scholarly journals Leaf area estimation of medium size plants using optical metrology

2013 ◽  
Vol 17 (6) ◽  
pp. 595-601 ◽  
Author(s):  
Kleber M. Ribeiro ◽  
Roberto A. Braga ◽  
Myriane S. Scalco ◽  
Graham W. Horgan
Keyword(s):  
Leaf Area ◽  
Direct Methods ◽  
Optical Metrology ◽  
Medium Size ◽  
Coffee Plant ◽  
Indirect Methods ◽  
Area Index ◽  
The Subject ◽  
Non Destructive ◽  
Commercial Equipment

The total leaf area (TLA) estimation is an important feature of the crops and their assessment a challenge, since the direct methods of obtaining it are destructive and time consuming. Non-destructive methods have been explored to obtain the TLA by indirect approaches, in turn creating other features, as the leaf area index. The development of non-destructive technology to access the TLA of a plant has been the subject of much research, and the optical metrology is an promising approach. In this work, some indirect methods associated with optical approaches were evaluated as an alternative to obtain the TLA of the coffee plant. Commercial equipment were used, such as a camera with a fish eye lens and lux meters, associated to the sizes of the canopies were tested and compared to another non-destructive method and with methods proposed in the literature. The association between production and the TLA estimated was also evaluated. The results showed that the commercial equipment, generally used in forestry, was not the best approach in coffee plants, and that the methods related to the size and lux values of the plants were the best alternatives to estimate the TLA of the coffee plant.

scholarly journals Study of a Non-destructive Method for Estimating the Leaf Area Index in Vegetable Crops Using Digital Images

HortScience ◽  
2010 ◽  
Vol 45 (10) ◽  
pp. 1459-1463 ◽  
Author(s):  
Carlos Campillo ◽  
M.I. García ◽  
C. Daza ◽  
M.H. Prieto
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Digital Images ◽  
Direct Methods ◽  
Vegetable Crops ◽  
Simple Method ◽  
Area Index ◽  
Skilled Operator ◽  
Significant Area ◽  
Non Destructive

One estimate of a crop's ability to capture light energy is the leaf area index (LAI), which is defined as the proportion of leaf area per unit of land area. Direct methods of estimation involve determining the LAI in a significant area of cultivation and individually measuring the leaf surface, which is often tedious. The objective of this study was to develop a cheap and simple method for determining LAI based on the percentage of groundcover (PGC) measured in two vegetable crops with notable differences in leaf type and plant architecture using digital images obtained with a commercial camera and applying open-source software. The PGC values obtained from digital image analysis in cauliflower and tomato crops and the measurements of LAI obtained by destructive sampling (measured with a planimeter) allowed us to obtain a relationship between two variables (r2 > 0.88). In all cases, the extinction coefficients were obtained from comparisons of LAI and PGC with values ranging between 0.75 and 0.85 for processing tomato and 0.60 and 0.70 for cauliflower. The method used allows non-destructive estimations of LAI that are comparable with other more expensive indirect methods that require a skilled operator.

scholarly journals A comparison of different methods for assessing leaf area index in four canopy types

2019 ◽  
Vol 65 (2) ◽  
pp. 67-80 ◽  
Author(s):  
Cristina Ariza-Carricondo ◽  
Francesca Di Mauro ◽  
Maarten Op de Beeck ◽  
Marilyn Roland ◽  
Bert Gielen ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Direct Methods ◽  
Leaf Angle ◽  
Pedunculate Oak ◽  
Angle Distribution ◽  
Indirect Methods ◽  
Area Index ◽  
Short Rotation ◽  
Maize Field

Abstract The agreement of Leaf Area Index (LAI) assessments from three indirect methods, i.e. the LAI–2200 Plant Canopy Analyzer, the SS1 SunScan Canopy Analysis System and Digital Hemispherical Photography (DHP) was evaluated for four canopy types, i.e. a short rotation coppice plantation (SRC) with poplar, a Scots pine stand, a Pedunculate oak stand and a maize field. In the SRC and in the maize field, the indirect measurements were compared with direct measurements (litter fall and harvesting). In the low LAI range (0 to 2) the discrepancies of the SS1 were partly explained by the inability to properly account for clumping and the uncertainty of the ellipsoidal leaf angle distribution parameter. The higher values for SS1 in the medium (2 to 6) to high (6 to 8) ranges might be explained by gap fraction saturation for LAI–2200 and DHP above certain values. Wood area index –understood as the woody light-blocking elements from the canopy with respect to diameter growth– accounted for overestimation by all indirect methods when compared to direct methods in the SRC. The inter-comparison of the three indirect methods in the four canopy types showed a general agreement for all methods in the medium LAI range (2 to 6). LAI–2200 and DHP revealed the best agreement among the indirect methods along the entire range of LAI (0 to 8) in all canopy types. SS1 showed some discrepancies with the LAI–2200 and DHP at low (0 to 2) and high ranges of LAI (6 to 8).

scholarly journals A PROPOSED METHODOLOGY FOR THE CORRECTION OF THE LEAF AREA INDEX MEASURED WITH A CEPTOMETER FOR PINUS AND EUCALYPTUS FORESTS

2016 ◽  
Vol 40 (5) ◽  
pp. 845-854 ◽  
Author(s):  
Domingos Mendes Lopes ◽  
Nigel Walford ◽  
Helder Viana ◽  
Carlos Roberto Sette Junior
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Correction Factor ◽  
Basal Area ◽  
Allometric Equations ◽  
Nutrient Cycle ◽  
Area Index ◽  
Physiological Processes ◽  
The Difference ◽  
Non Destructive

ABSTRACT Leaf area index (LAI) is an important parameter controlling many biological and physiological processes associated with vegetation on the Earth's surface, such as photosynthesis, respiration, transpiration, carbon and nutrient cycle and rainfall interception. LAI can be measured indirectly by sunfleck ceptometers in an easy and non-destructive way but this practical methodology tends to underestimated when measured by these instruments. Trying to correct this underestimation, some previous studies heave proposed the multiplication of the observed LAI value by a constant correction factor. The assumption of this work is LAI obtained from the allometric equations are not so problematic and can be used as a reference LAI to develop a new methodology to correct the ceptometer one. This new methodology indicates that the bias (the difference between the ceptometer and the reference LAI) is estimated as a function of the basal area per unit ground area and that bias is summed to the measured value. This study has proved that while the measured Pinus LAI needs a correction, there is no need for that correction for the Eucalyptus LAI. However, even for this last specie the proposed methodology gives closer estimations to the real LAI values.

Canopy Dynamics of Eucalyptus Maculata Hook. I. Distribution and Dynamics of Leaf Populations

1984 ◽  
Vol 32 (4) ◽  
pp. 387 ◽  
Author(s):  
EW Pook
Keyword(s):  
Water Supply ◽  
Leaf Area ◽  
Shoot Growth ◽  
Temperature Limit ◽  
Leaf Fall ◽  
Leaf Production ◽  
Area Index ◽  
Average Size ◽  
Non Destructive

The canopy dynamics of a regenerated 16-year-old stand of pole and sapling E. maculata were studied for 2½ years by repetitive non-destructive measurements in tree crowns accessed from a 20 m high scaffold tower. Average canopy leaf area density over a sample plot of 36 m2 was 0.23 m2 m-3 at a leaf area index of 4.3. Some 75% of leaf area was held in the canopies of overstorey eucalypts above 10 m in height. Average size of leaves increased gradually from top to bottom of tree canopies. Foliage production was usually concentrated in the upper crowns of trees where there was a higher proportion of active shoots, more frequent growth flushes and more rapid turnover of leaves than in lower canopy layers. Leaf area in the upper canopy fluctuated widely but increased in the long term, in mid canopy was more or less maintained and in lowest canopy declined. Crops of developing flower buds present on uppermost branches delayed and/or reduced shoot growth. Foliage production occurred in all months of the year. There was a unimodal annual rhythm of growth rate reaching a maximum in summer and a minimum in winter. Variable water supply, however, influenced production to peak in spring, summer or autumn. No shoot growth occurs in E. maculata at Kioloa when daily mean temperature (averaged for weekly intervals) falls below c. 10½C in winter. An upper temperature limit for growth could not be defined. The species apparently lacks dormancy mechanisms. Shoot growth is 'opportunistic' and occurs whenever environmental conditions are favourable. Patterns of leaf production and leaf fall were variable but peaks showed a general synchrony. Leaf fall, however, tended to lag behind leaf production. Leaves of all ages were shed but main losses were from older cohorts. Some 49% (s.d.±18%) of new leaves were lost while still small or immature, mainly during periods of vigorous shoot growth or low water supply. Browse of immature foliage was light. Normal senescence and leaf fall accounted for almost the entire loss of mature foliage.

scholarly journals A non-destructive method for estimating onion leaf area

2015 ◽  
Vol 54 (1) ◽  
Author(s):  
J.I. Córcoles ◽  
A. Domínguez ◽  
M.A. Moreno ◽  
J.F. Ortega ◽  
J.A. de Juan
Keyword(s):  
Leaf Area ◽  
Crop Production ◽  
Biomass Accumulation ◽  
Irrigation Season ◽  
Indirect Methods ◽  
Agronomic Management ◽  
Non Destructive ◽  
Direct And Indirect Methods ◽  
Sampling Event ◽  
Experimental Plots

AbstractLeaf area is one of the most important parameters for characterizing crop growth and development, and its measurement is useful for examining the effects of agronomic management on crop production. It is related to interception of radiation, photosynthesis, biomass accumulation, transpiration and gas exchange in crop canopies. Several direct and indirect methods have been developed for determining leaf area. The aim of this study is to develop an indirect method, based on the use of a mathematical model, to compute leaf area in an onion crop using non-destructive measurements with the condition that the model must be practical and useful as a Decision Support System tool to improve crop management. A field experiment was conducted in a 4.75 ha commercial onion plot irrigated with a centre pivot system in Aguas Nuevas (Albacete, Spain), during the 2010 irrigation season. To determine onion crop leaf area in the laboratory, the crop was sampled on four occasions between 15 June and 15 September. At each sampling event, eight experimental plots of 1 m

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.

Sign in / Sign up

Export Citation Format

Share Document