Comparative Analysis of Two Indirect Methods of Measuring Leaf Area Index as Applied to Minimal and Spur Pruned Grape Vines

1994 ◽  
Vol 21 (2) ◽  
pp. 197 ◽  
Author(s):  
KJ Sommer ◽  
ARG Lang
Keyword(s):  
Comparative Analysis ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Light Transmission ◽  
Accurate Estimate ◽  
Indirect Methods ◽  
Area Index ◽  
Leaf Sampling ◽  
Transmission Measurements

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.

scholarly journals Light dynamics and free-to-grow standards in aspen-dominated mixedwood forests

2002 ◽  
Vol 78 (1) ◽  
pp. 137-145 ◽  
Author(s):  
Victor J Lieffers ◽  
Bradley D Pinno ◽  
Kenneth J Stadt
Keyword(s):  
Leaf Area Index ◽  
Key Words ◽  
Leaf Area ◽  
Light Transmission ◽  
Stand Density ◽  
Canopy Gaps ◽  
Light Competition ◽  
Area Index ◽  
Mixedwood Forests ◽  
Key Words Competition

This study examines light competition between aspen and spruce during the sequence of aspen development. Leaf area index and light transmission were measured or estimated for aspen stands from 2 to 125 years old. Light transmission was lowest at 15-25 years, and in some stands, transmission was less than 5% of above-canopy light. Hypothetical aspen stands with various stem configurations and heights were developed, and positions were identified that would meet or fail Alberta free-to-grow (FTG) standards. Light transmission was estimated at each position with the MIXLIGHT forest light simulator. Positions in canopy gaps or at the northern sides of canopy gaps had higher light. In general, however, there was little difference in available light between positions that met or failed FTG criteria. Stand density and size of aspen trees appears to be a better index to predict light transmission and spruce success in juvenile aspen stands than current FTG criteria. Key words: competition, free to grow, hardwood, spruce, light

scholarly journals A Mixed Data-Based Deep Neural Network to Estimate Leaf Area Index in Wheat Breeding Trials

Agronomy ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 175 ◽  
Author(s):  
Orly Enrique Apolo-Apolo ◽  
Manuel Pérez-Ruiz ◽  
Jorge Martínez-Guanter ◽  
Gregorio Egea
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
High Throughput ◽  
Model Performance ◽  
Wheat Breeding ◽  
Plant Phenotyping ◽  
Indirect Methods ◽  
Area Index ◽  
Model Based ◽  
Recent Emergence

Remote and non-destructive estimation of leaf area index (LAI) has been a challenge in the last few decades as the direct and indirect methods available are laborious and time-consuming. The recent emergence of high-throughput plant phenotyping platforms has increased the need to develop new phenotyping tools for better decision-making by breeders. In this paper, a novel model based on artificial intelligence algorithms and nadir-view red green blue (RGB) images taken from a terrestrial high throughput phenotyping platform is presented. The model mixes numerical data collected in a wheat breeding field and visual features extracted from the images to make rapid and accurate LAI estimations. Model-based LAI estimations were validated against LAI measurements determined non-destructively using an allometric relationship obtained in this study. The model performance was also compared with LAI estimates obtained by other classical indirect methods based on bottom-up hemispherical images and gaps fraction theory. Model-based LAI estimations were highly correlated with ground-truth LAI. The model performance was slightly better than that of the hemispherical image-based method, which tended to underestimate LAI. These results show the great potential of the developed model for near real-time LAI estimation, which can be further improved in the future by increasing the dataset used to train the model.

scholarly journals Comparative analysis of different retrieval methods for mapping grassland leaf area index using airborne imaging spectroscopy

2015 ◽  
Vol 43 ◽  
pp. 19-31 ◽  
Author(s):  
Clement Atzberger ◽  
Roshanak Darvishzadeh ◽  
Markus Immitzer ◽  
Martin Schlerf ◽  
Andrew Skidmore ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Imaging Spectroscopy ◽  
Area Index ◽  
Airborne Imaging

scholarly journals Comparative analysis of GF-1, HJ-1, and Landsat-8 data for estimating the leaf area index of winter wheat

2017 ◽  
Vol 16 (2) ◽  
pp. 266-285 ◽  
Author(s):  
He LI ◽  
Zhong-xin CHEN ◽  
Zhi-wei JIANG ◽  
Wen-bin WU ◽  
Jian-qiang REN ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Winter Wheat ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Landsat 8 ◽  
Area Index
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