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Journal articles on the topic 'Leaf area index'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

CURRAN, P. J., and N. W. WARDLEY. "Radiometric leaf area index." International Journal of Remote Sensing 9, no. 2 (1988): 259–74. http://dx.doi.org/10.1080/01431168808954850.

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2

Balakrishnan, K., N. Natarajaratnam, and C. Rajendran. "Critical Leaf Area Index in Pigeonpea." Journal of Agronomy and Crop Science 159, no. 3 (1987): 164–66. http://dx.doi.org/10.1111/j.1439-037x.1987.tb00081.x.

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3

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 (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 quantifyi

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4

Zhang, Hu, Jing Li, Qinhuo Liu, et al. "Estimating Leaf Area Index with Dynamic Leaf Optical Properties." Remote Sensing 13, no. 23 (2021): 4898. http://dx.doi.org/10.3390/rs13234898.

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Leaf area index (LAI) plays an important role in models of climate, hydrology, and ecosystem productivity. The physical model-based inversion method is a practical approach for large-scale LAI inversion. However, the ill-posed inversion problem, due to the limited constraint of inaccurate input parameters, is the dominant source of inversion errors. For instance, variables related to leaf optical properties are always set as constants or have large ranges, instead of the actual leaf reflectance of pixel vegetation in the current model-based inversions. This paper proposes to estimate LAI with

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5

Pierce, Lars L., Steven W. Running, and Joe Walker. "Regional-Scale Relationships of Leaf Area Index to Specific Leaf Area and Leaf Nitrogen Content." Ecological Applications 4, no. 2 (1994): 313–21. http://dx.doi.org/10.2307/1941936.

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6

Anderson, Martha C. "Simple method for retrieving leaf area index from Landsat using MODIS leaf area index products as reference." Journal of Applied Remote Sensing 6, no. 1 (2012): 063554. http://dx.doi.org/10.1117/1.jrs.6.063554.

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7

Antognozzi, E., A. Tombesi, and A. Palliotti. "RELATIONSHIP BETWEEN LEAF AREA, LEAF AREA INDEX AND FRUITING IN KIWIFRUIT (ACTINDIA DELICIOSA)." Acta Horticulturae, no. 297 (April 1992): 435–42. http://dx.doi.org/10.17660/actahortic.1992.297.57.

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8

Borghetti, M., G. G. Vendramin, and R. Giannini. "Specific leaf area and leaf area index distribution in a young Douglas-fir plantation." Canadian Journal of Forest Research 16, no. 6 (1986): 1283–88. http://dx.doi.org/10.1139/x86-227.

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The spatial distribution of specific leaf area and leaf area index of needles in different age classes has been investigated in a young and unthinned Douglas-fir (Pseudotsugamenziesii (Mirb.) Franco) plantation in Central Italy through the destructive analysis of 12 trees sampled in four diameter size classes. Specific leaf area decreased with leaf age and from crown base to apex. A clear interaction between the effects of age and position on specific leaf area was demonstrated. For the whole canopy the vertical distribution of leaf area was well fitted by a normal curve equation, which explai

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9

Hirose, T., D. D. Ackerly, M. B. Traw, D. Ramseier, and F. A. Bazzaz. "CO2ELEVATION, CANOPY PHOTOSYNTHESIS, ANDOPTIMAL LEAF AREA INDEX." Ecology 78, no. 8 (1997): 2339–50. http://dx.doi.org/10.1890/0012-9658(1997)078[2339:cecpal]2.0.co;2.

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10

Price, J. C. "Estimating leaf area index from satellite data." IEEE Transactions on Geoscience and Remote Sensing 31, no. 3 (1993): 727–34. http://dx.doi.org/10.1109/36.225538.

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11

Abuelgasim, Abdelgadir A., and Sylvain G. Leblanc. "Leaf area index mapping in northern Canada." International Journal of Remote Sensing 32, no. 18 (2011): 5059–76. http://dx.doi.org/10.1080/01431161.2010.494636.

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12

Smith, N. J., and D. R. Clark. "Estimating salal leaf area index and leaf biomass from diffuse light attenuation." Canadian Journal of Forest Research 20, no. 9 (1990): 1265–70. http://dx.doi.org/10.1139/x90-168.

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Salal (Gaultheriashallon Pursh) leaf area index and leaf biomass were estimated from 37 quadrat samples in 13 stands dominated by Douglas-fir (Pseudotsugamenziesii (Mirb.) Franco) on eastern Vancouver Island, British Columbia. Leaf area index and biomass were predicted from a Beer's Law light attenuation model using diffuse photosynthetically active radiation (400–700 nm wavelength). The extinction coefficients, determined using reduced major axis maximum likelihood, were 0.8055 m2/m2 for leaf area index and 0.0069 g/m2 for leaf biomass. Salal leaf area index and biomass were then predicted fo

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13

Caldararu, S., P. I. Palmer, and D. W. Purves. "Inferring Amazon leaf demography from satellite observations of leaf area index." Biogeosciences Discussions 8, no. 5 (2011): 10389–421. http://dx.doi.org/10.5194/bgd-8-10389-2011.

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Abstract. Seasonal and year-to-year variations in leaf cover imprint significant spatial and temporal variability on biogeochemical cycles, and affect land-surface properties related to climate. We develop a demographic model of leaf phenology based on the hypothesis that trees seek an optimal Leaf Area Index (LAI) as a function of available light and soil water, and fitted it to spaceborne observations of LAI over the Amazon Basin, 2001–2005. We find the model reproduces the spatial and temporal LAI distribution whilst also predicting geographic variation in leaf age from the basin center (2.

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14

Caldararu, S., P. I. Palmer, and D. W. Purves. "Inferring Amazon leaf demography from satellite observations of leaf area index." Biogeosciences 9, no. 4 (2012): 1389–404. http://dx.doi.org/10.5194/bg-9-1389-2012.

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Abstract. Seasonal and year-to-year variations in leaf cover imprint significant spatial and temporal variability on biogeochemical cycles, and affect land-surface properties related to climate. We develop a demographic model of leaf phenology based on the hypothesis that trees seek an optimal leaf area index (LAI) as a function of available light and soil water, and fit it to spaceborne observations of LAI over the Amazon basin, 2001–2005. We find the model reproduces the spatial and temporal LAI distribution whilst also predicting geographic variation in leaf age from the basin centre (2.1 ±

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15

Nel, Elizabeth M., and Carol A. Wessman. "Canopy transmittance models for estimating forest leaf area index." Canadian Journal of Forest Research 23, no. 12 (1993): 2579–86. http://dx.doi.org/10.1139/x93-319.

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Leaf area index was estimated in old-growth and young post-fire coniferous forests in northwestern Colorado. A line quantum sensor was used to measure canopy transmittance at different solar zenith angles. Leaf area indices were estimated from canopy transmittance data according to three different models and were subsequently compared with leaf area indices derived from existing allometric equations. Of the three canopy transmittance methods evaluated, a Beer–Lambert model adjusted for diffuse light and solar zenith angle was in closest agreement with allometric leaf area index estimates (11.5

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16

Firman, D. M., and E. J. Allen. "Estimating individual leaf area of potato from leaf length." Journal of Agricultural Science 112, no. 3 (1989): 425–26. http://dx.doi.org/10.1017/s0021859600085889.

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Measurements of the area of individual leaves in crops are useful in the analysis of canopy architecture as they allow determination of the structure of leaf area index in a vertical profile. This information may be of use in modelling leaf growth and the assessment of photosynthetic potential of different strata of the canopy with ontogeny (cf. Firman & Allen, 1988).

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17

Xiao, Chun-Wang, I. A. Janssens, J. Curiel Yuste, and R. Ceulemans. "Variation of specific leaf area and upscaling to leaf area index in mature Scots pine." Trees 20, no. 3 (2006): 304–10. http://dx.doi.org/10.1007/s00468-005-0039-x.

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18

Chen, Wei, and Chunxiang Cao. "Topographic correction-based retrieval of leaf area index in mountain areas." Journal of Mountain Science 9, no. 2 (2012): 166–74. http://dx.doi.org/10.1007/s11629-012-2248-2.

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19

Doring, J., M. Stoll, R. Kauer, M. Frisch, and S. Tittmann. "Indirect Estimation of Leaf Area Index in VSP-Trained Grapevines Using Plant Area Index." American Journal of Enology and Viticulture 65, no. 1 (2013): 153–58. http://dx.doi.org/10.5344/ajev.2013.13073.

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20

Heitholt, J. J., and W. R. Meredith. "Yield, Flowering, and Leaf Area Index of Okra‐Leaf and Normal‐Leaf Cotton Isolines." Crop Science 38, no. 3 (1998): 643–48. http://dx.doi.org/10.2135/cropsci1998.0011183x003800030003x.

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21

Hardin, Perry J., and Ryan R. Jensen. "Neural Network Estimation of Urban Leaf Area Index." GIScience & Remote Sensing 42, no. 3 (2005): 251–74. http://dx.doi.org/10.2747/1548-1603.42.3.251.

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22

Neinavaz, Elnaz, Andrew K. Skidmore, Roshanak Darvishzadeh, and Thomas A. Groen. "LEAF AREA INDEX RETRIEVED FROM THERMAL HYPERSPECTRAL DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 20, 2016): 99–105. http://dx.doi.org/10.5194/isprs-archives-xli-b7-99-2016.

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Leaf area index (LAI) is an important essential biodiversity variable due to its role in many terrestrial ecosystem processes such as evapotranspiration, energy balance, and gas exchanges as well as plant growth potential. A novel approach presented here is the retrieval of LAI using thermal infrared (8–14 μm, TIR) measurements. Here, we evaluate LAI retrieval using TIR hyperspectral data. Canopy emissivity spectral measurements were recorded under controlled laboratory conditions using a MIDAC (M4401-F) illuminator Fourier Transform Infrared spectrometer for two plant species during which LAI

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23

Kiniry, Jim, Mari-Vaughn Johnson, Robert Mitchell, et al. "Switchgrass Leaf Area Index and Light Extinction Coefficients." Agronomy Journal 103, no. 1 (2011): 119–22. http://dx.doi.org/10.2134/agronj2010.0280.

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24

Kuusk, Andres, Mait Lang, Ave Kodar, and Allan Sims. "Estimation of Leaf Area Index of Hemiboreal Forests." Open Remote Sensing Journal 6, no. 1 (2015): 1–10. http://dx.doi.org/10.2174/1875413901506010001.

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25

ZHANG Zhengyang, 张正杨, 马新明 MA Xinming, 贾方方 JIA Fangfang, 乔红波 QIAO Hongbo, and 张营武 ZHANG Yingwu. "Hyperspectral estimating models of tobacco leaf area index." Acta Ecologica Sinica 32, no. 1 (2012): 168–75. http://dx.doi.org/10.5846/stxb201011051586.

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26

Neinavaz, Elnaz, Andrew K. Skidmore, Roshanak Darvishzadeh, and Thomas A. Groen. "LEAF AREA INDEX RETRIEVED FROM THERMAL HYPERSPECTRAL DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 20, 2016): 99–105. http://dx.doi.org/10.5194/isprsarchives-xli-b7-99-2016.

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Leaf area index (LAI) is an important essential biodiversity variable due to its role in many terrestrial ecosystem processes such as evapotranspiration, energy balance, and gas exchanges as well as plant growth potential. A novel approach presented here is the retrieval of LAI using thermal infrared (8–14 μm, TIR) measurements. Here, we evaluate LAI retrieval using TIR hyperspectral data. Canopy emissivity spectral measurements were recorded under controlled laboratory conditions using a MIDAC (M4401-F) illuminator Fourier Transform Infrared spectrometer for two plant species during which LAI

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27

Palán, Ladislav, Josef Křeček, and Yoshinobu Sato. "Leaf area index in a forested mountain catchment." Hungarian Geographical Bulletin 67, no. 1 (2018): 3–11. http://dx.doi.org/10.15201/hungeobull.67.1.1.

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28

DANSON, F. M., and S. E. PLUMMER. "Red-edge response to forest leaf area index." International Journal of Remote Sensing 16, no. 1 (1995): 183–88. http://dx.doi.org/10.1080/01431169508954387.

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29

CHEN, J. M., and T. A. BLACK. "Defining leaf area index for non-flat leaves." Plant, Cell and Environment 15, no. 4 (1992): 421–29. http://dx.doi.org/10.1111/j.1365-3040.1992.tb00992.x.

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30

Aboelghar, M., S. Arafat, A. Saleh, S. Naeem, M. Shirbeny, and A. Belal. "Retrieving leaf area index from SPOT4 satellite data." Egyptian Journal of Remote Sensing and Space Science 13, no. 2 (2010): 121–27. http://dx.doi.org/10.1016/j.ejrs.2010.06.001.

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31

Shih, S. F., and G. H. Snyder. "Leaf Area Index and Evapotranspiration of Taro 1." Agronomy Journal 77, no. 4 (1985): 554–56. http://dx.doi.org/10.2134/agronj1985.00021962007700040012x.

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32

Gordon, R., D. M. Brown, and M. A. Dixon. "Estimating potato leaf area index for specific cultivars." Potato Research 40, no. 3 (1997): 251–66. http://dx.doi.org/10.1007/bf02358007.

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33

Patočka, Zdeněk, Kateřina Novosadová, Pavel Haninec, Radek Pokorný, Tomáš Mikita, and Martin Klimánek. "Comparison of LiDAR-based Models for True Leaf Area Index and Effective Leaf Area Index Estimation in Young Beech Forests." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 68, no. 3 (2020): 559–66. http://dx.doi.org/10.11118/actaun202068030559.

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The leaf area index (LAI) is one of the most common leaf area and canopy structure quantifiers. Direct LAI measurement and determination of canopy characteristics in larger areas is unrealistic due to the large number of measurements required to create the distribution model. This study compares the regression models for the ALS-based calculation of LAI, where the effective leaf area index (eLAI) determined by optical methods and the LAI determined by the direct destructive method and developed by allometric equations were used as response variables. LiDAR metrics and the laser penetration ind

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34

Abdul Manan, Faid, Muhammad Buce Saleh, I. Nengah Surati Jaya, and Uus Saepul Mukarom. "Algorithm for assessing forest stand productivity index using leaf area index." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 3 (2019): 1311. http://dx.doi.org/10.11591/ijeecs.v16.i3.pp1311-1319.

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This paper describes a development of an algorithm for assessing stand productivity by considering the stand variables. Forest stand productivity is one of the crucial information that required to establish the business plan for unit management at the beginning of forest planning activity. The main study objective is to find out the most significant and accurate variable combination to be used for assessing the forest stand productivity, as well as to develop productivity estimation model based on leaf area index. The study found the best stand variable combination in assessing stand productiv

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35

Alchemi, P. J. K., and S. Jamin. "Impact Of Pestalotiopsis Leaf Fall Disease On Leaf Area Index and Rubber Plant Production." IOP Conference Series: Earth and Environmental Science 995, no. 1 (2022): 012030. http://dx.doi.org/10.1088/1755-1315/995/1/012030.

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Abstract Currently, Pestalotiopsis leaf fall disease caused by the fungus Pestalotiopsis microspora is commonly found in Indonesian rubber plantations. The rubber defoliation period usually occurs for 1 month as a response to drought during the dry season. However, due to this disease, the rubber defoliation period occurs gradually with an earlier fall. Leaf fall can cause a decrease in the number of plant canopy which affects the leaf area index and latex production. Therefore, this study was carried out to examine the effect of Pestalotiopsis leaf fall disease on the decrease in leaf area in

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36

Kucharik, Christopher J., John M. Norman, and Stith T. Gower. "Measurements of branch area and adjusting leaf area index indirect measurements." Agricultural and Forest Meteorology 91, no. 1-2 (1998): 69–88. http://dx.doi.org/10.1016/s0168-1923(98)00064-1.

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37

Shaikh Abdullah Al Mamun, Hossain, Wang Lixue, Chen Taotao, and Li Zhenhua. "Leaf area index assessment for tomato and cucumber growing period under different water treatments." Plant, Soil and Environment 63, No. 10 (2017): 461–67. http://dx.doi.org/10.17221/568/2017-pse.

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The aim of this study was to assess the leaf area index (LAI) of tomato and cucumber using an AccuPAR-LP-80-ceptometer to find the influence of irrigation. LAI was also determined by destructive sampling for comparison. The research was conducted at the Liaoning Water Conservancy Institute, North China in 2016. A randomized block design was used to test the influence of four treatments corresponding to field water capacity. Full irrigation (W<sub>1.0</sub>), 15% (W<sub>0.85</sub>), 25% (W<sub>0.75</sub>) and 35% (W<sub>0.65</sub>) water deficit w

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38

Klima, K., and B. Wiśniowska-Kielian. "Anti-erosion effectiveness of selected crops and the relation to leaf area index (LAI)." Plant, Soil and Environment 52, No. 1 (2011): 35–40. http://dx.doi.org/10.17221/3343-pse.

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This paper presents results of an experiment carried out in 2000&ndash;2003 in the mountain region (southern Poland, 545 m a.s.l.) to determine the effect of over-ground parts growth of fodder beet, winter triticale and horse bean on the intensity of soil losses. The research was conducted on the hillside with a 16% slope with the simulated rainfall (105 mm; 1.75 mm/min) applied at seven developmental stages of the plants. It was stated that soil protective efficiency of the fodder beet, horse bean and winter triticale started at about 60, 30 and 15% of covering the soil surface, respectiv

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39

Kuusk, Andres. "Leaf area index (LAI) and gap fraction. A discussion." Baltic Forestry 29, no. 2 (2023): id715. http://dx.doi.org/10.46490/bf715.

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Methodological aspects of estimating leaf area from gap fraction measurements are discussed. Instead of the common practice of linking in the Beer-Lambert law leaf area index and clumping factor together, the clumping factor and Ross-Nilson geometry function as two structure parameters should be combined into the effective geometry function, which considers both the leaf angle distribution and clumping/regularity of foliage in the expression of the gap fraction of a vegetation layer. Key words: leaf area index; foliage clumping; gap fraction; LAI-2000; G-function

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40

Gower, Stith T., and John M. Norman. "Rapid Estimation of Leaf Area Index in Conifer and Broad-Leaf Plantations." Ecology 72, no. 5 (1991): 1896–900. http://dx.doi.org/10.2307/1940988.

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41

Xuan-Ran, LI, LIU Qi-Jing, CAI Zhe, and MA Ze-Qing. "SPECIFIC LEAF AREA AND LEAF AREA INDEX OF CONIFER PLANTATIONS IN QIANYANZHOU STATION OF SUBTROPICAL CHINA." Chinese Journal of Plant Ecology 31, no. 1 (2007): 93–101. http://dx.doi.org/10.17521/cjpe.2007.0012.

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42

Bouriaud, O., K. Soudani, and N. Bréda. "Leaf area index from litter collection: impact of specific leaf area variability within a beech stand." Canadian Journal of Remote Sensing 29, no. 3 (2003): 371–80. http://dx.doi.org/10.5589/m03-010.

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43

Ghadami Firouzabadi, Ali, Mahmoud Raeini-Sarjaz, Ali Shahnazari, and Hamid Zareabyaneh. "Non-destructive estimation of sunflower leaf area and leaf area index under different water regime managements." Archives of Agronomy and Soil Science 61, no. 10 (2015): 1357–67. http://dx.doi.org/10.1080/03650340.2014.1002776.

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44

Klubertanz, T. H., L. P. Pedico, and R. E. Carlson. "Reliability of Yield Models of Defoliated Soybean Based on Leaf Area Index Versus Leaf Area Removed." Journal of Economic Entomology 89, no. 3 (1996): 751–56. http://dx.doi.org/10.1093/jee/89.3.751.

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45

Jůzl, M., and M. Štefl. "The effect of leaf area index on potatoes yield in soils contaminated by some heavy metals." Plant, Soil and Environment 48, No. 7 (2011): 298–306. http://dx.doi.org/10.17221/4369-pse.

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A&nbsp;method of growth analysis was used to evaluate the yield results in experiments conducted during years 1999&ndash;2001 on School co-operative farm in Žabčice. In sequential terms of sampling from two potato varieties with different duration of growing season, the effect of leaf area index (L, LAI), on yield of tubers in soils contaminated by cadmium, arsine and beryllium, was evaluated. From a&nbsp;growers view the phytotoxic influence on development of assimilatory apparatus and yields during the growth of a&nbsp;very-early variety Rosara and a&nbsp;medium-early Kor

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46

Penner, Margaret, and Godelieve Deblonde. "The relationship between leaf area and basal area growth in jack and red pine trees." Forestry Chronicle 72, no. 2 (1996): 170–75. http://dx.doi.org/10.5558/tfc72170-2.

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Relationships between leaf area and sapwood area, sapwood area and basal area, and leaf area and basal area growth are determined for jack pine and red pine. The relationships vary with species and stand origin. Growth efficiency (basal area growth per unit leaf area) is relatively independent of tree size under all but the densest conditions. Observed changes in the leaf area to leaf mass ratio from July to October indicate that allometric relationships vary seasonally. A procedure is outlined for obtaining estimates of stand leaf area index (LAI). These estimates may be used to calibrate ins

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47

Khosravi, S., M. Namiranian, H. Ghazanfari, and A. Shirvani. " Estimation of leaf area index and assessment of its allometric equations in oak forests: Northern Zagros, Iran." Journal of Forest Science 58, No. 3 (2012): 116–22. http://dx.doi.org/10.17221/18/2011-jfs.

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The focus of the present study is the estimation of leaf area index (LAI) and the assessment of allometric equations for predicting the leaf area of Lebanon oaks (Quercus libani Oliv.) in Iran&rsquo;s northern Zagros forests. To that end, 50 oak trees were randomly selected and their biophysical parameters were measured. Then, on the basis of destructive sampling of the oak trees, their specific leaf area (SLA) and leaf area were measured. The results showed that SLA and LAI of the Lebanon oaks were 136.9 cm&middot;g<sup>&ndash;1 </sup>and 1.99, respectively. Among all

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48

Vose, James M., Barton D. Clinton, Neal H. Sullivan, and Paul V. Bolstad. "Vertical leaf area distribution, light transmittance, and application of the Beer–Lambert Law in four mature hardwood stands in the southern Appalachians." Canadian Journal of Forest Research 25, no. 6 (1995): 1036–43. http://dx.doi.org/10.1139/x95-113.

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We quantified stand leaf area index and vertical leaf area distribution, and developed canopy extinction coefficients (k), in four mature hardwood stands. Leaf area index, calculated from litter fall and specific leaf area (c2•g−1), ranged from 4.3 to 5.4 m2•m−2. In three of the four stands, leaf area was distributed in the upper canopy. In the other stand, leaf area was uniformly distributed throughout the canopy. Variation in vertical leaf area distribution was related to the size and density of upper and lower canopy trees. Light transmittance through the canopies followed the Beer–Lambert

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49

Bidlake, William R., and R. Alan Black. "Vertical distribution of leaf area in Larixoccidentalis: a comparison of two estimation methods." Canadian Journal of Forest Research 19, no. 9 (1989): 1131–36. http://dx.doi.org/10.1139/x89-171.

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Total leaf-area index and the vertical distribution of leaf-area index were described for an unthinned stand (density 11 250 stems/ha) and a thinned stand (density 1660 stems/ha) of 30-year-old Larixoccidentalis Nutt. Two independent methods were used to estimate leaf-area index in each of the two stands. The first method is based on allometric relationships that are applied to stem measurements, and the second method is based on gap-fraction analysis of fisheye photographs. Leaf-area index estimates obtained by the two methods were not significantly different. The gap-fraction method provides

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50

Sommer, KJ, and ARG Lang. "Comparative Analysis of Two Indirect Methods of Measuring Leaf Area Index as Applied to Minimal and Spur Pruned Grape Vines." Functional Plant Biology 21, no. 2 (1994): 197. http://dx.doi.org/10.1071/pp9940197.

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Abstract:

Leaf area index of spur and minimal pruned vines was measured directly by destructive leaf sampling and indirectly from light transmission measurements using the LAI-2000 and the DEMON instruments. Both instruments provided good estimates of plant and leaf area index. The LAI-2000 had a tendency to underestimate leaf area index. The DEMON instrument provided the most accurate estimate of plant and leaf area index. With both instruments it is important to validate indirect with direct estimates of vine leaf area.

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