Smartphone image based digital chlorophyll meter to estimate the value of citrus leaves chlorophyll using Linear Regression, LMBP-ANN and SCGBP-ANN

Barman, Utpal; Choudhury, Ridip Dev

doi:10.1016/j.jksuci.2020.01.005

Cited by 26 publications

(17 citation statements)

References 28 publications

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“…Regression analysis is defined as powerful method in statistical modeling to show the relationship between two or more variables so that one variable can be predicted from other variables (Rawlings et al 1998). Previous studies used regression analysis to estimate citrus chlorophyll content (Barman and Choudhury 2020), citrus maturity level (Itakura et al 2019), and assessment of citrus chemical quality variables (Torres et al 2019). Present work used regression analysis to statistically estimate the leaf area and leaf weight of kaffir lime by observing some predictors.…”

Section: Resultsmentioning

confidence: 99%

Short Communication: Allometric model to estimate bifoliate leaf area and weight of kaffir lime (Citrus hystrix)

et al. 2021

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Abstract. Budiarto R, Poerwanto R, Santosa E, Efendi D, Agusta A. 2021. Short Communication: Allometric model to estimate bifoliate leaf area and weight of kaffir lime (Citrus hystrix). Biodiversitas 22: 2815-2820. Leaf is an economically important plant organ harvested from kaffir lime (Citrus hystrix DC.) for flavor and fragrance. This study aimed to formulate and validate regression models to estimate the leaf area (LA) and leaf weight (LW) of bifoliate kaffir lime leaf. There were 220 bifoliate leaves collected from 22 individual plants planted on Bogor. Bifoliate C. hystrix leaf consisted of upper main leaflets and winged petiole as lower secondary leaflet. All leaves were pooled and then grouped randomly into two subgroups for model formulation and validation, respectively. Linear, zero intercepts linear, exponential, logarithmic, polynomial, zero intercept polynomial and power regressions were used to properly estimate LA and LW. There was 63 formula obtained from nine predictors following seven regression models. Selected nine formulas with the highest R2 plus a stepwise formula were further tested for validation. Stepwise always showed the highest R2 followed by total of leaf ,length (TL) both on LA and LW estimation. However, the stepwise seemed to be more complicated and time wasted than TL regression model. Thus, our recommendation models for non-destructive and simple estimation in C. hystrix bifoliate leaf were LA = 0.1997 (TL)2 + 0.4571 (TL) and LW = 0.0067 (TL)2 + 0.0065 (TL), respectively.

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Section: Resultsmentioning

confidence: 99%

Short Communication: Allometric model to estimate bifoliate leaf area and weight of kaffir lime (Citrus hystrix)

et al. 2021

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“…RGB values from both red LED light and white LED light found to have a very weak correlation and non-significant relationship with the leaf Chl content in mg • g −1 , but very high correlation and significant relationship with the leaf Chl content in mg • MW −1 (Table 1). In a similar in press study by Barman and Choudhury (2020) alike method was used but constant light source (Eveready digital torch with 0.2 watt and 11 lumens) was used instead of white LED light. They did not test red LED light.…”

Section: Discussionmentioning

confidence: 99%

Mathematical models for the estimation of leaf chlorophyll content based on RGB colours of contact imaging with smartphones: A pomegranate example

Ozrecberoglu

Kahramanoğlu

2020

Folia Horticulturae

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The objective of this study was to develop a mathematical model for the non-destructive, fast estimation of the leaf chlorophyll (Chl) content of pomegranate trees. For this reason, contact images of the leaf samples were firstly captured with smartphones and the RGB colours of the images were used for the estimation of the leaf Chl contents. Here, different methods were used for the contact imaging. In the present study, two closed boxes with a small hole (equal to the dimensions of a smartphone camera) on each were formed. Samples were inserted into the hole; and a red LED light and white LED light, separately, were passed through the hole and the leaf. Furthermore, a series of models were tested to best estimate the leaf chlorophyll content of the pomegranate trees by using the RGB colours of contact imaging. Results showed that the use of red LED light sources, instead of white LED light sources, during contact imaging, provides a better estimation of the leaf Chl content. Results also suggest that colour values are highly related to the total weight of the contact imaging area. According to the results obtained, the best estimation of the leaf Chl content (of a given area) is possible by using both the G and B colour values with multiple regression models. It is also found to be important to use the weight of the sampled area for the estimation of the leaf chlorophyll content in mg ∙ g−1.

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“…Time series data streams are analyzed for knowing the underlying pattern of the data along the selected time. The time series analysis drives to build a fitting line between the dependent variable and independent ones (Barman and Choudhury 2020 ); therefore, it can be respected this quantitative estimating approach because predicting the time series' future values in function of its historical behavior.…”

Section: Methodsmentioning

confidence: 99%

Urban air quality changes resulting from the lockdown period due to the COVID-19 pandemic

Galán-Madruga¹

2022

Int. J. Environ. Sci. Technol.

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This work aims to quantify potential pollution level changes in an urban environment (Madrid city, Spain) located in South Europe due to the lockdown measures for preventing the SARS-CoV-2 transmission. Polluting 11 species commonly monitored in urban zones were attended. Except for O 3 , a prompt target pollutant levels abatement was reached, intensely when implanted stricter measures and moderately along those measures' relaxing period. In the case of TH and CH 4 , it is evidenced a progressive diminution over the lockdown period. While the highest decreasing average changes relapsed on NOx (NO 2 : − 40.0% and NO: − 33.3%) and VOCs (C 7 H 8 : − 36.3% and C 6 H 6 : − 32.8%), followed by SO 2 (− 27.0%), PM 10 (− 19.7%), CO (− 16.6%), CH 4 (− 14.7%), TH (− 11.6%) and PM 2.5 (− 10.1%), the O 3 level slightly raised 0.4%. These changes were consistently dependent on the measurement station location, emphasizing urban background zones for SO 2 , CO, C 6 H 6 , C 7 H 8 , TH and CH 4 , suburban zones for PM 2.5 and O 3 , urban traffic sites for NO and PM 10 , and keeping variations reasonably similar at all the stations in the case of NO 2 . Those pollution changes were not translated in variations on geospatial pattern, except for NO, O 3 and SO 2 . Although the researched urban atmosphere improvement was not attributable to meteorological conditions' variations, it was in line with the decline in traffic intensity. The evidenced outcomes might offer valuable clues to air quality managers in urban environments regarding decision-making in favor of applying punctual severe measures for quickly and considerably relieving polluting high load occurred in urban environments. Supplementary Information The online version contains supplementary material available at 10.1007/s13762-022-04464-6.

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Smartphone image based digital chlorophyll meter to estimate the value of citrus leaves chlorophyll using Linear Regression, LMBP-ANN and SCGBP-ANN

Cited by 26 publications

References 28 publications

Short Communication: Allometric model to estimate bifoliate leaf area and weight of kaffir lime (Citrus hystrix)

Short Communication: Allometric model to estimate bifoliate leaf area and weight of kaffir lime (Citrus hystrix)

Mathematical models for the estimation of leaf chlorophyll content based on RGB colours of contact imaging with smartphones: A pomegranate example

Urban air quality changes resulting from the lockdown period due to the COVID-19 pandemic

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