design of various sprayers like determining the dimensions of tunnel sprayer and allow them to test in laboratory conditions with simulated artificial tree.
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Awaya, Yoshio, and Kazuho Araki. "Estimating Three-Dimensional Distribution of Leaf Area Using Airborne LiDAR in Deciduous Broad-Leaved Forest." Remote Sensing 15, no. 12 (June 10, 2023): 3043. http://dx.doi.org/10.3390/rs15123043.
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We examined the performance of airborne light detection and ranging (LiDAR) data obtained in 2011 for leaf area estimation in deciduous broad-leaved forest using the Beer–Lambert law in Takayama, Gifu, Japan. We estimated leaf area index (LAI, allometry-LAI) and vertical leaf area density (LAD) using field survey data by applying allometric equations to estimate leaf-area of trees and a Weibull distribution equation to estimate vertical leaf distribution. We then estimated extinction coefficients (Ke) of LiDAR data for three height layers from the ground to the canopy top using the vertical LAD and vertical laser pulse distribution. The estimated PAI (LiDAR-PAI) using the Beer–Lambert law and Ke, when treating the canopies as three height layers, showed a significant linear relationship with allometry-LAI (p < 0.001). However, LiDAR-PAI when treating the canopies as single layer saturated at a PAI of six. It was similar to the lesser PAI estimation by hemispherical photography or relative photosynthetic photon flux density which treated the canopy as a single layer, compared to LAI measurements by litter traps. It is therefore important to allocate distinct Ke values to each of the multiple height layers for an accurate estimation of PAI and vertical PAD when applying the Beer–Lambert law to airborne LiDAR data.
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Rouzbeh Kargar, Ali, Richard MacKenzie, Gregory P. Asner, and Jan van Aardt. "A Density-Based Approach for Leaf Area Index Assessment in a Complex Forest Environment Using a Terrestrial Laser Scanner." Remote Sensing 11, no. 15 (July 31, 2019): 1791. http://dx.doi.org/10.3390/rs11151791.
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Forests are an important part natural ecosystems, by for example providing food, fiber, habitat, and biodiversity, all of which contribute to stable natural systems. Assessing and modeling the structure and characteristics of forests, e.g., Leaf Area Index (LAI), volume, biomass, etc., can lead to a better understanding and management of these resources. In recent years, Terrestrial Laser Scanning (TLS) has been recognized as a tool that addresses many of the limitations of manual and traditional forest data collection methods. In this study, we propose a density-based approach for estimating the LAI in a structurally-complex forest environment, which contains variable and diverse structural attributes, e.g., non-circular stem forms, dense canopy and below-canopy vegetation cover, and a diverse species composition. In addition, 242 TLS scans were collected using a portable low-cost scanner, the Compact Biomass Lidar (CBL), in the Hawaii Volcanoes National Park (HAVO), Hawaii Island, USA. LAI also was measured for 242 plots in the site, using an AccuPAR LP-80 ceptometer. The first step after cleaning the point cloud involved detecting the higher forest canopy in the light detection and ranging (lidar) point clouds, using normal change rate assessment. We then estimated Leaf Area Density (LAD), using a voxel-based approach, and divided the canopy point cloud into five layers in the Z (vertical) direction. These five layers subsequently were divided into voxels in the X direction, where the size of these voxels were obtained based on inter-quartile analysis and the number of points in each voxel. We hypothesized that the intensity returned to the lidar system from woody materials, like branches, would be higher than from leaves, due to the liquid water absorption feature of the leaves and higher reflectance for woody material at the 905 nm laser wavelength. We also differentiated between foliar and woody materials using edge detection in the images from projected point clouds and evaluated the density of these regions to support our hypothesis. Density of points, or the number of points divided by the volume of a grid, in a 3D grid size of 0.1 m, was calculated for each of the voxels. The grid size was determined by investigating the size of the branches in the lower portion of the canopy. Subsequently, we fitted a Kernel Density Estimator (KDE) to these values, with the threshold set based on half of the area under the curve in each of the density distributions. All the grids with a density below the threshold were labeled as leaves, while those grids above the threshold were identified as non-leaves. Finally, we modeled LAI using the point densities derived from the TLS point clouds and the listed analysis steps. This model resulted in an R 2 value of 0.88. We also estimated the LAI directly from lidar data using the point densities and calculating LAD, which is defined as the total one-sided leaf area per unit volume. LAI can be obtained as the sum of the LAD values in all the voxels. The accuracy of LAI estimation was 90%, with an RMSE value of 0.31, and an average overestimation of 9 % in TLS-derived LAI, when compared to field-measured LAI. Algorithm performance mainly was affected by the vegetation density and complexity of the canopy structures. It is worth noting that, since the LAI values cannot be considered spatially independent throughout all the plots in this site, we performed semivariogram analysis on the field-measured LAI data. This analysis showed that the LAI values can be assumed to be independent in plots that are at least 30 m apart. As a result, we divided the data into six subsets in which the plots were 30 m spaced. The R 2 values for these subsets, based on modeling of the field-measured LAI using leaf point density values, ranged between 0.84–0.96. The results bode well for using this method for efficient, automatic, and accurate/precise estimation of LAI values in complex forest environments, using a low-cost, rapid-scan TLS.
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Koranteng, Christian, Barbara Simons, and David Nyame-Tawiah. "SIMULATION-BASED ANALYSIS OF THE EFFECT OF GREEN ROOFS ON THERMAL PERFORMANCE OF BUILDINGS IN A TROPICAL LANDSCAPE." Journal on Innovation and Sustainability RISUS 12, no. 1 (April 12, 2021): 45–56. http://dx.doi.org/10.23925/2179-3565.2021v12i1p45-56.
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Apart from the ever- increasing population of most tropical urban cities, high ambient temperature, deteriorated comfort conditions, highly polluted environments are but a few of the problems these cities are confronted with. In the long run, increase energy demands both for production and the provision of comfortable spaces becomes necessary even though it’s a very scarce resource. It is widely known that Urban heat island (UHI) can significantly affect building’s thermal performance and as such, this study was conducted to find out how green roof which is a mitigating factor can reduce the thermal discomfort in indoor spaces. By means of dynamic simulation in EnergyPlus software, a numerical comparative analysis between eight scenarios was done in a tropical climate of Ghana, taking into account climatological, thermal, and hydrological variables. Two factors: Leaf Area Index (LAI) and Soil depth were the main determinants of the comparative analysis. From the results, 5 out of the 8 scenarios was seen to all have performed better leading to a 1.5°C temperature reduction. Out of the 5, LAI5/70-150mm and LAI2/500mm suggest that at every point, there could be a reduction in indoor temperature if either LAI is larger or substrate depth is deep. A larger LAI and a deeper depth could also produce a favorable results (LAI5/500mm) though after a certain threshold, their effect weakens. Based on the findings, it is highly recommended that green roofs becomes part of the solution towards the fight against indoor thermal discomfort and not mechanical ventilation which could have a dire consequence on an already scare resource which is energy.
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Iiames, John S., Ellen Cooter, Andrew N. Pilant, and Yang Shao. "Comparison of EPIC-Simulated and MODIS-Derived Leaf Area Index (LAI) across Multiple Spatial Scales." Remote Sensing 12, no. 17 (August 26, 2020): 2764. http://dx.doi.org/10.3390/rs12172764.
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Modeled leaf area index (LAI) in conjunction with satellite-derived LAI data streams may be used to support various regional and local scale air quality models for retrospective and future meteorological assessments. The Environmental Policy Integrated Climate (EPIC) model holds promise for providing LAI within a dynamic range for input into climate and air quality models, improving on current LAI distribution assumptions typical within atmospheric modeling. To assess the potential use of EPIC LAI, we first evaluated the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI product collections 5 and 6 (i.e., Mc5, Mc6) with in situ LAI estimates upscaled at four 1.0 km resolution research sites distributed over the Albemarle-Pamlico Basin in North Carolina and Virginia, USA. We then compared the EPIC modeled 12.0 km resolution LAI to aggregated MODIS LAI (Mc5, Mc6) over a 3 × 3 grid (or 36 km × 36 km) centered over the same four research sites. Upscaled in situ LAI comparison with MODIS LAI showed improvement with the newer collection where the Mc5 overestimate of +2.22 LAI was reduced to +0.97 LAI with the Mc6. On three of the four sites, the EPIC/MODIS LAI comparison at 12.0 km resolution grid showed similar weighted mean LAI differences (LAI 1.29–1.34), with both Mc5 and Mc6 exceeding EPIC LAI across most dates. For all four research sites, both MODIS collections showed a positive bias when compared to EPIC LAI, with Mc6 (LAI = 0.40) aligning closer to EPIC than the Mc5 (LAI = 0.61) counterpart. Despite modest differences between both MODIS collections and EPIC LAI, the overestimation trend suggests the potential for EPIC to be used for future meteorological alternative management applications on a regional or national scale.
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Stip, Emmanuel, and Jean Lachaine. "Real-world effectiveness of long-acting antipsychotic treatments in a nationwide cohort of 3957 patients with schizophrenia, schizoaffective disorder and other diagnoses in Quebec." Therapeutic Advances in Psychopharmacology 8, no. 11 (June 22, 2018): 287–301. http://dx.doi.org/10.1177/2045125318782694.
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Background: Long-acting injectable antipsychotics (LAI-AP) for patients with schizophrenia (SCZ) have saved significant healthcare costs. However, the cost effectiveness of LAI-AP for patients with other mental disorders has yet to be established. The goal of this study was to evaluate the impact of early initiation of LAI-AP medications on healthcare resource utilization (HRU). Drawing on the Quebecois universal healthcare program (RAMQ), we conducted a nationwide prospective cohort study of LAI-AP under real-world conditions. Methods: This study was performed using a representative sample of patients newly treated with LAI-AP ( n = 3957) who were covered by the Québec Health Insurance Plan. The index date was defined as the date of the first prescription for LAI-AP between 1 January 2008 and 31 March 2012. We collected (a) the demographics and patient characteristics; (b) the treatment characteristics index drug, speciality of the principal prescriber, prescriptions of LAI-AP; and (c) HRU and costs. Two comparisons were made between (a) non-SCZ users of LAI-AP and SCZ users of LAI-AP; and (b) patients with SCZ using first-generation antipsychotic LAI-AP (FGA-LAI) and second-generation antipsychotic LAI-AP (SGA-LAI). Results: In the people with SCZ group, 976 patients were on an SGA-LAI, and 1020 patients were on an FGA-LAI; 41.9% of all users were on risperidone LAI-AP during this period and 17.9% were on zuclopenthixol decanoate. The number of hospitalizations was reduced by half. Durations were also significantly reduced. The total healthcare cost savings for all users were C$29,876 per patient/per year. Younger patients tended to receive more SGA-LAI than FGA-LAI: 29% versus 13%. The percentage of general practitioners who prescribe LAI-AP is higher in the FGA-LAI group than in the SGA-LAI group: 19% versus 13%. For psychiatrist prescribers, it is the opposite: 86% (SGA-LAI) versus 79% (FGA-LAI). The concomitant use of oral antipsychotics (OAP) in the year following index date is higher in the FGA-LAI group: 75% versus 43%. The number of hospitalization days was reduced by 31.5 days in the FGA-LAI group and 38.8 days in the SGA-LAI group. Cost savings were of C$31,924 in the FGA-LAI group and of C$39,100 in the SGA-LAI group. Conclusion: The initiation of LAI-AP saved significant costs to the province of Québec compared with the previous year. Initiation of a LAI-AP resulted in lower resource use. Higher medication costs were offset by lower inpatient and outpatient costs.
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Éva Szabó and Péter Pepó. "Relationships between nutrientsupply, genotype and some physiological properties of winter wheat." Acta Agraria Debreceniensis, no. 48 (July 31, 2012): 141–45. http://dx.doi.org/10.34101/actaagrar/48/2469.
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The chlorophyll content (SPAD), leaf area index (LAI) and leaf area duration (LAD) of three winter wheat varieties have been investigated on a chernozem soil. Three winter wheat varieties (GK Öthalom, Pannonikus and Genius) in three different nutrient-supply levels have been involved in our experiment in the crop-year of 2010/2011. The investigated physiological properties have been set against to the yield results. Upon the results of this comparison it has been stated that there is a close relationship between the investigated physiological properties and yield averages. The SPAD-values showed a growing tendency parallel to the growth of the nutrient-supply levels. The varieties have the highest SPAD-values at the nutri ent-level of N120+PK. Compared to the yield averages we have stated that varieties that have higher SPAD-values have realized higher yields as well. Higher nutrient dosages have increased in the leaf area. In case of all the three varieties the highest LAI-values were measured at the flowering stage (23. 05.) in the treatment whit N120+PK. Varieties with higher leaf area have produced higher yields as well. Parallel to the increasing nutrient-supply levels the value of leaf area duration increased as well. We measured the highest LAD-values in the treatment of N120+PK nutrient-level. By the LAD-values it can be stated that more durable and larger leaf area has been produced in the flowering and ripening phenophases, due to the higher nutrient-dosages. Analysing the relationships between the results it can be stated that there is a strong positive relationship between fertilizer treatments and SPAD-, LAI- and LAD-values. The genotype showed a strong positive correlation to SPAD-values. Yield averages showed strong positive correlation to SPAD-, LAI- and LAD-values as well.
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Wang, Ting, Yonghua Qu, Ziqing Xia, Yiping Peng, and Zhenhua Liu. "Multi-Scale Validation of MODIS LAI Products Based on Crop Growth Period." ISPRS International Journal of Geo-Information 8, no. 12 (November 30, 2019): 547. http://dx.doi.org/10.3390/ijgi8120547.
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Leaf area index (LAI) is one of the most important canopy structure parameters utilized in process-based models of climate, hydrology, and biogeochemistry. In order to determine the reliability and applicability of satellite LAI products, it is critical to validate satellite LAI products. Due to surface heterogeneity and scale effects, it is difficult to validate the accuracy of LAI products. In order to improve the spatio-temporal accuracy of satellite LAI products, we propose a new multi-scale LAI product validation method based on a crop growth cycle. In this method, we used the PROSAIL model to derive Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LAI data and Gaofen-1 (GF-1) for the study area. The Empirical Bayes Kriging (EBK) interpolation method was used to perform a spatial multi-scale transformation of Moderate Resolution Imaging Spectroradiometer (MODIS) LAI products, GF-1 LAI data, and ASTER LAI data. Finally, MODIS LAI satellite products were compared with field measured LAI data, GF-1 LAI data, and ASTER LAI data during the growing season of crop field. This study was conducted in the agricultural oasis area of the middle reaches of the Heihe River Basin in northwestern China and the Conghua District of Guangzhou in Guangdong Province. The results suggest that the validation accuracy of the multi-scale MODIS LAI products validated by ASTER LAI data were higher than those of the GF-1 LAI data and the reference field measured LAI data, showing a R2 of 0.758 and relative mean square error (RRMSE) of 28.73% for 15 m ASTER LAI and a R2 of 0.703 and RRMSE of 30.80% for 500 m ASTER LAI, which imply that the 15 m MODIS LAI product generated by the EBK method was more accurate than the 500 m and 8 m products. This study provides a new validation method for satellite remotely sensed products.
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Ueapanjasin, Piyanut, Wiwat Thavornwattanayong, Jadesada Lertsirimunkong, and Kamolpat Chaiyakittisopon. "Cost-Effectiveness Analysis of Long-acting Injectable Once-monthly of Aripiprazole Compared with Long-acting Injectable Once-monthly Paliperidone Palmitate for the Treatment of Stable Schizophrenia Patients in Thailand." Siriraj Medical Journal 75, no. 10 (October 1, 2023): 725–35. http://dx.doi.org/10.33192/smj.v75i10.264770.
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Objective: Long-acting injectable (LAI)-aripiprazole and LAI-paliperidone palmitate are both second-generation antipsychotics that have been introduced to increase drug compliance in patients. These attributes are expected to enhance drug compliance, particularly in stable patients. The previous studies demonstrated that the efficacy of LAI-aripiprazole and LAI-paliperidone palmitate is controversial. Nevertheless, the costs of treatments and adverse events of both LAI-aripiprazole and LAI-paliperidone palmitate are unlikeness. As there had been no previous cost-effectiveness studies comparing the use of LAI-aripiprazole and LAI-paliperidone palmitate in Thailand, this study was carried out to investigate the matter. Materials and Methods: This study analysed the cost-effectiveness of LAI-aripiprazole compared with LAI-paliperidone palmitate in the treatment of stable schizophrenia, by using the Markov model from a societal perspective. Results: The total cost of treatment with LAI-aripiprazole and LAI-paliperidone palmitate was 1,334,919.05 baht and 1,329,818.79 baht, respectively, while the quality-adjusted life years (QALYs) were both 16.35 years. Life-year of the treatment with LAI-aripiprazole and LAI-paliperidone was 24.27 years and 24.25 years, respectively. The cost-effectiveness ratios (CER) of the treatment with LAI-aripiprazole and LAI-paliperidone palmitate were 81,652.85 baht/QALY gained and 81,330.94 baht/QALY gained, respectively. Conclusion: In Thailand, the treatment of stable schizophrenia with LAI-aripiprazole was shown to provide similar benefits to LAI-paliperidone palmitate in terms of QALYs, despite being more costly. Comparatively, LAI-aripiprazole exhibited better clinical efficacy and led to a longer average life expectancy than LAI-paliperidone. Treatment with LAI-aripiprazole may be dominant strategy, especially with a 2% reduction in drug cost. The results could contribute to appropriate decision-making by policymakers.
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Bình, Nguyễn Văn, and Đinh Ngọc Bách. "ƯU THẾ LAI VỀ MỘT SỐ TÍNH TRẠNG CỦA CÁC TỔ HỢP LAI GIỮA 3 GIỐNG THUẦN DUROC, PIÉTRAIN VÀ LANDRACE." TNU Journal of Science and Technology 227, no. 10 (June 24, 2022): 75–81. http://dx.doi.org/10.34238/tnu-jst.4555.
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Mục đích của nghiên cứu này là chọn lọc ra được các tổ hợp đực lai cuối cùng tốt nhất giữa 3 giống trên để phục vụ cho sản suất lợn thương phẩm có năng suất, chất lượng cao. Nghiên cứu được thực hiện trên 1.718 cá thể của 12 tổ hợp lai với các chỉ tiêu nghiên cứu về ưu thế lai của các tính trạng tăng khối lượng/ngày (TKL), dày mỡ lưng (DML), tiêu tốn thức ăn (TTTA) và tỉ lệ nạc (TLN). Kết quả nghiên cứu cho thấy, ưu thế lai có biểu hiện tốt ở tất cả các tổ hợp lai đối với tính trạng TKL và TLN, biến động tương ứng từ 0,06 đến 1,06% và 0,04 đến 2,47%. Các tính trạng DML và TTTA không thấy biểu hiện ưu thế lai. Đối với tính trạng TKL, ưu thế lai tốt nhất ở tổ hợp lai DP (1,06%) và DxDP (0,89%). Đối với tính trạng TLN, ưu thế lai tốt nhất ở tổ hợp lai PD (0,82%) và DP (0,38%). Đối với tính trạng TKL, ưu thế lai tốt nhất ở tổ hợp lai DL (1,00%) và LxDL (0,66%). Đối với tính trạng TLN, ưu thế lai tốt nhất ở tổ hợp lai DL (0,91%) và DxLD (0,71%). Đối với tính trạng TKL, ưu thế lai tốt nhất ở tổ hợp lai PL (0,35%) và PxLP (0,24%). Đối với tính trạng TLN, ưu thế lai tốt nhất ở 3 tổ hợp lai: PL (2,47%); PxLP (1,25%) và LxPL (0,83%). Qua kết quả đánh giá về ưu thế lai, bước đầu đã chọn ra được 06 tổ hợp lai: DP, DxPD, DL, LxDL, PL và PxLP để đưa vào các bước chọn lọc tiếp theo.
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Diebold, J., S. Caulet, and J. Audouin. "Lymphadénopathie angio-immunoblastique (LAI) et lymphome malin T de type LAI." La Revue de Médecine Interne 9, no. 1 (January 1988): 13–14. http://dx.doi.org/10.1016/s0248-8663(88)80034-1.
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Houborg, Rasmus, Matthew F. McCabe, and Feng Gao. "A Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI)." International Journal of Applied Earth Observation and Geoinformation 47 (May 2016): 15–29. http://dx.doi.org/10.1016/j.jag.2015.11.013.
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Awal, M. A., and W. I. Wan Ishak. "Measurement of Oil Palm LAI by Manual and LAI-2000 Method." Asian Journal of Scientific Research 1, no. 1 (December 15, 2007): 49–56. http://dx.doi.org/10.3923/ajsr.2008.49.56.
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Awal, M. A., and W. I. Wan Ishak. "Measurement of Oil Palm LAI by Manual and LAI-2000 Method*." Asian Journal of Scientific Research 3, no. 4 (September 15, 2010): 315–22. http://dx.doi.org/10.3923/ajsr.2010.315.322.
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Cholula, Uriel, Manuel A. Andrade, and Juan K. Q. Solomon. "Leaf Area Index Estimation of Fully and Deficit Irrigated Alfalfa through Canopy Cover and Canopy Height." AgriEngineering 6, no. 3 (July 8, 2024): 2101–14. http://dx.doi.org/10.3390/agriengineering6030123.
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In arid and semiarid regions, crop production has high irrigation water demands due to low precipitation. Efficient irrigation water management strategies can be developed using crop growth models to assess the effect of different irrigation management practices on crop productivity. The leaf area index (LAI) is an important growth parameter used in crop modeling. Measuring LAI requires specialized and expensive equipment not readily available for producers. Canopy cover (CC) and canopy height (CH) measurements, on the other hand, can be obtained with little effort using mobile devices and a ruler, respectively. The objective of this study was to determine the relationships between LAI, CC, and CH for fully and deficit-irrigated alfalfa (Medicago sativa L.). The LAI, CC, and CH measurements were obtained from an experiment conducted at the Valley Road Field Lab in Reno, Nevada, starting in the Fall of 2020. Three irrigation treatments were applied to two alfalfa varieties (Ladak II and Stratica): 100%, 80%, and 60% of full irrigation demands. Biweekly measurements of CC, CH, and LAI were collected during the growing seasons of 2021 and 2022. The dataset was randomly split into training and testing subsets. For the training subset, an exponential model and a simple linear regression (SLR) model were used to determine the individual relationship of CC and CH with LAI, respectively. Also, a multiple linear regression (MLR) model was implemented for the estimation of LAI with CC and CH as its predictors. The exponential model was fitted with a residual standard error (RSE) and coefficient of determination (R2) of 0.97 and 0.86, respectively. A lower performance was obtained for the SLR model (RSE = 1.03, R2 = 0.81). The MLR model (RSE = 0.82, R2 = 0.88) improved the performance achieved by the exponential and SLR models. The results of the testing indicated that the MLR performed better (RSE = 0.82, R2 = 0.88) than the exponential model (RSE = 0.97, R2 = 0.86) and the SLR model (RSE = 1.03, R2 = 0.82) in the estimation of LAI. The relationships obtained can be useful to estimate LAI when CC, CH, or both predictors are available and assist with the validation of data generated by crop growth models.
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Pareek, Akshay, Satyajeet, Khemendra Choudhary, Abhishek, Siddharth Saroha, and Manoj Saini. "Effect of Varieties and Nutrient Treatments on Physiological and Phenological Parameters of Summer Greengram (Vigna radiata L.)." International Journal of Environment and Climate Change 14, no. 4 (May 8, 2024): 852–58. http://dx.doi.org/10.9734/ijecc/2024/v14i44163.
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The present investigation was conducted during the summer season of 2020 at Regional Research Station (Bawal), CCS Haryana Agricultural University, Hisar to study the response of greengran to different varieties and nutrients treatments. The experiment was laid out in split-plot design with four replications. The main plot consisted of varieties (MH-421, MH-318 and SML-668) and sub-plot consisted of nutrient treatments (Control, 100% recommended dose of fertilizer (RDF), 75% RDF + 25% FYM + Rhizobium + phosphate solubilizing bacteria (PSB), 50% RDF + 50% FYM + Rhizobium + PSB). The findings suggest that variety MH-318 gave significantly higher no. of branches, leaf area, leaf area index (LAI) and leaf area duration (LAD) as well as phenological traits such as days taken to 50% flowering (days) over SML-668 and MH-421. Among the nutrient treatments, application of 75% RDF + 25% FYM + Rhizobium + PSB demonstrated superior performance across physiological (no. of branches, leaf area, LAI and LAD) and phenological traits (50% flowering) over 100% RDF, 50% RDF + 50% FYM + Rhizobium + PSB and control. Thus, a combination of variety MH-318 with 75% RDF + 25% FYM + Rhizobium + PSB helps in enhancing the physiological and phenological parameters of greengram without negative influence on plant and the environment.
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Xavier, Alexandre Cândido, and Carlos Alberto Vettorazzi. "Monitoring leaf area index at watershed level through NDVI from Landsat-7/ETM+ data." Scientia Agricola 61, no. 3 (June 2004): 243–52. http://dx.doi.org/10.1590/s0103-90162004000300001.
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Leaf area index (LAI) is an important parameter of the vegetation canopy, and is used, for instance, to estimate evapotranspiration, an important component of the hydrological cycle. This work analyzed the relationship between LAI, measured in field, and NDVI from four dates (derived from Landsat-7/ETM+ data), and with such vegetation index, to generate and analyze LAI maps of the study area for the diverse dates. LAI data were collected monthly in the field with LAI-2000 equipment in stands of sugar cane, pasture, corn, eucalypt, and riparian forest. The relationships between LAI and NDVI were adjusted by a potential model; 57% to 72% of the NDVI variance were explained by the LAI. LAI maps generated by empirical relationships between LAI and NDVI showed reasonable precision (standard error of LAI estimate ranged from 0.42 to 0.87 m² m-2). The mean LAI value of each monthly LAI map was shown to be related to the total precipitation in the three previous months.
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Probo, M., V. Dalo’, F. Facchini, M. Rudoni, V. Preziosi, and D. Nano. "Long-acting injectable antipsychotics and global functioning in north western italian public health service." European Psychiatry 41, S1 (April 2017): S605—S606. http://dx.doi.org/10.1016/j.eurpsy.2017.01.951.
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IntroductionLong-acting injectable antipsychotics (LAI-APs) should be the first choice therapy in the treatment of schizophrenia, however their use in outpatient's psychiatric services remains limited.ObjectiveObservational study in schizophrenic patients of the northwestern public health service.AimTo assess demographic and psychopathological features in patients treated with LAI haloperidol (H-LAI) and second-generation LAI antipsychotics (SG-LAI).MethodsWe recruited 105 schizophrenic patients upon LAI-APs treatment, and we assessed socio-demographic data, medical comorbidity, substances use, time from admission, treatment length, and per os augmentation therapies. All participants were assessed for global functioning and severity of illness by CGI-SCH and PSP, respectively.ResultsOf all patients, 52% were treated by H-LAI, 48% by SG-LAI. No statistical differences (P > 0.05) were found between the 2 groups for age, gender, other demographic variables, substances use, somatic comorbidities. Both groups were homogeneous for severity of illness (CGI-SCH score = 4.20 in H-LAI vs. 4.38 in SG-LAI) and global functioning (PSP score = 49.1 in H-LAI vs. 54.4 in SG-LAI). Compared with the H-LAI group, SG-LAI-treated patients were characterized by shorter time from admission (>10 yrs) and treatment length (>1 yr), and less frequent anticholinergic drug co-prescription. We counted only 6 LAI-APs treatments started in the last year.ConclusionsDespite of the literature support, LAI-APs treatment for schizophrenia is still limited in our service. Our data suggest that SG-LAI-APs are used as first choice of LAI-APs treatment, although maintained for short time, while H-LAI are reserved to long-standing patients and are burdened by side effects needing anticholinergic treatment.Disclosure of interestThe authors have not supplied their declaration of competing interest.
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Kodar, Ave, Mait Lang, Tauri Arumäe, Alo Eenmäe, Jan Pisek, and Tiit Nilson. "Metsa lehepinnaindeksi kaardistamine lennukilidari, satelliidipiltide ja maapealsete mõõtmiste abil Järvselja VALERI testalal / Leaf area index mapping with airborne lidar, satellite images and ground measurements in Järvselja VALERI test site." Forestry Studies 55, no. 1 (December 1, 2011): 11–32. http://dx.doi.org/10.2478/v10132-011-0099-1.
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Abstract The aim of this study was to compile the leaf area index (LAI) map of a 3×3 km VALERI test site in Järvselja, Estonia. Canopy transmittance measurements of LAI by LAI-2000 Plant Canopy Analyzers and digital cameras supplied with fisheye converters were carried out on 42 elementary sampling units at ground level and at breast height level. The vegetation LAI was estimated as a sum of the tree canopy true green LAI obtained from the inversion of canopy gap fraction data and of the ground vegetation effective LAI. Red channel from SPOT-4 HRV-IR image and airborne lidar data based canopy transmittance were used for up-scaling. The LAI map was compared with standard LAI products from Terra MODIS and ENVISAT MERIS. We found that lidar data based LAI estimate on up-scaled map saturated at high values (LAI > 4.5) compared to the LAI estimates based on SPOT-4 HRV-IR red channel. Validation of MODIS LAI product revealed substantial underestimates of LAI compared to the up-scaled field measurements and rather large random noise. ENVISAT MERIS LAI product was more similar to up-scaled field measurements; however, rather large unexpected random variations exist in its time series.
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Qiao, Kun, Wenquan Zhu, Zhiying Xie, and Peixian Li. "Estimating the Seasonal Dynamics of the Leaf Area Index Using Piecewise LAI-VI Relationships Based on Phenophases." Remote Sensing 11, no. 6 (March 22, 2019): 689. http://dx.doi.org/10.3390/rs11060689.
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The leaf area index (LAI) is not only an important parameter used to describe the geometry of vegetation canopy but also a key input variable for ecological models. One of the most commonly used methods for LAI estimation is to establish an empirical relationship between the LAI and the vegetation index (VI). However, the LAI-VI relationships had high seasonal variability, and they differed among phenophases and VIs. In this study, the LAI-VI relationships in different phenophases and for different VIs (i.e., the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and near-infrared reflectance of vegetation (NIRv)) were investigated based on 82 site-years of LAI observed data and the Moderate Resolution Imaging Spectroradiometer (MODIS) VI products. Significant LAI-VI relationships were observed during the vegetation growing and declining periods. There were weak LAI-VI relationships (p > 0.05) during the flourishing period. The accuracies for the LAIs estimated with the piecewise LAI-VI relationships based on different phenophases were significantly higher than those estimated based on a single LAI-VI relationship for the entire vegetation active period. The average root mean square error (RMSE) ± standard deviation (SD) value for the LAIs estimated with the piecewise LAI-VI relationships was 0.38 ± 0.13 (based on the NDVI), 0.41 ± 0.13 (based on the EVI) and 0.41 ± 0.14 (based on the NIRv), respectively. In comparison, it was 0.46 ± 0.13 (based on the NDVI), 0.55 ± 0.15 (based on the EVI) and 0.55 ± 0.15 (based on the NIRv) for those estimated with a single LAI-VI relationship. The performance of the three VIs in estimating the LAI also varied among phenophases. During the growing period, the mean RMSE ± SD value for the estimated LAIs was 0.30 ± 0.11 (LAI-NDVI relationships), 0.37 ± 0.11 (LAI-EVI relationships) and 0.36 ± 0.13 (LAI-NIRv relationships), respectively, indicating the NDVI produced significantly better LAI estimations than those from the other two VIs. In contrast, the EVI produced slightly better LAI estimations than those from the other two VIs during the declining period (p > 0.05), and the mean RMSE ± SD value for the estimated LAIs was 0.45 ± 0.16 (LAI-NDVI relationships), 0.43 ± 0.23 (LAI-EVI relationships) and 0.45 ± 0.25 (LAI-NIRv relationships), respectively. Hence, the piecewise LAI-VI relationships based on different phenophases were recommended for the estimations of the LAI instead of a single LAI-VI relationship for the entire vegetation active period. Furthermore, the optimal VI in each phenophase should be selected for the estimations of the LAI according to the characteristics of vegetation growth.
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Zhang, Xuezhen, and Qiuhong Tang. "Response of Simulated Surface Air Temperature to the Interannual Variability of Leaf Area Index in Eastern China." Advances in Meteorology 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/817870.
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Using the coupled WRF-Noah model, we conducted two experiments to investigate impacts of the interannual variability of leaf area index (LAI) on the surface air temperature (SAT) in eastern China. The Moderate Resolution Imaging Spectroradiometer (MODIS) observed dynamic LAI data from 2002 to 2009 were used in one modeling experiment, and the climatological seasonal cycle of the MODIS LAI was used in the other experiment. The results show that the use of dynamic LAI improves model performance. Compared with the use of climatological LAI, the use of dynamic LAI may reduce the warm (cool) bias in the years with large positive (negative) LAI anomalies. The reduction of the warm bias results from the modeled cooling effect of LAI increase through reducing canopy resistance, promoting transpiration, and decreasing sensible heat flux. Conversely, the reduction of cool bias is a result of the warming effect of negative anomaly of LAI. The use of dynamic LAI can improve model performance in summer and to a lesser extent, spring and autumn. Moreover, the dynamic LAI exerts a detectable influence on SAT in the WRF model when the LAI anomaly is at least 20% of the climatological LAI.
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Smith, N. J., J. M. Chen, and T. A. Black. "Effects of clumping on estimates of stand leaf area index using the LI-COR LAI-2000." Canadian Journal of Forest Research 23, no. 9 (September 1, 1993): 1940–43. http://dx.doi.org/10.1139/x93-244.
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Eighteen natural second-growth stands of Douglas-fir (Pseudotsugamenziesii (Mirb.) Franco) from a wide range of stand densities and stocking levels were measured for stand leaf area index (LAI) from allometric relationships (direct LAI) and the LI-COR LAI-2000 plant canopy analyzer (indirect LAI). LAI was based on one-half total leaf area (m2) per square metre of ground surface area, normal to any slope. The LAI-2000 underestimated direct LAI by 62%. The underestimate of LAI was due to the confinement of needles within branches (74%) and nonrandom branch distribution (26%). In effect, the branches behaved like big leaves. The LAI-2000 can be used to estimate LAI across a variety of stand density and stocking levels by using a single stand clumping factor of 2.63.
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Bình, Nguyễn Văn, and Đinh Ngọc Bách. "SỰ BIẾN ĐỘNG VỀ ƯU THẾ LAI CỦA CÁC TỔ HỢP LAI KHÁC NHAU GIỮA 3 GIỐNG LỢN DUROC, PIÉTRAIN, LANDRACE." TNU Journal of Science and Technology 227, no. 14 (August 23, 2022): 42–47. http://dx.doi.org/10.34238/tnu-jst.6212.
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Nghiên cứu các yếu tố ảnh hưởng tới sức sản xuất của con giống là rất quan trọng để đề xuất các giải pháp nâng cao sức sản xuất của chúng. Mục đích của nghiên cứu này là phân tích sự biến động của ưu thế lai về một số tính trạng sản xuất của các tổ hợp lai giữa 3 giống lợn Duroc, Piétrain, Landrace để chọn ra các tổ hợp lai tốt nhất đưa vào sản xuất. Nghiên cứu được thực hiện trên 767 cá thể của 3 giống Duroc, Piétrain, Landrace và 528 cá thể của 04 tổ hợp lai giữa chúng với công thức lai khác nhau. Các tính trạng nghiên cứu là: Tăng khối lượng, dày mỡ lưng, tiêu tốn thức ăn, tỉ lệ nạc. Kết quả nghiên cứu cho thấy: Ưu thế lai tốt nhất ở tổ hợp lai F1 – lai thuận giữa các cặp Duroc x Piétrain, Duroc x Landrace và Piétrain x Landrace về cả 4 tính trạng. Đặc biệt, ưu thế lai về tăng khối lượng cao nhất ở tổ hợp lai Duroc x Piétrain (1,06%), thấp nhất ở tổ hợp lai Piétrain x Landrace (0,35%); Nhưng ưu thế lai về tỷ lệ nạc lại cao nhất ở tổ hợp lai Piétrain x Landrace (2,47%) và thấp nhất ở tổ hợp lai Duroc x Piétrain (0,38%); Các tính trạng tăng khối lượng và tỷ lệ nạc có ưu thế lai >0, trái lại các tính trạng dày mỡ lưng và tiêu tốn thức ăn có ưu thế lai <0. Đây là lợi điểm quan trọng trong lai tạo để tạo ra các giống lợn sinh trưởng tốt, tỷ lệ nạc cao nhưng lại tiêu tốn thức ăn thấp.
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Luo, Xin, Lili Jin, Xin Tian, Shuxin Chen, and Haiyi Wang. "A High Spatiotemporal Enhancement Method of Forest Vegetation Leaf Area Index Based on Landsat8 OLI and GF-1 WFV Data." Remote Sensing 15, no. 11 (May 29, 2023): 2812. http://dx.doi.org/10.3390/rs15112812.
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The leaf area index (LAI) is a crucial parameter for analyzing terrestrial ecosystem carbon cycles and global climate change. Obtaining high spatiotemporal resolution forest stand vegetation LAI products over large areas is essential for an accurate understanding of forest ecosystems. This study takes the northwestern part of the Inner Mongolia Autonomous Region (the northern section of the Greater Khingan Mountains) in northern China as the research area. It also generates the LAI time series product of the 8-day and 30 m forest stand vegetation growth period from 2013 to 2017 (from the 121st to the 305th day of each year). The Simulated Annealing-Back Propagation Neural Network (SA-BPNN) model was used to estimate LAI from Landsat8 OLI, and the multi-period GaoFen-1 WideField-View satellite images (GF-1 WFV) and the spatiotemporal adaptive reflectance fusion mode (STARFM) was used to predict high spatiotemporal resolution LAI by combining inversion LAI and Global LAnd Surface Satellite-derived vegetation LAI (GLASS LAI) products. The results showed the following: (1) The SA-BPNN estimation model has relatively high accuracy, with R2 = 0.75 and RMSE = 0.38 for the 2013 LAI estimation model, and R2 = 0.74 and RMSE = 0.17 for the 2016 LAI estimation model. (2) The fused 30 m LAI product has a good correlation with the LAI verification of the measured sample site (R2 = 0.8775) and a high similarity with the GLASS LAI product. (3) The fused 30 m LAI product has a high similarity with the GLASS LAI product, and compared with the GLASS LAI interannual trend line, it accords with the growth trend of plants in the seasons. This study provides a theoretical and technical reference for forest stand vegetation growth period LAI spatiotemporal fusion research based on high-score data, and has an important role in exploring vegetation primary productivity and carbon cycle changes in the future.
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Törnros, Tobias, and Lucas Menzel. "Leaf area index as a function of precipitation within a hydrological model." Hydrology Research 45, no. 4-5 (September 12, 2013): 660–72. http://dx.doi.org/10.2166/nh.2013.143.
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The Leaf Area Index (LAI) was derived from the Normalised Difference Vegetation Index (NDVI) obtained from Advanced Very High Resolution Radiometer (AVHRR) data for the years 1982–2004. The NDVI-derived LAI showed a very good agreement (correlation coefficient r up to 0.96) with MODIS LAI. To address the relation between precipitation and LAI, linear correlation analysis between gridded precipitation and the NDVI-derived LAI was conducted for several land uses and each month of the year. Based on the regression coefficients, LAI could be simulated as a function of precipitation. During validation, the simulated LAI showed a very good agreement (r ≥ 0.75) with the NDVI-derived LAI. The simulated dynamic LAI was thereafter implemented in a hydrological model. For comparison, a model run with a static LAI without any inter-annual variations was also conducted. During abnormally dry conditions, the dynamic LAI was lower than the static LAI and less transpiration was therefore simulated. It is shown that a dynamic LAI contributes to a more realistic simulation approach during individual weather events but also that in the long run the simulated transpiration is much more strongly influenced by inter-annual variations in weather than by the additional vegetation dynamics in a semi-arid region.
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He, Yuhong, Xulin Guo, and John F. Wilmshurst. "Comparison of different methods for measuring leaf area index in a mixed grassland." Canadian Journal of Plant Science 87, no. 4 (October 1, 2007): 803–13. http://dx.doi.org/10.4141/cjps07024.
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Available LAI instruments have greatly increased our ability to estimate leaf area index (LAI) non-destructively. However, it is difficult to infer from existing studies which instrument has the advantages in measuring LAI over other instruments for grassland ecosystems. The objective of our study was to compare the LAI estimates by two instruments (AccuPAR, and LAI2000), and correlate the LAI measurements to remote sensing data for a mixed grassland. Leaf area index of four grass communities was measured by both the destructive method and instruments. Ground canopy reflectance was measured and further calculated to be LAI-related vegetation indices. Statistical analysis showed that destructively sampled LAI ranged from 0.61 to 5.7 in the study area. Both instruments underestimated LAI in comparison with the destructive method. However, the LAI2000 is better than AccuPAR for estimating LAI. Comparison of four grass communities indicated that the lower the grass LAI, the greater the underestimated percentage of LAI values collected by both instruments. The adjusted transformed soil-adjusted vegetation index (ATSAVI), was the best LAI estimator in the mixed grassland. Key words: Leaf area index, sward structure, nondestructive vegetation sampling, hyperspectral remote sensing, mixed grass prairie
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Goeking, Sara A., and David G. Tarboton. "Spatially Distributed Overstory and Understory Leaf Area Index Estimated from Forest Inventory Data." Water 14, no. 15 (August 4, 2022): 2414. http://dx.doi.org/10.3390/w14152414.
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Forest change affects the relative magnitudes of hydrologic fluxes such as evapotranspiration (ET) and streamflow. However, much is unknown about the sensitivity of streamflow response to forest disturbance and recovery. Several physically based models recognize the different influences that overstory versus understory canopies exert on hydrologic processes, yet most input datasets consist of total leaf area index (LAI) rather than individual canopy strata. Here, we developed stratum-specific LAI datasets with the intent of improving the representation of vegetation for ecohydrologic modeling. We applied three pre-existing methods for estimating overstory LAI, and one new method for estimating both overstory and understory LAI, to measurements collected from a probability-based plot network established by the US Forest Service’s Forest Inventory and Analysis (FIA) program, for a modeling domain in Montana, MT, USA. We then combined plot-level LAI estimates with spatial datasets (i.e., biophysical and remote sensing predictors) in a machine learning algorithm (random forests) to produce annual gridded LAI datasets. Methods that estimate only overstory LAI tended to underestimate LAI relative to Landsat-based LAI (mean bias error ≥ 0.83), while the method that estimated both overstory and understory layers was most strongly correlated with Landsat-based LAI (r2 = 0.80 for total LAI, with mean bias error of -0.99). During 1984-2019, interannual variability of understory LAI exceeded that for overstory LAI; this variability may affect partitioning of precipitation to ET vs. runoff at annual timescales. We anticipate that distinguishing overstory and understory components of LAI will improve the ability of LAI-based models to simulate how forest change influences hydrologic processes.
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Yang, Zhu, Xuanrui Huang, Yunxian Qing, Hongqian Li, Libin Hong, and Wei Lu. "Estimation of Time-Series Forest Leaf Area Index (LAI) Based on Sentinel-2 and MODIS." Applied Sciences 13, no. 15 (July 29, 2023): 8777. http://dx.doi.org/10.3390/app13158777.
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The LAI is a key parameter used to describe the exchange of material and energy between soil, vegetation and the atmosphere. It has become an important driving datum in the study of carbon and water cycle mechanism models at many regional scales. In order to obtain high temporal resolution and high spatial resolution LAI products, this study proposed a method to combine the high temporal resolution of MODIS LAI products with the high spatial resolution of Sentinel-2 data. The method first used the LACC algorithm to smooth the LAI time-series data and extracted the normalized growth curve of the MODIS LAI of forest and used this curve to simulate the annual variation of the LAI. Secondly, it estimated the LAI at the period of full leaf spread based on the traditional remote sensing statistical model and Sentinel-2 remote sensing data as the maximum value of the forest LAI in the study area and used it to control the LAI growth curve. Finally, the time-series LAI data set was created by multiplying the maximum LAI by the normalized forest LAI growth curve. The results indicate that: (1) the remote sensing statistical estimation model of LAI was developed using the atmospherically resistant vegetation index ARVI (R2 = 0.494); (2) the MODIS LAI normalized growth curve keeps a good level of agreement with the actual variation. This study provides a simple and efficient method for obtaining effective time-series forest LAI data for the scope of small- and medium-sized areas.
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Islam, Saiful, and Nargis Jahan. "Growth Analysis of Chickpea var. Bari Chola-7 Following Application of TIBA (2, 3, 5- Triiodobenzoic Acid)." Journal of Bangladesh Academy of Sciences 40, no. 2 (December 22, 2016): 199–205. http://dx.doi.org/10.3329/jbas.v40i2.30775.
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An investigation was made to see the effect of different concentrations (10, 20, 30 and 40 ppm) of 2, 3, 5- triiodobenzoic acid (TIBA) on leaf area index (LAI), leaf area duration (LAD), crop growth rate (CGR), relative growth rate (RGR) and net assimilation rate (NAR) of a cultivar of chickpea (Cicer arietinum L.) grown during rabi season of 2015 - 2016. Results revealed that LAI and LAD showed a positive response from flowering stage to maturity (66 - 110 DAS) due to 30 ppm TIBA application with maximum LAI and LAD occurring at the flowering stage. At 66 - 83 and 83 - 97 DAS, CGR was highest with the application of 30 ppm TIBA, while RGR was highest due to 10 ppm TIBA. Peak CGR was recorded at the time of pod setting to pod filling stage (8 - 97) and increased over control by 29.64%. Irrespective of the treatments, NAR was recorded maximum during flowering stage to pod setting (66 - 83 DAS) and thereafter decreased till maturity. At 66 - 83 and 83 - 97 DAS, maximum NAR values were recorded due to 30 ppm TIBA and the increases were 9.09 and 32.69% higher over the control, respectively.Journal of Bangladesh Academy of Sciences, Vol. 40, No. 2, 199-205, 2016
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Tanioka, Yosuke, Yihan Cai, Hideyuki Ida, and Mitsuru Hirota. "A Spatial Relationship between Canopy and Understory Leaf Area Index in an Old-Growth Cool-Temperate Deciduous Forest." Forests 11, no. 10 (September 25, 2020): 1037. http://dx.doi.org/10.3390/f11101037.
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Quantification of leaf area index (LAI) is essential for understanding forest productivity and the atmosphere–vegetation interface, where the majority of gas and energy exchange occurs. LAI is one of the most difficult plant variables to adequately quantify, owing to large spatial and temporal variability, and few studies have examined the horizontal and vertical distribution of LAI in forest ecosystems. In this study, we demonstrated the LAI distribution in each layer from the understory to canopy using multiple-point measurements (121 points) and examined the relationships among layers in a cool-temperate deciduous forest. LAI at each point, and the spatial distribution of LAI in each layer, varied within the forest. The spatial distribution of LAI in the upper layer was more heterogeneous than that of LAI at the scale of the entire forest. Significant negative correlations were observed between the upper- and lower-layer LAI. Our results indicate that the understory compensates for gaps in LAI in the upper layer; thus, the LAI of the entire forest tends to remain spatially homogeneous even in a mature forest ecosystem.
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Jin, Huaan, Weixing Xu, Ainong Li, Xinyao Xie, Zhengjian Zhang, and Haoming Xia. "Spatially and Temporally Continuous Leaf Area Index Mapping for Crops through Assimilation of Multi-resolution Satellite Data." Remote Sensing 11, no. 21 (October 28, 2019): 2517. http://dx.doi.org/10.3390/rs11212517.
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As a key parameter that represents the structural characteristics and biophysical changes of crop canopy, the leaf area index (LAI) plays a significant role in monitoring crop growth and mapping yield. A considerable amount of farmland is dispersed with strong spatial heterogeneity. The existing time series satellite LAI products fail to capture spatial distributions and growth changes of crops due to coarse spatial resolutions and spatio-temporal discontinuities. Therefore, it becomes crucial for fine resolution LAI mapping in time series over crop areas. A two-stage data assimilation scheme was developed for dense time series LAI mapping in this study. A LAI dynamic model was first constructed using multi-year MODIS LAI data. This model coupled with the PROSAIL radiative transfer model, and MOD09A1 reflectance data were used to retrieve temporal LAI profiles at the 500 m resolution with the assistance of the very fast simulated annealing (VFSA) algorithm. Then, the LAI dynamics at the 500 m scale were incorporated as prior information into the Landsat 8 OLI reflectance data for time series LAI mapping at the 30 m resolution. Finally, the spatio-temporal continuities and retrieval accuracies of assimilated LAI values were assessed at the 500 m and 30 m resolutions respectively, using the MODIS LAI product, fine resolution LAI reference map and field measurements. The results indicated that the assimilated the LAI estimations at the 500 m scale effectively eliminated the spatio-temporal discontinuities of the MODIS LAI product and displayed reasonable temporal profiles and spatial integrity of LAI. Moreover, the 30 m resolution LAI retrievals showed more abundant spatial details and reasonable temporal profiles than the counterparts at the 500 m scale. The determination coefficient R2 between the estimated and field LAI values was 0.76 with a root mean square error (RMSE) value of 0.71 at the 30 m scale. The developed method not only improves the spatio-temporal continuities of the LAI at the 500 m scale, but also obtains 30 m resolution LAI maps with fine spatial and temporal consistencies, which can be expected to meet the needs of analysis on crop dynamic changes and yield mapping in fragmented and highly heterogeneous areas.