scholarly journals Identifikasi Nilai Konstanta Bentuk Daun untuk Pengukuran Luas Daun Metode Panjang Kali Lebar pada Tanaman Hortikultura di Tanah Gambut

2015 ◽  
Vol 14 (2) ◽  
pp. 139-146 ◽  
Author(s):  
Djoko Eko Hadi Susilo
Keyword(s):  
Plant Growth ◽  
Leaf Area ◽  
Low Cost ◽  
Peat Soil ◽  
Leaf Shape ◽  
Area Measurement ◽  
Leaf Lamina ◽  
Graph Paper ◽  
Non Destructive ◽  
Destructive Methods

The purpose of this research is to know and identification constanta value of leaf shape for leaf area measurement using length cross width of leaf of horticulture plant in peat soil. This research was conducted from February to May 2015 in Palangka Raya City, Central Kalimantan. This research implemented by observed of leaf from 32 species of horticulture plant in peat soil. In every species, was observed 30 leaf (lamina). Measuring leaf area absolutelly using on grid paper or millimeter graph paper, and than measuring ratio if leaf area is can finding using length cross width of leaf. Result of this research, showed that 32 species of horticulture plant in peat soil have regularity of leaf shape and can identified of constanta value for leaf area measurement using length cross width of leaf.Leaf area measurement using length cross width of leaf is alternative technique because easier (simple), quick (fast), low cost, and accurate to plant growth analysis for non-destructive methods. Leaf area measurement not explain plant growth only, but many purposes was can resulted from it. This research suggested to identification of constanta value of leaf shape for another species horticulture plant in peat soil cultivation.

A simple and low-cost method for leaf area measurement of detached leaves

1997 ◽  
Vol 33 (01) ◽  
pp. 65-72 ◽  
Author(s):  
J. T. Korva ◽  
G. A. Forbes
Keyword(s):  
Solanum Tuberosum ◽  
Leaf Area ◽  
Low Cost ◽  
Electronic Equipment ◽  
New Method ◽  
Area Measurement ◽  
Water Spray ◽  
Spray Method ◽  
Detached Leaves ◽  
Highly Correlated

A technique for leaf area measurement utilizing water spray as an inexpensive substitute for electronic equipment was developed and tested with leaves of potato (Solanum tuberosum L.). The leaf areas measured by the spray method were highly correlated with those measured by an electronic area meter. Measurements of leaf area obtained by the spray method were significantly more highly correlated with those obtained by the area meter than were the measurements of dry weights. The main advantages of the new method are precision, accuracy and immediate results at a low cost.

scholarly journals A Simple, Cost-Effective Method for Leaf Area Estimation

2011 ◽  
Vol 2011 ◽  
pp. 1-6 ◽  
Author(s):  
S. K. Pandey ◽  
Hema Singh
Keyword(s):  
Leaf Area ◽  
Cost Effective ◽  
Botanical Garden ◽  
Area Estimation ◽  
Graph Paper ◽  
Cost Effective Method ◽  
Cost Effective Alternative ◽  
Cost Efficient ◽  
Non Destructive ◽  
Paper Method

Easy, accurate, inexpensive, and nondestructive methods to determine individual leaf area of plants are a useful tool in physiological and agronomic studies. This paper introduces a cost-effective alternative (called here millimeter graph paper method) for standard electronic leaf area meter, using a millimeter graph paper. Investigations were carried out during August–October, 2009-2010, on 33 species, in the Botanical garden of the Banaras Hindu University at Varanasi, India. Estimates of leaf area were obtained by the equation, leaf area (cm2) = x/y, where x is the weight (g) of the area covered by the leaf outline on a millimeter graph paper, and y is the weight of one cm2 of the same graph paper. These estimates were then compared with destructive measurements obtained through a leaf area meter; the two sets of estimates were significantly and linearly related with each other, and hence the millimeter graph paper method can be used for estimating leaf area in lieu of leaf area meter. The important characteristics of this cost-efficient technique are its easiness and suitability for precise, non-destructive estimates. This model can estimate accurately the leaf area of plants in many experiments without the use of any expensive instruments.

scholarly journals Digital image processing methods for estimating leaf area of cucumber plants

2022 ◽  
Vol 25 (1) ◽  
pp. 317
Author(s):  
Uoc Quang Ngo ◽  
Duong Tri Ngo ◽  
Hoc Thai Nguyen ◽  
Thanh Dang Bui
Keyword(s):  
Plant Growth ◽  
Leaf Area ◽  
Negative Impact ◽  
High Accuracy ◽  
Growth Monitoring ◽  
Accuracy Rate ◽  
Outdoor Scenes ◽  
Artificial Intelligence Technology ◽  
Rgb Images ◽  
Non Destructive

Increasingly <span>emerging technologies in agriculture such as computer vision, artificial intelligence technology, not only make it possible to increase production. To minimize the negative impact on climate and the environment but also to conserve resources. A key task of these technologies is to monitor the growth of plants online with a high accuracy rate and in non-destructive manners. It is known that leaf area (LA) is one of the most important growth indexes in plant growth monitoring system. Unfortunately, to estimate the LA in natural outdoor scenes (the presence of occlusion or overlap area) with a high accuracy rate is not easy and it still remains a big challenge in eco-physiological studies. In this paper, two accurate and non-destructive approaches for estimating the LA were proposed with top-view and side-view images, respectively. The proposed approaches successfully extract the skeleton of cucumber plants in red, green, and blue (RGB) images and estimate the LA of cucumber plants with high precision. The results were validated by comparing with manual measurements. The experimental results of our proposed algorithms achieve 97.64% accuracy in leaf segmentation, and the relative error in LA estimation varies from 3.76% to 13.00%, which could meet the requirements of plant growth monitoring </span>systems.

scholarly journals Non-Destructive Measurement of Three-Dimensional Plants Based on Point Cloud

Plants ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 571 ◽  
Author(s):  
Yawei Wang ◽  
Yifei Chen
Keyword(s):  
Plant Growth ◽  
Point Cloud ◽  
Growth Parameters ◽  
Leaf Shape ◽  
Three Dimensional ◽  
3D Point Cloud ◽  
Surface Integral ◽  
Plant Model ◽  
Destructive Measurement ◽  
Non Destructive

In agriculture, information about the spatial distribution of plant growth is valuable for applications. Quantitative study of the characteristics of plants plays an important role in the plants’ growth and development research, and non-destructive measurement of the height of plants based on machine vision technology is one of the difficulties. We propose a methodology for three-dimensional reconstruction under growing plants by Kinect v2.0 and explored the measure growth parameters based on three-dimensional (3D) point cloud in this paper. The strategy includes three steps—firstly, preprocessing 3D point cloud data, completing the 3D plant registration through point cloud outlier filtering and surface smooth method; secondly, using the locally convex connected patches method to segment the leaves and stem from the plant model; extracting the feature boundary points from the leaf point cloud, and using the contour extraction algorithm to get the feature boundary lines; finally, calculating the length, width of the leaf by Euclidean distance, and the area of the leaf by surface integral method, measuring the height of plant using the vertical distance technology. The results show that the automatic extraction scheme of plant information is effective and the measurement accuracy meets the need of measurement standard. The established 3D plant model is the key to study the whole plant information, which reduces the inaccuracy of occlusion to the description of leaf shape and conducive to the study of the real plant growth status.

scholarly journals Non-destructive and Destructive Methods to Determine the Leaf Area of Zucchini

2020 ◽  
Vol 8 (3) ◽  
pp. 295
Author(s):  
Adriano Bicioni Pacheco ◽  
Jéssica Garcia Nascimento ◽  
Larissa Brêtas Moura ◽  
Tárcio Rocha Lopes ◽  
Sergio Nascimento Duarte ◽  
...  
Keyword(s):  
Leaf Area ◽  
Prediction Models ◽  
Standard Procedure ◽  
Efficiency Index ◽  
Estimation Model ◽  
Statistical Parameters ◽  
Important Indicator ◽  
Area Estimation ◽  
Non Destructive ◽  
Destructive Methods

Leaf area estimation is a very important indicator in studies related to plant anatomy, morphology and physiology, and in many cases, it is a fundamental criterion to understand plant response to input conditions. Although there are leaf area prediction models have been produced for some plant species, a leaf area estimation model has not yet been developed for the zucchini. The objective of this paper was to determine the leaf area based on destructive and non-destructive methods for zucchini. The accuracy of measurement methods was evaluated and compared to determinations of the leaf area by the scanning integration method (LICOR equipment LI 3100C), considered as standard procedure. Non-destructive methods consisted of digital photography and measurement of leaf dimensions (width and length) based on ImageJ software. The destructive methods used were a) leaf area integrator LI-3100C, b) determination of leaf mass and c) weighing of leaf discs punched from the leaves. According to statistical parameters that evaluate the performance of the analyzed methods: determination coefficient (R2), Pearson (r) correlation coefficient, Willmott agreement index (d) and Camargo and Sentelhas performance index (c) the parameters presented values higher than 0.8820, classifying the methods as very good, whereas the modeling efficiency index (NSE) and the percentage of bias (PBIAS) also classified the methods as very good (0.87≤NSE≤0.99; -4.80≤PBIAS≤1.40), except the ImageJ method without correction (NSE=0.77; PBIAS = -22.70).

scholarly journals Allometric models for non-destructive leaf area measurement of stevia: an in depth and complete analysis

2021 ◽  
Vol 39 (2) ◽  
pp. 205-215
Author(s):  
Israel A Hernández-Fernandéz ◽  
Alfredo Jarma-Orozco ◽  
Marcelo F Pompelli
Keyword(s):  
Leaf Area ◽  
Linear Models ◽  
Stevia Rebaudiana ◽  
Leaf Length ◽  
Area Measurement ◽  
Complete Analysis ◽  
Statistical Criterion ◽  
Power Models ◽  
Non Destructive ◽  
Statistical Criteria

ABSTRACT Leaf area measurement is pivotal for plant physiologists. Hence, accurate measurement of their leaf area is incredibly relevant in agronomic terms. The plant Stevia rebaudiana is a sucrose-free plant species that is now vital to the global production of sucrose-free foods. Here, we estimated S. rebaudiana leaf area using a nondestructive methodology comprising allometric equations. Through leaf length (L), leaf width (W), and/or their product (LW) the leaf area was determined. One thousand leaves were sampled from four distinct S. rebaudiana genotypes for model construction. Linear or power models were generated, and the best equation was selected using a statistical criterion. The statistical criteria indicated that the linear models best suited all genotypes tested, included a function of LW, exhibited increased stability, and precisely estimated coefficients. ANOVA revealed that both generalized and combined equations were feasible. Nevertheless, grouping all genotypes into a single model was not possible as the genotype leaf architectures were very dissimilar.

scholarly journals Non-destructive Estimation of Spinach Leaf Area: Image Processing and Artificial Neural Network Based Approach

2020 ◽  
pp. 146-153
Author(s):  
Naveen Kumar Mahanti ◽  
Upendar Konga ◽  
Subir Kumar Chakraborty ◽  
V. Bhushana Babu
Keyword(s):  
Image Processing ◽  
Leaf Area ◽  
Linear Models ◽  
Measurement Techniques ◽  
Area Measurement ◽  
Image Processing Techniques ◽  
Spinach Leaf ◽  
Processing Techniques ◽  
Non Destructive ◽  
Better Than

Leaf area (LA) measurement provides valuable key information in understanding the growth and physiology of a plant. Simple, accurate and non-destructive methods are inevitable for leaf area estimation. These methods are important for physiological and agronomic studies. However, the major limitations of existing leaf area measurement techniques are destructive in nature and time consuming. Therefore, the objective of the present work is to develop ANN and linear regression models along with image processing techniques to estimate spinach leaf area making use of leaf width (LW) and length (LL) and comparison of developed models performance based on the statistical parameters. The spinach leaves were grown under different nitrogen fertilizer doses (0, 50, 100, 150, 200, 250, 300, 350 and 400 kg N/ha). The morphological parameters length (LL), width (LW) and area (LA) of leaves were measured using an image-processing software. The performance LA= -0.66+0.64 (LL × LW) (R2 = 0.98, RMSE = 3.25 cm2) equation was better than the other linear models. The performance of the ANN model (R2 = 0.99, RMSE = 3.10 cm2) was better than all other linear models. Therefore, developed models along with image processing techniques can be used as a non-destructive technique for estimation of spinach leaf area.

scholarly journals Non-destructive measurement for estimating leaf area of Bellis perennis

2017 ◽  
Vol 10 (1) ◽  
pp. 58-64
Author(s):  
Indera Sakti Nasution
Keyword(s):  
Image Processing ◽  
Plant Growth ◽  
Leaf Area ◽  
Color Space ◽  
Morphological Operations ◽  
Connected Component ◽  
Kinect Camera ◽  
Growth Estimation ◽  
Destructive Measurement ◽  
Non Destructive

Non-destructive measurement of approaches of modeling can be very convenient and useful for plant growth estimation. This study, digital image processing was evaluated as a non-destructive technique to estimate leaf area of Bellis perennis. The plant samples were growing in the greenhouse and the images were taken every day using Kinect camera. The proposed method used combination of L*a*b* color space, Otsu’s thresholding, morphological operations and connected component analysis to estimate leaf area of Bellis perennis. L* channel was used to distinguish the leaves and background. Calibration area uses a pot of known area in each image as a scale to calibrate the leaves area. The results show that the algorithm is able to separate leaf pixels from soil or pot backgrounds, and also allow it to be implemented in greenhouse automatically. This algorithm can be used for other plants in assumption that there is not too much leaf overlapped during measurement.

Sign in / Sign up

Export Citation Format

Share Document