Estimating Canopy Light Interception and Absorption Using Leaf Mass Per Unit Leaf Area in Solanum melongena

Abstract Knowledge of canopy light interception and absorption is fundamental for understanding many aspects of crop growth and productivity, and for crop modelling. Light interception is commonly measured with expensive equipment or estimated with elaborate models; simpler and more economical ways of estimation would be advantageous. Since leaf mass per unit leaf area ( M A ) is closely related to long-term light interception by leaves, the latter can be estimated by measuring M A  . In this study, partitioning of leaf area into one of six classes of M A was used to estimate canopy light interception and absorption in aubergine ( Solanum melongena L.) grown with different amounts of nitrogen fertilizer and with or without artificial shade. Although plants grown with ample fertilizer had a greater leaf area index (LAI) than those grown with less nitrogen, the increase in leaf area occurred in the lower and intermediate M A classes, while the leaf area in the two highest M A classes was similar. Artificially shaded plants had more leaf area in the lower M A classes and less in the higher classes compared to unshaded plants, showing acclimation to low light conditions. The amount of light intercepted daily by leaves in each M A class was estimated using the previously determined light :  M A relationship. Canopy light interception was calculated as the sum of intercepted light for all M A classes, and canopy light absorption was estimated from light interception data assuming a constant absorption coefficient (82%). To validate the results, the estimated values were compared to those calculated from independent measurements of light absorption carried out in the same field. Results indicate that it is possible to estimate canopy light interception and absorption from the partitioning of leaf area into M A classes.

[1]  Ü. Niinemets.  Distribution of foliar carbon and nitrogen across the canopy of Fagus sylvatica: adaptation to a vertical light gradient , 1995 .

[2]  Tadaki Hirose,et al.  CO2 ELEVATION, CANOPY PHOTOSYNTHESIS, AND OPTIMAL LEAF AREA INDEX , 1997 .

[3]  C. T. Wit.  Photosynthesis of leaf canopies , 1965 .

[4]  B. Barfield,et al.  Modification of the aerial environment of plants , 1979 .

[5]  F. D. Whisler,et al.  Crop simulation models in agronomic systems , 1986 .

[6]  I. R. Cowan.  The Interception and Absorption of Radiation in Plant Stands , 1968 .

[7]  R. Ryel,et al.  Foliage Orientation and Carbon Gain in Two Tussock Grasses as Assessed with a New Whole-plant Gas Exchange Model , 1993 .

[8]  T. Dejong,et al.  Distribution of leaf mass per unit area and leaf nitrogen concentration determine partitioning of leaf nitrogen within tree canopies. , 2000, Tree physiology.

[9]  P. Reich,et al.  Response of Ulmus americana seedlings to varying nitrogen and water status. 1 Photosynthesis and growth. , 1989, Tree physiology.

[10]  T. W. Jurik,et al.  Temporal and spatial patterns of specific leaf weight in successional northern hardwood tree species , 1986 .

[11]  Ü. Niinemets.  Role of foliar nitrogen in light harvesting and shade tolerance of four temperate deciduous woody species , 1997 .

[12]  M. Monsi.  Uber den Lichtfaktor in den Pflanzengesellschaften und seine Bedeutung fur die Stoffproduktion , 1953 .

[13]  M. Dingkuhn,et al.  Nitrogen fertilization of direct-seeded flooded vs. transplanted rice. II, Interactions among canopy properties , 1990 .

[14]  T. Dejong,et al.  Seasonal relationships between leaf nitrogen content (photosynthetic capacity) and leaf canopy light exposure in peach (Prunus persica) , 1985 .

[15]  T. W. Jurik,et al.  Effects of Light and Nutrients on Leaf Size, CO(2) Exchange, and Anatomy in Wild Strawberry (Fragaria virginiana). , 1982, Plant physiology.

[16]  R. Hunt,et al.  The Mathematics of Photosynthesis and Productivity. , 1981 .

[17]  M. Werger,et al.  Optimal leaf area indices in C3 and C4 mono‐ and dicotyledonous species at low and high nitrogen availability , 1995 .

[18]  Hans R. Schultz,et al.  Leaf absorptance of visible radiation in Vitis vinifera L.: estimates of age and shade effects with a simple field method , 1996 .

[19]  Paul G. Jarvis,et al.  Description and validation of an array model - MAESTRO. , 1990 .

[20]  G. Hammer,et al.  Night Temperature Affects Radiation‐Use Efficiency in Peanut , 1992 .

[21]  T. Dejong,et al.  Influence of canopy light environment and nitrogen availability on leaf photosynthetic characteristics and photosynthetic nitrogen-use efficiency of field-grown nectarine trees. , 1999, Tree physiology.

[22]  W. Claussen,et al.  Die Bedeutung der Saccharose- und Stärkegehalte der Blätter für die Regulierung der Netto-Photosyntheseraten , 1977 .

[23]  P. Reich,et al.  Leaf age and season influence the relationships between leaf nitrogen, leaf mass per area and photosynthesis in maple and oak trees , 1991 .

[24]  P. Jarvis,et al.  CHANGES IN CHLOROPHYLL AND CAROTENOID CONTENT, SPECIFIC LEAF AREA AND DRY WEIGHT FRACTION IN SITKA SPRUCE, IN RESPONSE TO SHADING AND SEASON , 1977 .

[25]  David W. Lee,et al.  Optical properties of leaves of some Indian plants , 1986 .

[26]  Tadaki Hirose,et al.  CO2 ELEVATION, CANOPY PHOTOSYNTHESIS, ANDOPTIMAL LEAF AREA INDEX , 1997 .

[27]  C. E. Murphy,et al.  Development and Evaluation of Simplified Models for Simulating Canopy Photosynthesis and Transpiration , 1976 .

[28]  C.J.T. Spitters,et al.  Separating the diffuse and direct component of global radiation and its implications for modeling canopy photosynthesis Part II. Calculation of canopy photosynthesis , 1986 .

[29]  J. Goudriaan,et al.  Crop Micrometeorology: A Simulation Study , 1977 .

[30]  W. E. Loomis,et al.  Absorption Spectra of Leaves. I. The Visible Spectrum. , 1952, Plant physiology.

[31]  J. Cermak.  Solar equivalent leaf area: an efficient biometrical parameter of individual leaves, trees and stands. , 1989, Tree physiology.