An Analysis of Leaf Chlorophyll Measurement Method Using Chlorophyll Meter and Image Processing Technique

Dey, Amar Kumar; Шарма, Маниша; Meshram, M.R.

doi:10.1016/j.procs.2016.05.235

Cited by 51 publications

(34 citation statements)

References 8 publications

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“…Data recording procedure. The leaf chlorophyll content was measured by following Dey et al (2016) procedure. The P N , E, and g s were measured using the LC-pro portable photosynthetic system (ADC BioScientific Ltd., UK) as described by Quamruzzaman et al (2017).…”

Section: Methodsmentioning

confidence: 99%

Photosynthetic Response and Antioxidant Content of Hydroponic Bitter Gourd as Influenced by Organic Substrates and Nutrient Solution

Rahman¹,

Quamruzzaman²,

Uddain³

et al. 2018

horts

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Crop-specific nutrient solution and suitable growing media mixtures are necessary in hydroponic system to improve the yield of vegetables. Therefore, an experiment was conducted to specify the required amount of nutrient solution and ecofriendly mixtures of growing substrates of a hydroponic bitter gourd. Treatments consisted two factors, viz., four different types of growing substrate (M1 = 60% rice husk + 30% coconut coir + 10% vermicompost, M2 = 60% coconut coir + 30% khoa + 10% vermicompost, M3 = 60% sawdust + 30% khoa + 10% vermicompost, and M4 = 60% ash + 30% khoa + 10% vermicompost) and three different composition of nutrient solutions [N1 = full strength Rahman and Inden (2012), N2 = full strength Hoagland and Arnon (1940), and N3 = ½ strength Rahman and Inden (2012)]. Photosynthetic responses and its related parameters, namely, stomatal conductance (gs), transpiration (E), and photosynthetic rate (PN) were significantly affected by nutrient solution composition and growing substrate mixtures. Results revealed that the leaf gas exchange parameters, yield contributing characters, and biochemical parameters showed that full strength of Rahman and Inden (2012) nutrient solution application was better in a growing mixture of 60% rice husk + 30% coconut coir + 10% vermicompost in soilless culture for obtaining high yield and high quality of bitter gourd.

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Section: Methodsmentioning

confidence: 99%

Photosynthetic Response and Antioxidant Content of Hydroponic Bitter Gourd as Influenced by Organic Substrates and Nutrient Solution

Rahman¹,

Quamruzzaman²,

Uddain³

et al. 2018

horts

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show abstract

“…Robust base parameters should deliver accurate results. Nevertheless, previous vision‐based approaches demonstrated that it is difficult to obtain base parameters with high discriminant and repeatability . For the acquisition technique, previous vision‐based approaches have used natural illumination, and this has delivered poor performance in terms of accuracy.…”

Section: Methodsmentioning

confidence: 99%

An FPGA‐based smart camera for accurate chlorophyll estimations

Pérez-Patricio

Aguilar-González

Camas-Anzueto

et al. 2018

Circuit Theory & Apps

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In this work, a new chlorophyll estimation approach based on the reflectance/ transmittance from the leaf being analyzed is proposed. First, top/underside images from the leaf under analysis are captured, then, the base parameters (reflectance/transmittance) are extracted. Finally, a double-variable linear regression model estimates the chlorophyll content. To estimate the base parameters, a novel optical arrangement is presented. On the other hand, in order to provide a portable device suitable for chlorophyll estimation under large scale food crops, we have implemented our optical arrangement and our algorithmic formulation inside an field-programmable gate array (FPGA)-based smart camera fabric. Experimental results demonstrated that the proposed approach outperforms (in terms of accuracy and processing speed) most previous vision-based approaches, reaching more than 97% accuracy and delivering fast chlorophyll estimations (near 5 ms per estimation).

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“…Leaf chlorophyll is mostly used as an index to diagnose diseases and getting the nutrient and nitrogen status in the plants [49]. Hence, the chlorophyll meter is a promising tool in leaf N assessment [47], and identifies N deficiencies in plants [50,51].…”

Section: Leaf Chlorophyll and Polyphenolics Measurement Methodsmentioning

confidence: 99%

Nitrogen (N) Mineral Nutrition and Imaging Sensors for Determining N Status and Requirements of Maize

Rhezali¹,

Lahlali

2017

J. Imaging

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Nitrogen (N) is one of the most limiting factors for maize (Zea mays L.) production worldwide. Over-fertilization of N may decrease yields and increase NO 3 − contamination of water.However, low N fertilization will decrease yields. The objective is to optimize the use of N fertilizers, to excel in yields and preserve the environment. The knowledge of factors affecting the mobility of N in the soil is crucial to determine ways to manage N in the field. Researchers developed several methods to use N efficiently relying on agronomic practices, the use of sensors and the analysis of digital images. These imaging sensors determine N requirements in plants based on changes in Leaf chlorophyll and polyphenolics contents, the Normalized Difference Vegetation Index (NDVI), and the Dark Green Color index (DGCI). Each method revealed limitations and the scope of future research is to draw N recommendations from the Dark Green Color Index (DGCI) technology. Results showed that more effort is needed to develop tools to benefit from DGCI.

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An Analysis of Leaf Chlorophyll Measurement Method Using Chlorophyll Meter and Image Processing Technique

Cited by 51 publications

References 8 publications

Photosynthetic Response and Antioxidant Content of Hydroponic Bitter Gourd as Influenced by Organic Substrates and Nutrient Solution

Photosynthetic Response and Antioxidant Content of Hydroponic Bitter Gourd as Influenced by Organic Substrates and Nutrient Solution

An FPGA‐based smart camera for accurate chlorophyll estimations

Nitrogen (N) Mineral Nutrition and Imaging Sensors for Determining N Status and Requirements of Maize

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