ESTIMATION OF RICE PLANT HEIGHT AND STEM NUMBER BASED ON LASER-SCANNED POINT CLOUD DATA ANALYSIS By Phan Thi Anh Thu A Dissertation Submitted to the Graduate School of Engineering of Nagaoka University of Technology for the Degree of Doctor of Engineering Energy and Environment Science Program Nagaoka University of Technology, Japan 2017 Table of contents Table of contents. i List of figures. iii List of Table. vi Chapter 1: INTRODUCTION.1 The importance of rice .2 Rice growth phases .3 The main factors effect on rice growth .4 Rice growth parameters measurement methods .5 Laser scanner in precise agriculture.
8 Chapter 2: DATA ACQUISITION .2 Laser scanner instrument. 16 Chapter 3: METHOD FOR ESTIMATING RICE PLANT HEIGHT WITHOUT GROUND SURFACE DETECTION USING LASER SCANNER MEASUREMENT. 29 Chapter 4: FUNDAMENTAL STUDY FOR ESTIMATING RICE PLANT STEM NUMBER USING LASER SCANNER MEASUREMENTS .1 Basic Concepts of Estimating Rice Plant Stem Number from Laser Data under Ideal Conditions (Good Laser Data) .2 Conceptual application using the observed laser data .3 Limitations and future works. 62 ii List of figures Fig 1.1: Apparent calorie intake and contribution from rice of Countries where rice represents more than 20 percent of calorie intake, 2000-2002 average.2: Rice growth phases and stages.
Source: Arkansas rice production handbook, 2012 .3: Research technicians is measuring rice plant height and stem number in the field .1: Schematic of the field experiment setup for measuring the 3D laser point cloud in 2013 and 2014. Arrows indicate row orientation. Row orientation is not considered in plot 3.2: Field observations were collected by laser scanners (a) SICK LMS 200 and (b) UTM 30LX in 2014 and 2016, respectively. Both lasers were hung approximately 3 m above the paddy field surface and could move along the rail under motorized power.3: Cultivation calendar of special cultivated rice Koshihikari.
The studied period is from middle June to end of July every year and is identified inside the red rectangle. In this period, plant height increases from 12 cm to 80 cm and stem number increases from 60 stems/m2 to 500 stems/m2. Source: http://www.jp/contents/1_einou/agrinet /310undou/2012/06koshihikari.4: The measured physical parameters of rice plant in (a) average rice plant height (𝐻) and (b) rice plant stem number (𝑆) with their standard deviation in three growing seasons .5: Illustration of point cloud data (a) SICK LMS 200 point cloud of rice canopy in nadir viewing and (b) Point cloud capture with LIDAR sensor (Velodyne); Source: https://www.net/news/velodyne-releases-powerful-lidar/ .6: Plot 3 target area in 2014.7: Histograms of 3D point cloud data from plot 2, collected in three years. The rows show the results from 2013 (a–g), 2014 (h–n), and 2016 (o–u) Red dashed lines show the ground position after harvesting the crop.8: The likelihood of SICK LMS 200 laser pulses reaching a ground surface covered by water.
Images a) and b) are an infrared image and an intensity image collected by SICK LMS 200 on June 21st, 2013, respectively. For this, potted rice plants were put into clear water, and the tops of the pots at a water depth of around 4 cm could be recognized from the intensity image. In contrast, c) the paddy field was covered by turbid water with many bubbles on the iii water surface on June 18th, 2014, and d) the paddy field was not covered by water on June 24th, 2014 .1: Determination of the top and bottom location, where 𝑝𝑡 and 𝑝𝑏 are the closest percentiles to the top and bottom of the rice plant, respectively; 𝐷𝑡 and 𝐷𝑏 are the vertical distances from the scanning point to the installation height of the laser scanner at 𝑝𝑡 and 𝑝𝑏.2: Vertical distance at various percentile ranks. Columns show results from (a and d) densely planted plots, (b, e and g) moderate density plots, and (c and f) sparse plots.
Red dashed lines show the position of the ground surface after harvesting the crop.3: Plots of 𝑟𝐷 against measured rice plant height. The rows show the results from 2013 (a–c), 2014 (d–f), and 2016 (g–i). The columns show the results with the reference position computed at 70th (a, d, g), 80th (b, e, h), and 95th (c, f, i) percentile ranks. Red dash-dotted lines show the regression lines.4: Plots of 𝑟𝐷 against measured rice plant height, the regression lines and achieved 𝑅𝑀𝑆𝐸 (a) show the result of a combination of the first two years and (b) shows the result of a combination of three years .1: Spatial volume (𝑉𝑠) between the ground and the rice canopy surface detected by the laser: Cross-section of voxel representation of 𝑉𝑠.3: Calculation of 𝑛𝑉𝑠 from laser scanning data.
(a) Top and bottom (close to the ground surface) positions of the rice plant used for normalizing 𝐷. The corresponding laser data are then divided into many layers for 𝑛𝑉𝑠 computaion. (b) Volumes (in voxels) of scanning points corresponding to each layer, (c) the computation of 𝑛𝑉𝑘 from the scanning points, and (d) the relationship between 𝑛𝑉𝑠 and 𝑛𝑉𝑠𝑚𝑎𝑥.4: The 𝑛𝐷 histogram shape of the third observation of plot 2 in growing season of 2014 with divided layers of (a) 𝑚 = 5, (b) 𝑚 = 10, (c) 𝑚 = 50, and (d) 𝑚 = 100.5: Distributions of original and normalized data of seven observations collected at different times of the growing season in (a) 2014 and (e) 2016. The observation date is clearly displayed in Table 2.
The planting density was 15.m-2 and the planting direction was perpendicular. Rows show the results from 2014 (a–d) and 2016 (e–h). Columns show the original data (a, e) and the 𝑛𝐷 values for different bottom positions of the rice plant; 𝐷95 (b, f), 𝐷80 (c, g), and 𝐷70 (d, h).6: These charts show the relationship between relative spatial volume and stem number in 2013 with m=100. The columns show the results with the various determined bottom position of 𝐷70, 𝐷80 , and 𝐷95.
The rows show the results from plot 1 (a-c)), plot 2 (d-f), plot 3 (g-i), plot 4 (j-l) and plot 5 (m-o).7: These charts show the relationship between relative spatial volume and stem number in 2014 with m=100. The columns show the results with the various determined bottom position of 𝐷70, 𝐷80 , and 𝐷95. The rows show the results from plot 1 (a-c)), plot 2 (d-f), plot 3 (g-i), plot 4 (j-l) and plot 5 (m-o).8: These charts show the relationship between relative spatial volume and stem number in 2016 with m=100. The columns show the results with the various determined bottom position of 𝐷70, 𝐷80 , and 𝐷95.
The rows show the results from target area 1 (a-c)) and target area 2 (d-f).9: Estimated rice plant stem numbers during the growing season of 2013 with 𝑚=100. Rows show the results from plot 1 (a–c), plot 2 (d–f), plot 3 (g–i), plot 4 (j–l), and plot 5 (m– o). Columns show the results for different bottom positions of the rice plants; 𝐷70 (a, d, g, j, m), 𝐷80 (b, e, h, k, m), and 𝐷95 (c, f, i, l, o).10: Estimated rice plant stem numbers during the growing season of 2014 with 𝑚=100. Rows show the results from plot 1 (a–c), plot 2 (d–f), plot 3 (g–i), plot 4 (j–l), and plot 5 (m– o).
Columns show the results for different bottom positions of the rice plants; 𝐷70 (a, d, g, j, m), 𝐷80 (b, e, h, k, m), and 𝐷95 (c, f, i, l, o).11: Estimated rice plant stem numbers during the growing season of 2016. Rows show the results for different numbers of layers; 𝑚 = 500 (a–c), 𝑚 = 100 (d–f), and 𝑚 = 10 (g–i). Columns show the results for different bottom positions of the rice plants; 𝐷70 (a, d, g), 𝐷80 (b, e, h), and 𝐷95 (c, f, i). Rows show the results in plot 2 for different numbers of layers; 𝑚 = 500 (a–c), 𝑚 = 100 (d–f), and 𝑚 = 10 (g–i).
Columns show the results for different bottom positions of the rice plants; 𝐷70 (a, d, g), 𝐷80 (b, e, h), and 𝐷95 (c, f, i). 53 v List of Table Table 2.1: Rice planting densities and geometries during the growing seasons of 2013 and 2014.2: List of field observation data .1: Computed allometric parameters for the scaling exponential functions that predict the rice plant stem number in moderate density plots.2: Effect of layer number and bottom position of rice plant on the precision of the estimated stem number in a moderate density plot (plot 2) during the 2014 and 2016 growing seasons.3: Effect of planting density and geometry on the precision of the estimated stem number in 2013 with 𝐷𝑏𝑜𝑡𝑡𝑜𝑚 = 𝐷95 .4: Effect of planting density and geometry on the precision of the estimated stem number in 2014 with 𝐷𝑏𝑜𝑡𝑡𝑜𝑚 = 𝐷80. 47 vi Chapter 1: Introduction Chapter 1: INTRODUCTION 1.1 The importance of rice For food security, a critical issue in the world, the most important thing is to have enough food to provide the daily life of the human. In Asian countries, rice is the main food crop.
The population needs rice for survival because they consume rice for every daily meal (Figure 1. The management of rice crop is necessary for national food security and political stability. Moreover, rice is the main income of people living in the agricultural area. Therefore, the social security is directly affected by rice production.
According to a report of FAO in 2000, rice production got the problem of declining rate of growth in yields, depletion of natural resources, labor shortages, institutional limitations and environmental pollution. By applying new rice variety and fertilizer technology, the increase of rice yield leads to the growth in rice production. Nowadays, the consumers pay more attention to rice quality. They demand for safe, affordable, and high-quality rice.
Because of the importance of rice, rice growth must be controlled by applying technologies to reduce labor costs and achieve the optimized yield with good quality. Thus, it is necessary to monitor the rice growth during the rice growing season.1: Apparent calorie intake and contribution from rice of Countries where rice represents more than 20 percent of calorie intake, 2000-2002 average. Source: FAO 1 Chapter 1: Introduction 1.2 Rice growth phases Rice growth includes many stages from seeding to harvesting. According to Arkansas rice production handbook, 2012, rice growth can be divided into three main phases of development including vegetative phase, reproduction phase and ripening phase or maturation phase (Figure 1.
The rice growth duration depends on the variety and the environment.2: Rice growth phases and stages. Source: Arkansas rice production handbook, 2012 2 Chapter 1: Introduction The vegetative phase starts from seed germination stage and ends at tillering stage. This phase is characterized by a gradual increase in plant height, tillering activity, and more leaves. During this phase, the rice plant almost stands upright and the number of tillers (stems) increase in a sigmoidal-shaped curve.
After the maximum tiller number is reached the tiller number decreases, whereas rice plant height continues to increase with a slower rate. From this time, no more effective tillers are produced. Therefore, the yield component, potential panicles per unit area, is determined. The reproduction phase starts at panicle initiation stage and ends at flowering stage.
During this period, the culm elongates, tiller number lightly decrease, panicle emerges from the stem. The heading date, which is used to predict draining and harvest date, is identified when the 50% of panicles are exserted from the boot. Flowering begins after panicles have fully emerged from the boot. The ripening phase is characterized by grain growth.
Solar intensity and temperature also effect on this period. The size and weight of rice grain will increase. Moreover, the color of grain will turn to gold or straw color at maturity, whereas the rice leaves begin to senesce.3 The main factors effect on rice growth Rice is almost grown in many humid tropical and subtropical areas.
