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Artykuły w czasopismach na temat „Leaf area”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 25 lipca 2025

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1

Payne, W. A., C. W. Wendt, L. R. Hossner, and C. E. Gates. "Estimating Pearl Millet Leaf Area and Specific Leaf Area." Agronomy Journal 83, no. 6 (1991): 937–41. http://dx.doi.org/10.2134/agronj1991.00021962008300060004x.

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2

S, THIMMEGOWDA. "ESTIMATION OF LEAF AREA IN WHEAT GENOTYPES." Madras Agricultural Journal 73, May (1986): 278–80. http://dx.doi.org/10.29321/maj.10.a02268.

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Leaf product cons ants for night wheat genotypes, ware investigated. The test product constants varied significantly 10.729 to 0.709 for flag-leat, 0.737 10 0.864. for other than flag leaf and 0 740 to 0.831 for all leaves) among the genotypes. This indicated that a singla constant for whost cras as such cannot be accepted." However, a lea! product constant of flag leaf only could be used for estimating leaf area in wheat genotypes as the high releationship existed between the actual leal area and the estimated leaf area in all the genotypes as compared to other than flag leaf and all leaves

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3

Chinnamuthu, C. R., C. Kailasam, and Dr S. Sankaran. "Sorghum Leaf Area as a Function of Sixth Leaf Area." Journal of Agronomy and Crop Science 162, no. 5 (1989): 300–304. http://dx.doi.org/10.1111/j.1439-037x.1989.tb00720.x.

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4

K, BALAKRISHNAN, NATARAJARATNAM N, and SUNDARUM K.M. "A RAPID METHOD FOR THE ESTIMATION OF LEAF AREA IN FIELD BEAN." Madras Agricultural Journal 72, November (1985): 633–35. http://dx.doi.org/10.29321/maj.10.a02415.

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The present investigation aimed to establish a relationship between leaf length x leal breadth and leat area in field bean CV. Co. 1. The regression equation fitted against leaf area and the product between terminal leaf length and breadth was Y = 3 09+1.63 (X) (r = 0.9647**), where Y = leaf area (trifoliate leaf) per leaf. X = Length X Breadth of the terminal leaf let of the trifoliate leaf (L x B). The leaf area was also predicted by using the formula A = 1,685 (L x B). A significant correlation (r=0.9630) was also obtained with actual and predicted leaf area by using the above constants. It

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5

Awal, M. A., Wan Ishak ., J. Endan ., and M. Haniff . "Determination of Specific Leaf Area and Leaf Area-leaf Mass Relationship in Oil Palm Plantation." Asian Journal of Plant Sciences 3, no. 3 (2004): 264–68. http://dx.doi.org/10.3923/ajps.2004.264.268.

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6

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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7

Smith, Duncan D., John S. Sperry, and Frederick R. Adler. "Convergence in leaf size versus twig leaf area scaling: do plants optimize leaf area partitioning?" Annals of Botany 119, no. 3 (2016): 447–56. http://dx.doi.org/10.1093/aob/mcw231.

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Background and Aims Corner’s rule states that thicker twigs bear larger leaves. The exact nature of this relationship and why it should occur has been the subject of numerous studies. It is obvious that thicker twigs should support greater total leaf area (Atwig) for hydraulical and mechanical reasons. But it is not obvious why mean leaf size (A-) should scale positively with Atwig. We asked what this scaling relationship is within species and how variable it is across species. We then developed a model to explain why these relationships exist. Methods To minimize potential sources of variabil

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8

Tony, K. Hariadi, Fadholi Zulfan, NN Chamim Anna, A. Utama Nafi, Prabasari Indira, and Riyadi Slamet. "Development of Leaf Area Meter Using Open CV for Smartphone Application." TELKOMNIKA Telecommunication, Computing, Electronics and Control 16, no. 4 (2018): 1857–63. https://doi.org/10.12928/TELKOMNIKA.v16i4.8608.

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This study aimed to design an accurate and practical system of leaf area determination using a smartphone. A software application for leaf area computation was developed using Open CV (Open Source Computer Vision) library. Open CV software was tested to estimate the accuracy of leaf area calculation. Leaf area calculations were undertaken using three different image resolutions to compare their accuracy. The results of the software calculations were then compared with the results of the laboratory leaf area meter to identify any errors. The results showed that higher image resolutions improved

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9

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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10

Cargnelutti Filho, Alberto, Rafael Vieira Pezzini, Ismael Mario Márcio Neu, and Gabriel Elias Dumke. "Estimation of buckwheat leaf area by leaf dimensions." Semina: Ciências Agrárias 42, no. 3Supl1 (2021): 1529–48. http://dx.doi.org/10.5433/1679-0359.2021v42n3supl1p1529.

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The objective of this work was to model and identify the best models for estimating the leaf area, determined by digital photos, of buckwheat (Fagopyrum esculentum Moench) of the cultivars IPR91-Baili and IPR92-Altar, as a function of length (L), width (W) or length x width product (LW) of the leaf blade. Ten uniformity trials (blank experiments) were carried out, five with IPR91-Baili cultivar and five with IPR92-Altar cultivar. The trials were performed on five sowing dates. In each trial and cultivar, expanded leaves were collected at random from the lower, middle and upper segments of the

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11

Toebe, M., P. J. Melo, R. R. Souza, A. C. Mello, and F. L. Tartaglia. "Leaf area estimation in triticale by leaf dimensions." Revista Brasileira de Ciências Agrárias - Brazilian Journal of Agricultural Sciences 14, no. 2 (2019): 1–9. http://dx.doi.org/10.5039/agraria.v14i2a5656.

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12

Simón, M. R. "Inheritance of flag-leaf angle, flag-leaf area and flag-leaf area duration in four wheat crosses." Theoretical and Applied Genetics 98, no. 2 (1999): 310–14. http://dx.doi.org/10.1007/s001220051074.

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13

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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14

Silva, Jocélia Rosa da, Arno Bernardo Heldwein, Andressa Janaína Puhl, et al. "Leaf Area Estimation in Chamomile." Journal of Agricultural Science 11, no. 2 (2019): 429. http://dx.doi.org/10.5539/jas.v11n2p429.

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The knowledge of the variables specific leaf area and leaf area index is important for direct or indirect quantification of plant growth, development and yield. However, there is a lack of these information due to the difficulty in measuring the leaf area of chamomile. Measuring leaf area by direct methods, such as the use of leaf area integrator is a very laborious and time consuming activity because the plant has many leaves and with small size. The use of leaf dry matter is a promising variable for the leaf area estimation. As an important measure to evaluate plant growth, the present study

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15

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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16

Stancioiu, Petru Tudor, and Kevin L. O'Hara. "Sapwood area leaf area relationships for coast redwood." Canadian Journal of Forest Research 35, no. 5 (2005): 1250–55. http://dx.doi.org/10.1139/x05-039.

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Coast redwood (Sequoia sempervirens (D. Don) Endl.) trees in different canopy strata and crown positions were sampled to develop relationships between sapwood cross-sectional area and projected leaf area. Sampling occurred during the summers of 2000 and 2001 and covered tree heights ranging from 7.7 to 45.2 m and diameters at breast height ranging from 9.4 to 92.7 cm. Foliage morphology varied greatly and was stratified into five types based on needle type (sun or shade) and twig color. A strong linear relationship existed between projected leaf area and sapwood area at breast height or sapwoo

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17

Liu, Guofan, and Kent D. Kobayashi. "250 Using Leaf Area Devices (LADS) to Estimate Total Leaf Area of Coffee Plants." HortScience 34, no. 3 (1999): 485C—485. http://dx.doi.org/10.21273/hortsci.34.3.485c.

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It is difficult to estimate the total leaf area of coffee plants with accuracy due to the large number of leaves and the high leaf density of the plant canopy. In 1996, on Maui, Hawaii, 98 leaves of various sizes were randomly collected for each of five cultivars of Coffea arabica L. The cultivars used were `Guadalupe', `Guatemalan', `Mokka', `Red Catuai', and `Yellow Caturra'. Leaf length, width, and area were measured. Seventy-five leaves were used to develop leaf area models, and the remaining leaves were used to test the accuracy of the models using a 1:1 line. We then developed leaf area

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18

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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19

Bhagsari, A. S., and R. H. Brown. "Leaf Photosynthesis and its Correlation with Leaf Area 1." Crop Science 26, no. 1 (1986): 127–32. http://dx.doi.org/10.2135/cropsci1986.0011183x002600010030x.

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20

Thanisawanyangkura, Sornprach, Herve Sinoquet, Pierre Rivet, Michel Cretenet, and Eric Jallas. "Leaf orientation and sunlit leaf area distribution in cotton." Agricultural and Forest Meteorology 86, no. 1-2 (1997): 1–15. http://dx.doi.org/10.1016/s0168-1923(96)02417-3.

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21

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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22

Schrader, Julian, Giso Pillar, and Holger Kreft. "Leaf-IT: An Android application for measuring leaf area." Ecology and Evolution 7, no. 22 (2017): 9731–38. http://dx.doi.org/10.1002/ece3.3485.

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23

Solov’ev, A. V., and M. K. Kayumov. "Determining optimal leaf surface area." Russian Agricultural Sciences 33, no. 1 (2007): 16–18. http://dx.doi.org/10.3103/s1068367407010065.

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24

Lafarge, T. A., and G. L. Hammer. "Predicting plant leaf area production:." Field Crops Research 77, no. 2-3 (2002): 137–51. http://dx.doi.org/10.1016/s0378-4290(02)00085-0.

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25

Darshan, Muchadia, and Vrinda S. Thaker. "Leaf Area Meter (LAM): Software for the Measurement of Leaf Area and Related Analysis." Vegetos- An International Journal of Plant Research 30, special (2017): 64. http://dx.doi.org/10.5958/2229-4473.2017.00035.0.

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26

Çırak, C., M. S Odabaş, B. Sağlam, and A. K Ayan. "Relation between leaf area and dimensions of selected medicinal plants." Research in Agricultural Engineering 51, No. 1 (2012): 13–19. http://dx.doi.org/10.17221/4896-rae.

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In this research, leaf area prediction models were developed for some leaf-used medicinal plants namely Calamintha nepeta, Datura stromonium, Melissa officinalis, Mentha piperita, Nerium oleander, Origanum onites and Urtica dioica growing wild in Black Sea region of Turkey. Lamina width, length and leaf area were measured non-destructively to develop the models. The actual leaf areas of the plants were measured by PLACOM Digital Planimeter, and multiple regression analysis with Excel 7.0 computer package program was performed for the plants separately. The produced leaf area prediction models

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27

Keane, M. G., and G. F. Weetman. "Leaf area – sapwood cross-sectional area relationships in repressed stands of lodgepole pine." Canadian Journal of Forest Research 17, no. 3 (1987): 205–9. http://dx.doi.org/10.1139/x87-036.

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To better understand the phenomenon of growth "stagnation" in high-density lodgepole pine (Pinuscontorta Dougl. ex Loud.), leaf area and its relationship with sapwood cross-sectional area were examined on both an individual tree and stand basis. Leaf areas of individual trees in a 22-year-old stand varied from 30.8 m2 (dominants in stands of low stocking) to 0.05 m2 (suppressed trees in stands of high stocking). Leaf area indices ranged from 13.4 to 2.3 m2 m−2 between low and high stocking levels, respectively. Over the same stocking range, the ratio of leaf area to sapwood cross-sectional are

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28

Wu, Dan, Stuart Phinn, Kasper Johansen, Andrew Robson, Jasmine Muir, and Christopher Searle. "Estimating Changes in Leaf Area, Leaf Area Density, and Vertical Leaf Area Profile for Mango, Avocado, and Macadamia Tree Crowns Using Terrestrial Laser Scanning." Remote Sensing 10, no. 11 (2018): 1750. http://dx.doi.org/10.3390/rs10111750.

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Vegetation metrics, such as leaf area (LA), leaf area density (LAD), and vertical leaf area profile, are essential measures of tree-scale biophysical processes associated with photosynthetic capacity, and canopy geometry. However, there are limited published investigations of their use for horticultural tree crops. This study evaluated the ability of light detection and ranging (LiDAR) for measuring LA, LAD, and vertical leaf area profile across two mango, macadamia and avocado trees using discrete return data from a RIEGL VZ-400 Terrestrial Laser Scanning (TLS) system. These data were collect

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29

Righetti, Timothy L., Carmo Vasconcelos, David R. Sandrock, Samuel Ortega-Farias, Yerko Moreno, and Francisco J. Meza. "Assessments of CO2 Assimilation on a Per-leaf-area Basis are Related to Total Leaf Area." Journal of the American Society for Horticultural Science 132, no. 2 (2007): 230–38. http://dx.doi.org/10.21273/jashs.132.2.230.

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Net photosynthetic rates often are dependent on leaf size when expressed on a leaf-area basis (CO2 assimilation as μmol·m−2·s−1). Therefore, distinguishing between leaf-size-related and other causes of differences in net photosynthetic rate cannot be determined when data are presented on a leaf-area basis. From a theoretical perspective, CO2 assimilation expressed on a leaf-area basis (μmol·m−2·s−1) will be independent of leaf area only when total net CO2 assimilation (leaf CO2 assimilation as μmol·s−1) is linearly related to leaf area and the function describing this relationship has a nonzer

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30

Abani, M. S. C. "Leaf Area Formulae for Estimating Leaf Areas of "Okazi" (Gnetum afrianum) and "Nchuanwu" (Ocimum viridis)." Journal of Agronomy and Crop Science 160, no. 3 (1988): 180–82. http://dx.doi.org/10.1111/j.1439-037x.1988.tb00315.x.

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31

Easlon, Hsien Ming, and Arnold J. Bloom. "Easy Leaf Area: Automated Digital Image Analysis for Rapid and Accurate Measurement of Leaf Area." Applications in Plant Sciences 2, no. 7 (2014): 1400033. http://dx.doi.org/10.3732/apps.1400033.

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32

Barclay, H. J. "Conversion of total leaf area to projected leaf area in lodgepole pine and Douglas-fir." Tree Physiology 18, no. 3 (1998): 185–93. http://dx.doi.org/10.1093/treephys/18.3.185.

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33

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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34

Cristian, Manuel Agudelo Restrepo, Eduardo Roa-Guerrero Edgar, and Numpaque López Humberto. "Leaf detector box: Artificial vision system for leaf area identification." African Journal of Agricultural Research 12, no. 20 (2017): 1702–12. http://dx.doi.org/10.5897/ajar2016.11698.

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35

Singh, A. "APPROXIMATION OF LEAF AREA BY USING LEAF DIMENSIONS IN GUAVA." Acta Horticulturae, no. 735 (March 2007): 321–24. http://dx.doi.org/10.17660/actahortic.2007.735.44.

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36

Koubouris, Georgios, Dimitris Bouranis, Efraim Vogiatzis, et al. "Leaf area estimation by considering leaf dimensions in olive tree." Scientia Horticulturae 240 (October 2018): 440–45. http://dx.doi.org/10.1016/j.scienta.2018.06.034.

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37

Mencuccini, Maurizio, Teresa Rosas, Lucy Rowland, et al. "Leaf economics and plant hydraulics drive leaf : wood area ratios." New Phytologist 224, no. 4 (2019): 1544–56. http://dx.doi.org/10.1111/nph.15998.

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38

FARGO, W. S., E. L. BONJOUR, and T. L. WAGNER. "AN ESTIMATION EQUATION FOR SQUASH LEAF AREA USING LEAF MEASUREMENTS." Canadian Journal of Plant Science 66, no. 3 (1986): 677–82. http://dx.doi.org/10.4141/cjps86-089.

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An equation was developed which may be used to estimate the area of all sizes of developing squash (Cucurbita pepo L.) leaves. The equation uses two leaf measurements (midrib length (ML) and the distance between tertiary lobes (TD)) which may be taken quickly in the laboratory or field without disturbing the host plant. The equation is:[Formula: see text]The equation is applicable in monitoring individual leaf expansion as well as total plant leaf area increase and in examining the dynamics of the plant under various environmental conditions.Key words: Cucurbita pepo L., leaf area, growth, dev

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39

Reddy, V. R., B. Acock, D. N. Baker, and M. Acock. "Seasonal Leaf Area‐Leaf Weight Relationships in the Cotton Canopy." Agronomy Journal 81, no. 1 (1989): 1–4. http://dx.doi.org/10.2134/agronj1989.00021962008100010001x.

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Shi, Hanyu, Jingyi Jiang, Stéphane Jacquemoud, Zhiqiang Xiao, and Mingguo Ma. "Estimating leaf mass per area with leaf radiative transfer model." Remote Sensing of Environment 286 (March 2023): 113444. http://dx.doi.org/10.1016/j.rse.2022.113444.

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41

Sellin, Arne, and Priit Kupper. "Spatial variation in sapwood area to leaf area ratio and specific leaf area within a crown of silver birch." Trees 20, no. 3 (2006): 311–19. http://dx.doi.org/10.1007/s00468-005-0042-2.

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42

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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Lee, Jae Myun, Jae Yeon Jeong, and Hyo Gil Choi. "Estimation of Leaf Area Using Leaf Length, Leaf width, and Lamina Length in Tomato." Journal of Bio-Environment Control 31, no. 4 (2022): 325–31. http://dx.doi.org/10.12791/ksbec.2022.31.4.325.

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Mack, Laura, Filippo Capezzone, Sebastian Munz, et al. "Nondestructive Leaf Area Estimation for Chia." Agronomy Journal 109, no. 5 (2017): 1960–69. http://dx.doi.org/10.2134/agronj2017.03.0149.

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45

NeSmith, D. S. "Estimating Summer Squash Leaf Area Nondestructively." HortScience 27, no. 1 (1992): 77. http://dx.doi.org/10.21273/hortsci.27.1.77.

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46

Erlacher, Wellington A., Fábio L. Oliveira, Gustavo S. Fialho, Diego MN Silva, and Arnaldo HO Carvalho. "Models for estimating yacon leaf area." Horticultura Brasileira 34, no. 3 (2016): 422–27. http://dx.doi.org/10.1590/s0102-05362016003019.

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ABSTRACT The recent exploration of yacon demands scientific information for improving the crop production technology. This study aimed to set a leaf area estimate model for yacon plants, using non-destructive measurements of leaf length (L) and/or width (W). Sixty-four representative yacon plants were randomly selected in an experimental field during the full vegetative growth. One thousand leaves of various sizes were taken from those plants for setting and validating a model. The logarithmic model best fitted this purpose, the result of multiplying length by width being used as independent v

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47

Aleynikov, A. F., and S. M. Shadrin. "Smartphone-based plant leaf area meter." IOP Conference Series: Earth and Environmental Science 839, no. 3 (2021): 032032. http://dx.doi.org/10.1088/1755-1315/839/3/032032.

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Abstract A portable device is described for measuring an important plant trait – plant leaf area. The principle of operation of the device is based on digital processing of the obtained images by the method of technical vision. It is implemented on the basis of a free cross-platform framework for game development and visualization – the LibGDX software project. An algorithm and a program for the automated determination of the leaf area are presented. The device is autonomous and is based on a smartphone and a gadget for it. The results of his research tests are presented. The purpose of the de

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48

Çi̇rak, C., M. Odabaş, A. Ayan, B. Sağlam, and K. Kevseroğlu. "Estimation of leaf area in selectedHypericumspecies." Acta Botanica Hungarica 50, no. 1-2 (2008): 81–91. http://dx.doi.org/10.1556/abot.50.2008.1-2.5.

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49

Westoby, Warton, and Reich. "The Time Value of Leaf Area." American Naturalist 155, no. 5 (2000): 649. http://dx.doi.org/10.2307/3078987.

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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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