A Review on Diagnosis of Nutrient Deficiency Symptoms in Plant Leaf Image Using Digital Image Processing

Jeyalakshmi, S.; Radha, R.

doi:10.21917/ijivp.2017.0216

Cited by 34 publications

(23 citation statements)

References 20 publications

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“…They use color feature extraction method namely histogram of template (HOT) to extract the features for both test and training data. According to Jeyalakshmi and Radha [10], proposed a software is good and can replace the manual system of plant disease detection.…”

Section: Classification In Agriculturementioning

confidence: 99%

Comparison of color-based feature extraction methods in banana leaf diseases classification using SVM and K-NN

Said

Madzin

Ali

et al. 2021

IJEECS

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In Malaysia, banana is a top fruit production which contribute to the economy growth in agriculture field. Hence, it is significant to have a quality production of banana and important to detect the plant diseases at the early stage. There are many types of banana leaf diseases such as Banana Mosaic, Black Sigatoka and Yellow Sigatoka. These three diseases are related to color changes at banana. This research paper is an experiment based and need to identify the best color feature extraction method to classify banana leaf diseases. Total of 48 banana leaf images that are used in this research paper. Four types of color feature extraction methods which are color histogram, color moment, hue, saturation, and value (HSV) histogram and color auto correlogram are experimented to determine the best method for banana leaf diseases classification. While for the classifiers, support vector machine (SVM) and k-Nearest neighbors (k-NN) are used to evaluate the performance and accuracy of each color feature extraction methods. There are also preliminary experiments to identify accurate parameters to use during classification for both classifiers. Our experimental result express that HSV histogram is the best method to classify banana leaf diseases with 83.33% of accuracy and SVM classifier perform better compared to k-NN.

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Section: Classification In Agriculturementioning

confidence: 99%

Comparison of color-based feature extraction methods in banana leaf diseases classification using SVM and K-NN

Said

Madzin

Ali

et al. 2021

IJEECS

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“…There are also physiological and colorimetric effects on plant colors. Deficiency of mineral nutrients causes different colorimetric effects on plant leaves (Jeyalakshmi and Radha 2017;McCauley et al 2011). Nitrogen deficiency and iron deficiency both cause chlorosis, the color change from green to yellow-green or yellow.…”

Section: Physiological Effects On Plant Colorsmentioning

confidence: 99%

Measuring plant colors

Kasajima

2019

Plant Biotechnology

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Plant colors such as 'green leaf ' and 'red apple' are often described based on human sense, even in scientific papers. On the other hand, colors are measured based on colorimetric principles in some papers, especially in the studies of horticultural plants. The science of color measurements ('colorimetry') is not included in any of the popular lectures in schools and universities, thus the principles of color measurements would not be understood by most researchers. The present review will overview the principles of colorimetry, and will introduce colorimetric methods which can be used for scientific measurement of plant colors. That is to say, the reflection spectrum of visible light (380-780 nm) is measured at 5-nm intervals on the surface of leaves or petals in 'Spectrometric Color Measurement' (SCM). The spectral data is multiplied with RGB or XYZ color matching functions and integrated to obtain RGB or XYZ intensities. Alternatively, approximate RGB values are directly obtained in 'Photographic Color Measurement' (PCM). RGB/XYZ intensities are further calculated to obtain 'hue' , 'saturation' , and 'lightness' , the three factors of colors. Colorimetric insights into genetic regulations (such as MYB gene) and physiological regulations (such as alexandrite effect) of plant colors are also described.

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“…Doi: https://doi.org/10.22236/j.bes/537772 ISSN: 2614ISSN: -1558 Plant nutrients are distinguished into macronutrients, micronutrients, and trace elements based on nutrient needs. Macronutrient elements consist of N, K, S, Ca, Mg, and P (Jeyalakshmi and Radha, 2017). Micronutrient elements include Na, K, B, Mn, Zn, Cu, and Mo and trace elements, namely Al, Si, Au, Ni (Mc Cauley et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Determination of Optimization of Nutritional Deficiencies in Plant Physiology Practicum in Hydroponic Laboratories (Axis and No-Axis System)

Sumiati

surur

2021

BES

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Background: Hydroponics is a method of agriculture that utilizes water as a planting medium. The purpose of the study was to find out good working procedures and nutrient solution formulas capable of showing symptoms of morphological nutritional deficiencies in plants. Methods: The plants used are the seeds of kale plants that are sown within 1 - 2 weeks (until roots, stems, and leaves grow). The design used is Random Group using three formulas with nine kinds of treatment on each formula and three repeats. Experiments were conducted on two hydroponic systems, the axis and without the axis. The parameters observed are the number of leaves, the leaves' length, the leaves' width, the plant's height, and the plant's height. Results: Observational data in the analysis using SPSS 25. The effect of treatment with test parameters is seen using ANOVA analysis and BNT advanced tests. Visual observations showed the formula of nutrient solutions 1, 2 and 3 using both the axis system and without the axis showed symptoms of nutritional deficiencies in kale plants. The axis less system experiment gave more significant results on all parameters except PD (leaf length) than the axis system based on the average results of BNT advanced tests. Conclusion: Nutrient solutions 1, 2 and 3 have a real effect on all test parameters.

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A Review on Diagnosis of Nutrient Deficiency Symptoms in Plant Leaf Image Using Digital Image Processing

Cited by 34 publications

References 20 publications

Comparison of color-based feature extraction methods in banana leaf diseases classification using SVM and K-NN

Comparison of color-based feature extraction methods in banana leaf diseases classification using SVM and K-NN

Measuring plant colors

Determination of Optimization of Nutritional Deficiencies in Plant Physiology Practicum in Hydroponic Laboratories (Axis and No-Axis System)

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