Daytime and Nighttime Field Spectral Imagery of Ripening Paddy Rice for Determining Leaf Greenness and 1000-Grain Weight

Shibayama, Michio; Sakamoto, Toshihiro; Homma, Kohzo; Okada, Shuhei; Yamamoto, Hiromichi

doi:10.1626/pps.12.307

Cited by 5 publications

(6 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In agriculture, there has been a great deal of research on the practical utilization of digital camera images for crop management, for example, plant species identification (Meyer et al, 1999), weed detection (Perez et al, 2000), crop growth diagnosis in terms of vegetative fraction (Lukina et al, 1999;Woebbecke et al, 1995), leaf area index (LAI) (Demarez et al, 2008;Shibayama et al, 2011), leaf color (Adamsen et al, 1999;Shibayama et al, 2009a), and nitrogen content (Matsuda et al, 2003;Shibayama et al, 2009b). Sakamoto et al (2010a) devised a low-cost camera observation system called the crop phenology recording system (CPRS) to estimate seasonal changes in the biophysical parameters of rice, barley, and maize using daytime red, green, and blue (RGB) and nighttime-flash near-infrared (NIR) images.…”

Section: Introductionmentioning

confidence: 99%

An alternative method using digital cameras for continuous monitoring of crop status

Sakamoto

Gitelson²,

Nguy-Robertson

et al. 2012

Agricultural and Forest Meteorology

Self Cite

149

View full text Add to dashboard Cite

a b s t r a c tCrop physiological and phenological status is an important factor that characterizes crop yield as well as carbon exchange between the atmosphere and the terrestrial biosphere in agroecosystems. It is difficult to establish high frequency observations of crop status in multiple locations using conventional approaches such as agronomical sampling and also remote sensing techniques that use spectral radiometers because of the labor intensive work required for field surveys and the high cost of radiometers designed for scientific use. This study explored the potential utility of an inexpensive camera observation system called crop phenology recording system (CPRS) as an alternative approach for the observation of seasonal change in crop growth. The CPRS consisting of two compact digital cameras was used to capture visible and near infrared (NIR) images of maize in 2009 and soybean in 2010 for every hour both day and night continuously. In addition, a four channel sensor SKYE measured crop reflectance and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images were acquired over crop fields. The six different camera-radiometer-and MODIS-derived vegetation indices (VIs) were calculated and compared with the ground-measured crop biophysical parameters. In addition to VIs that use digital numbers, we proposed to use daytime exposure value-adjusted VIs. The camera-derived VIs were compared with the VIs calculated from spectral reflectance observations taken by SKYE and MODIS. It was found that new camera-derived VIs using daytime exposure values are closely related to VIs calculated using SKYE and MODIS reflectance and good proxies of crop biophysical parameters. Camera-derived green chlorophyll index, simple ratio and NDVI were found to be able to estimate the total leaf area index (LAI) of maize and soybean with high accuracy and were better than the widely used 2g-r-b. However, camera-derived 2g-rb showed the best accuracy in estimating daily fAPAR in vegetative and reproductive stages of both crops. Visible atmospherically resistant vegetation index showed the highest accuracy in the estimation of the green LAI of maize. A unique VI, calculated from nighttime flash NIR images called the nighttime relative brightness index of NIR, showed a strong relationship with total aboveground biomass for both crops. The study concludes that the CPRS is a practical and cost-effective approach for monitoring temporal changes in crop growth, and it also provides an alternative source of ground truth data to validate time-series VIs derived from MODIS and other satellite systems.

show abstract

Section: Introductionmentioning

confidence: 99%

An alternative method using digital cameras for continuous monitoring of crop status

Sakamoto

Gitelson²,

Nguy-Robertson

et al. 2012

Agricultural and Forest Meteorology

Self Cite

149

View full text Add to dashboard Cite

show abstract

“…Future studies using higher spatial resolution cameras could evaluate the spatial distribution of greenness in the field and in each plot and row or hill. Further close-range imaging may reveal color divergence in a plant or organ (Shibayama et al, 2009a), but it could not be acquired at the same time with measurement at the field level or higher.…”

Section: Lgi Means Of Cross-sectional Lines In Images With Medium Spamentioning

confidence: 99%

“…Hand-held digital cameras sensitive to both visible and near infrared wavelengths are available for agricultural and vegetation studies (White et al, 2000;Omine, 2007;Okada and Ikeba, 2008;Sakamoto et al, 2010). Imaging spectrometers with higher spectral resolution, may be effective for basic studies, but available imagers are too costly and unwieldy for practical field work (Inoue and Peñuelas, 2001;Minekawa et al, 2007;Shibayama et al, 2009a).For paddy rice leaf color and nitrogen concentration assessments, advanced research has supported the possibility of using commercial color digital cameras (Matsuda et al, 2003;Nagano and Shigedomi, 2005). Of course, changing weather conditions affecting measurement times and the viewing and illumination geometry of camera images have been major obstacles.…”

mentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

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

Self Cite

View full text Add to dashboard Cite

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 ...

show abstract

“…Compared with other monitoring method, it is characterized by substantial data collection, rapid speed, high precision, etc. Furthermore, it has huge potential in saving labor and lowering the subjectivity of human judgment [3,4]. Till now, images acquired with visual system are employed for conducting automatic monitoring of crop growth, and substantial research work has been conducted, which can be concluded in the following aspects: (1) detection and recognition of disease, insect pests and weeds [5]; (2) measurement of external crop growth parameter (such as blade area, height, etc.)…”

Section: Introductionmentioning

confidence: 99%

Automatic recognition of rape seeding emergence stage based on computer vision technology

Fang

Chang

Zhai

et al. 2014

2014 the Third International Conference on Agro-Geoinformatics

View full text Add to dashboard Cite

Acquisiton of crop growth stage information can not only help to analyze the relation between the crop growth process and environmental condition, but also to guide the field operation effectively. Therefore, different growth stages of rape crops are monitored with the visual system constructed in this paper, and the first critical growth stage of rape is detected automatically, which is seeding emergence stage. The rape should be first extracted from the image. Considering the the impacts of the complicated environment and climatic changes, HI color segmentation method is adopted to segment the crops from the background. Then, two limited conditions, cotyledon area and density, are applied to judge whether it is at seeding emergence stage. Eventually, the experimental results are compared to the ones from other mature methodologies and manual observation, and it shows that the proposed methodology is effective and feasible, and it can provide support for precision agriculture.

show abstract

Daytime and Nighttime Field Spectral Imagery of Ripening Paddy Rice for Determining Leaf Greenness and 1000-Grain Weight

Cited by 5 publications

References 21 publications

An alternative method using digital cameras for continuous monitoring of crop status

An alternative method using digital cameras for continuous monitoring of crop status

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

Automatic recognition of rape seeding emergence stage based on computer vision technology

Contact Info

Product

Resources

About