Estimating Paddy Rice Leaf Area Index with Fixed Point Continuous Observation of Near Infrared Reflectance Using a Calibrated Digital Camera

Shibayama, Michio; Sakamoto, Toshihiro; Takada, Eiji; Inoue, Akihiro; Morita, Katsusada; Takahashi, Wataru; Kimura, Akihiko

doi:10.1626/pps.14.30

Cited by 35 publications

(30 citation statements)

References 48 publications

(50 reference statements)

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“…The green LAI, defined as the one-sided green leaf area per unit horizontal ground area [4], is directly related to the growth status of crops [5] and largely influences the spectral reflectance of vegetation canopies. Thus, for site-specific crop management, it is crucial to be able to estimate LAI in a timely and nondestructive manner using remote sensing, since the site-specific crop management requires both high-quality crop production and the minimization of adverse environmental effects via better fertilizer management [2,[6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…Recently, Viña et al [10] found that chlorophyll indices (the red-edge chlorophyll index [CIred-edge] and the green chlorophyll index [CIgreen]), devised for chlorophyll assessment at the leaf scale [18], are more accurate for LAI assessments of maize and soybean crops than for the above-mentioned SIs. These SI-based studies have successfully predicted LAI at various spatial scales using commercially available digital cameras, field spectroradiometers, or airborne and satellite-borne sensors [8,11,[19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

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Spectral Index for Quantifying Leaf Area Index of Winter Wheat by Field Hyperspectral Measurements: A Case Study in Gifu Prefecture, Central Japan

et al. 2015

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Timely and nondestructive monitoring of leaf area index (LAI) using remote sensing techniques is crucial for precise and efficient management of crops. In this paper, a new spectral index (SI) for estimating LAI of winter wheat (Triticum aestivum L.) is proposed on the basis of field hyperspectral measurements. A simple index based on the empirical relationships between LAIs and SIs of all available two-waveband combinations from hyperspectral data is developed by considering the difference between reflectance values at 760 and 739 nm (DSIR760-R739 = R760 -R739). Among published and newly developed SIs, DSIR760-R739 exhibited a significant and strong linear relationship with LAI OPEN ACCESSRemote Sens. 2015, 7 5330 and showed outstanding performance in LAI assessments. The permissible bandwidths for broad-band DSIR760-R739 investigated using simulated reflectance were 5 nm for both 760 and 739 nm center wavelengths. The results indicate that the linear regression model based on the narrow-band and broad-band DSIR760-R739 is a simple but accurate method for timely and nondestructive monitoring of LAI.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spectral Index for Quantifying Leaf Area Index of Winter Wheat by Field Hyperspectral Measurements: A Case Study in Gifu Prefecture, Central Japan

et al. 2015

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“…The configuration of the PDC results in observations that are closer to the RF measurement than reflectance. The PDC was adjusted for radiometric values prior to field measurements in 2008 and estimated RF values were validated by placing a gray-scale board at the center of the viewed field (Shibayama et al, 2011a). The PDC has separate solar irradiance sensors fitted with the same-spec filters used in the cameras; the measured solar irradiance provides a correction for fluctuating illumination to enable calculation of the instantaneous values of the RF of each band.…”

Section: Instrumentsmentioning

confidence: 99%

“…On the contrary, optical remote detection of chlorophyll content would be a more challenging task than chlorophyll density. However, Haboudane et al (2002) developed a predictive index for corn leaf chlorophyll content for LAI values varying from 0.5 to 6 from above-canopy reflectance data.The techniques for collecting fixed-point, seasonally continuous observations of visible red and near infrared band reflectance images of paddy rice canopies and applications for rice nitrogen uptake and LAI predictions have been described (Shibayama et al, 2009b(Shibayama et al, , 2011a(Shibayama et al, , 2011b. These agronomic variables are measured on a unit land area basis.…”

mentioning

confidence: 99%

“…The techniques for collecting fixed-point, seasonally continuous observations of visible red and near infrared band reflectance images of paddy rice canopies and applications for rice nitrogen uptake and LAI predictions have been described (Shibayama et al, 2009b(Shibayama et al, , 2011a(Shibayama et al, , 2011b. These agronomic variables are measured on a unit land area basis.…”

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confidence: 99%

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Estimating Rice Leaf Greenness (SPAD) Using Fixed-Point Continuous Observations of Visible Red and Near Infrared Narrow-Band Digital Images

Shibayama

Sakamoto

Takada

et al. 2012

Plant Production Science

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A narrow-band dual camera system demonstrated a new close-range sensing technique to seasonally track trends in leaf greenness in rice paddies. A weatherproof digital imaging system for the visible red (RED, 620 − 650 nm) and near infrared band (NIR, 820 − 900 nm) was positioned 12 m above a 600-m 2 rice field. During the 2009 and 2010 paddy rice seasons, the system automatically logged images at 10-min intervals throughout the day. Radiometric corrections for the images utilized solar irradiance sensors and prior calibration to calculate 0900-1500 JST daily-averaged reflectance factors (DARF). The DARF in RED (DARF-RED) and NIR (DARF-NIR) values were transformed to provide a daily-averaged normalized difference vegetation index (DA-NDVI). The DA-NDVI increased more rapidly in the vegetative growth period, and reached an asymptotic plateau earlier than the DARF-NIR. From transplanting to harvest, leaf greenness values (measured by the SPAD index) were measured for the central part of the uppermost leaves of targeted canopies weekly with a chlorophyll meter. We developed a leaf greenness index (LGI), the ratio of DA-NDVI to DARF-NIR, and a simple calculation method for area means to reduce the background effect. The modified area means of LGI followed the seasonal trend in SPAD value well; its pattern was inherently different from the patterns of any of the original three parameters: DARF-RED, DARF-NIR or DA-NDVI. Throughout the paddy seasons in the two years, a regression equation for estimating SPAD values using the LGI, daily solar radiation, the cosine of angle between the view and the meridian directions and the cosine of culmination solar zenith angle performed favorably (R 2 =0.815). The nitrogen concentration per dry plant hill (g kg -1) had a close relation to the SPAD values estimated using the equation.Key words: Digital camera, NDVI, Nitrogen, Reflectance factor, Rice, SPAD.One of the essential factors of carbon assimilation per unit land area after heading is the rate of carbon assimilation per unit leaf area, and an effective cultural practice for increasing it is to topdress at the late spikelet initiation stage and at the full heading stage (Matsushima, 1976). Technically, the nutrient condition of crop plants at critical stages should be estimated in situ to determine the appropriate amount of topdressing. Nitrogen concentration, dry weight basis) of the leaf or whole plant has already proven to be relevant to many requirements of crop monitoring to assess the nutrient condition of rice plants. It has been used to determine the appropriate timing of application and amount of topdressing nitrogen fertilizer for normal growth and development of the crop during vegetative growth (Wada, 1969;Balasubramanian, 1999;Dobermann, 2003) and for preharvest assessment of 294 Plant Production Science Vol.15, 2012 the yield and grain quality in the maturing period (Abe et al., 2007;Mori et al., 2010). Nitrogen content variation among plant hills and locations in the plot or field are important for ...

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Phenomics: Technologies and Applications in Plant and Agriculture

Rahman

Ramanathan

Jeyabalan

et al. 2015

PlantOmics: The Omics of Plant Science

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Estimating Paddy Rice Leaf Area Index with Fixed Point Continuous Observation of Near Infrared Reflectance Using a Calibrated Digital Camera

Cited by 35 publications

References 48 publications

Spectral Index for Quantifying Leaf Area Index of Winter Wheat by Field Hyperspectral Measurements: A Case Study in Gifu Prefecture, Central Japan

Spectral Index for Quantifying Leaf Area Index of Winter Wheat by Field Hyperspectral Measurements: A Case Study in Gifu Prefecture, Central Japan

Estimating Rice Leaf Greenness (SPAD) Using Fixed-Point Continuous Observations of Visible Red and Near Infrared Narrow-Band Digital Images

Phenomics: Technologies and Applications in Plant and Agriculture

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