Leaf Area Index (LAI) can give a clue to the most of the magic in the plant and its photosyntesis. At the same time, the more you know about this aspect, the better you understand what does your plant needs and how to be the most effective grower.
If you still don’t know what is Leaf Area Index, don’t feel ashamed. Every year thousands of hundreds people ask this in Google. They also asked about other things related to leaf area index. Hence, in this article we will try to get as many insights for beginners about leaf area index as possible.
Basically, leaf area index is the amount of green leaf mass in a canopy. It expresses the leaf area per unit ground or trunk surface area of a plant. Also, leaf area index is common equivalent of an indicator of the growth rate of a plant. Leaf Area Index is one of the top requests for many plant researchers Leaf Area Index is one of the top requests for many plant researchers
One of the first mentions of this index appeared in 1927 in the article “Sclerotinia Wilt of Sunflower”. Paul Allen Young and Harry Elwood Morris published this 32-pages research in the Bulletin of Montana Agricultural Experiment Station in the United States. One of the earliest mentions of leaf area index was published in the research of Sclerotinia disease in sunflowers. Photo credit: The American Phytopathological Society.
However, the most cited definition of leaf area index appeared in 1947. Dr. Watson suggested that leaf area index is the total one-sided area of leaf tissue per unit ground surface area. His 35-page research “Comparative Physiological Studies on the Growth of Field Crops. Variation in Net Assimilation Rate and Leaf Area between Species and Varieties and between Years” in the Annals of Botany.
In modern usage we have slightly more advanced version of this definition:
Leaf Area Index is geometrically defined as the total one-sided area of photosynthetic tissue per unit ground surface area Journal of Experimental Botany, 2003
Since that time, leaf area index has become one of the frequently used parameters by scientists in agriculture, ecology and climate change studies. Hence, researchers of the specific fields of science developed their own definitions such as:
Leaf Area Index is defined as the projected area of leaves over a unit of land (m2 m−2), so one unit of LAI is equivalent to 10,000 square meters of leaf area per hectare. Forest Ecosystems (Third Edition), 2007 The Leaf Area Index of a plant canopy or ecosystem, defined as one half of the total green leaf area per unit horizontal ground surface area, measures the area of leaf material present in the specified environment. US National Centres for Environmental Information
Leaf Area Index as a crucial characterization parameter, reflects the canopy structural characteristics of crops or ecosystems. It significant role is based on the factor that LAI partly impacts on important mass and energy exchange processes. For example, it participates in control of radiation and rain interception, as well as photosynthesis and respiration, which couple vegetation to the climate system.
Analysis and estimation of Leaf Area Index is of prime importance in the agricultural sector and is one of the key biophysical variables. It has a direct link to plant growth status, net assimilation rate, plant photosynthesis, and carbon dioxide in the environment. Crop modelling requires it to assess canopy structure. Also, LAI is a key input parameter in many crop growth simulation as well as radiative transfer models.
Alongside with climate and nitrogen (N), leaf area index is one of the key determinants of crop yield. Majority of precision farming applications need to leverage the assimilation of LAI measurements; they convert them into dynamic crop simulation models.
Leaf Area Index is one of the key parameters in plant ecology for global and regional models of biosphere/atmosphere exchange of carbon dioxide as well as water vapor. Particularly, it helps to understand:
how much foliage there is; what is the photosynthetic active area in specific region, and which of the area is a subject to transpiration and contacts with air pollutants.
Hence, this index serves as a numerical representation of specific zones, trees, forests, etc. in thousands of studies. In ecology, LAI works on different levels. For example, it can be calculated for a plant or scaled up to more significant areas, like a forest or even a region.
Also, researchers use historical data to build global datasets of this index, based on field measurements of green canopy.
According to FAO, monitoring the distribution and changes of LAI is important for assessing growth and vigour of vegetation on our planet. Its value has fundamental importance as a parameter in land-surface processes and parameterizations in climate models. Particularly, this variable represents the amount of leaf material in ecosystems. Additionally, it controls the links between biosphere and atmosphere through various processes, such as photosynthesis, respiration, transpiration and rain interception.
Because of its importance, the Global Climate Observing System (GCOS) considers LAI as an Essential Climate Variable (ECV) by the .
Depending on the subject of the research, available data about the plants and financial input of the project, the methods to calculate LAI are different. As a result, there is a division to direct and indirect methods.
These methods are good fit for small-scale and/or low budget projects. The core step of this method is to collect leaves during leaf fall in traps of certain area. This leaf traps has to be distributed below the canopy. Then after measuring total leaf area with convenient method, it is possible to get the LAI. The total leaf area of measured leaves can be divided by the area of the traps. Petiole Pro mobile application for agritech: Leaf Area Meter Measurement in a mobile application Mobile applications, which can be run on most of the smartphones, are helpful to calculate Leaf Area
There is an alternative way how to directly calculate LAI. However, it is more complicated in comparison with the described one. For this method a researcher needs to have a sub-sample of the collected leaves and measure leaf dry mass. There is no need to measure the area of all leaves one by one, but weigh the collected leaves after drying. To dry the leaves, there is a need to place them to the oven at 60–80 °C for 48 hours. Leaf dry mass multiplied by the specific leaf area, which is the ratio of leaf area to leaf dry mass, is converted into leaf area.
Traditionally, there are two main indirect methods of estimating LAI in situ such as:
indirect contact LAI measurements. For example, plumb lines and inclined point quadrats and indirect non-contact measurements. For example, the most widespread type of these measurements is hemispherical photography.
Hemispherical Photo is one of the most popular indirect non-contact measurement method for Leaf Area Index. Photo credit: Wikimedia Hemispherical Photo is one of the most popular indirect non-contact measurement method for LAI. Photo credit: Wikimedia
Space agencies and other institutions generate maps of LAI at various spatial resolutions. The frequency of generating differs from a daily to monthly period over the globe. Traditionally, they use optical space borne sensors. For example, one of the most trustable sensors, which provide reliable data about LAI is Sentinel-3/OLCI, Proba-V. Global LAI map of PROBA-V LAI 300m for the first decade of July 2017. Photo credit: The Copernicus Global Land Service
In 1999 a group of scientists published a research “LAI evolution of a perennial ryegrass crop estimated from the sum of temperatures in spring time”. They confirmed a significant increase in LAI grassland during one spring month. Correlating this phenomenon with the appropriate nutrient level and water supply it is clear that in spring time, the key inputs were close to optimum. At the same time, in unfavourable light conditions biomass does not develop properly. Leaf Area Index is significantly affected by the light because plant development depends on the amount of light in the environment. Photo credit: Katie Chen LAI is significantly affected by the light because plant development depends on the amount of light in the environment. Photo credit: Katie Chen
A group of Polish scientists found that the development processes of vegetation coverage were stopped at the sites of lower solar radiation, which are evidenced by a decreasing in the LAI values and aboveground biomass. The high correlation coefficient between LAI and leaves coverage and between LAI and sward height were found in both parks.
The research “Leaf Area Index Estimates for Wheat from LANDSAT and Their Implications for Evapotranspiration and Crop Modelling” establishes the foundation of the research about impact of LAI on evapotranspiration. It took place in 1979 and one of the main conclusions of the scientific work said about the suitability of LAI as a core input for building evapotranspiration and photosynthesis models.
Following this topic, recently, it has been once more confirmed that LAI is a critical variable of evapotranspiration calculations.
However, its role for different geographical locations is not the same. For example, the conclusion in one of the Canadian studies says that significance in terms of an impact on evapotranspiration for LAI is higher than soil texture. As a result, scientists consider proportion of leaf canopy per ground unit as a more efficient moderator of recharge and runoff. Especially, this is relevant for the soil texture of very fine sand.
First of all, let’s translate the abbreviations. LAI stands for Leaf Area Index but NDVI means “normalized difference vegetation index”. On one hand, it seems that both indices are about the amount of green canopy. That’s true. However, on the other hand, LAI is not directly proportional to NDVI. Also different vegetation types and soil types demonstrate different relationships between the two parameters. For example, broadleaf evergreens versus needleleaf evergreens will have completely different indices without any correlation.
Answer to this question depends on the type of crop, geography and environmental factors.
For example, in the recent research of early 2000s, the scientists found: in soybean there is a significant linear decrease in yield. It occurs when leaf area index values were lower, whereas yields usually reached a plateau at higher leaf area index levels. Respectively, bigger amount of leaves correlates to the maximum potential yield.
However, other group of scientist published a research in 2016 and concluded that decreasing, not increasing, leaf area will raise crop yields under global atmospheric change. Particularly, they experimentally confirmed that a modern crop cultivar produces more leaf than is optimal for yield under today’s and future [CO2]. Hence, reducing leaf area would give higher yields. They also suggest the significant role of breeding or bioengineering in the process of increasing soybean yield by developing lower leaf area.
Additionally, there are some recent studies on the topic such as:
Comprehensive and quantitative analysis of growth characteristics of winter wheat in China based on growing degree days (2020) An Estimation of Crop Leaf Area Index Using Image Processing and GSM Technology (2015) Digital Cover Photography for Estimating Leaf Area Index (LAI) in Apple Trees Using a Variable Light Extinction Coefficient (2015) Measuring leaf area index (LAI)from colour digital image of wheat crop (2014) Estimation of Leaf Area Index and Plant Area Index of a Submerged Macrophyte Canopy Using Digital Photography (2012)
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