Impedance analysis of Labisia pumila plant water status

Jamaludin, Diyana; Aziz, Samsuzana Abd; Ahmad, Desa; Jaafar, Hawa Z. E.

doi:10.1016/j.inpa.2015.07.004

Cited by 21 publications

(21 citation statements)

References 11 publications

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“…The determination of the relative water content (RWC) (Equation 3) for the Experiment I on 10/04/2018 following the methodology proposed by Jamaludin, Aziz, Ahmad, and Jaafar (2015) in which samples of leaf discs were taken and weighed immediately by a digital scale with a precision of 0.01 g for determination of the fresh weight (FW). After weighing, the samples were floated in distilled water and kept in the dark for 24 h to regain full turgor.…”

Section: Measurement Of Plantsmentioning

confidence: 99%

Evaluation of the Growth and the Yield of Eggplant Crop Under Different Irrigation Depths and Magnetic Treatment of Water

Souza¹,

Rezende²,

Seron³

et al. 2019

JAS

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The use of magnetizers for the treatment of irrigation water can be used in agriculture as an alternative to increase the growth and yield of several crops. The objective of this study was to evaluate the effect of different irrigation depths and magnetic treatment of water on eggplant crop cultivated in protected environment. The study was carried out in two experiments, in the first one, the design was completely randomized with four replications and two factors: water depths (50, 75 and 100% ETc) for two water qualities (water treated by magnetizers and water without treatment). In the second one, the design was completely randomized with five replicates and two factors: water depths (75 and 100% ETc) for two irrigation water treatment (water treated by magnetizers and water without treatment). In the second experiment was ignored the treatment of 50% of ETc in order to increase the number of repetitions to check if there are differences between water treated to water without treatment. There were no significant differences in eggplant yield and growth as function of the magnetic treatment of water. The water depth that provided the highest yield, number of fruits per plant and stem dry matter in the two experiments was 100% ETc regardless of water quality.

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Section: Measurement Of Plantsmentioning

confidence: 99%

Evaluation of the Growth and the Yield of Eggplant Crop Under Different Irrigation Depths and Magnetic Treatment of Water

Souza¹,

Rezende²,

Seron³

et al. 2019

JAS

View full text Add to dashboard Cite

show abstract

“…Since the physiological electrical property of plants is related to water content [9] (in fact, the electrical behaviour of a plant is relatively resistive, as the tissue contains water [10]), several systems have used this property to estimate plant water status (and especially relative water content). This technique was successfully tested in plants such as Labisia pumila [11], Camellia sinensis [12], Solanum lycopersicum [13], and Lactuca sativa [14]. Recently, systems have been developed that allow continuous monitoring of water status in plants.…”

Section: Introductionmentioning

confidence: 99%

Field Spectroscopy: A Non-Destructive Technique for Estimating Water Status in Vineyards

et al. 2019

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Water status controls plant physiology and is key to managing vineyard grape quality and yield. Water status is usually estimated by leaf water potential (LWP), which is measured using a pressure chamber; however, this method is difficult, time-consuming, and error-prone. While traditional spectral methods based on leaf reflectance are faster and non-destructive, most are based on vegetation indices derived from satellite imagery (and so only take into account discrete bandwidths) and do not take full advantage of modern hyperspectral sensors that capture spectral reflectance for thousands of wavelengths. We used partial least squares regression (PLSR) to predict LWP from reflectance values (wavelength 350–2500 nm) captured with a field spectroradiometer. We first identified wavelength ranges that minimized regression error. We then tested several common data pre-processing methods to analyze the impact on PLSR prediction precision, finding that derivative pre-processing increased the determination coefficients of our models and reduced root mean squared error (RMSE). The models fitted with raw data obtained their best results at around 1450 nm, while the models with derivative pre-processed achieved their best estimates at 826 nm and 1520 nm.

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“…As water plays a vital role in all processes in biomaterials (Jamaludin et al 2015 ), it is expected that significant change will occur in impedance with the dehydration process in onions. The EIS studies conducted for different onion samples for 3 weeks showed that at a particular frequency, the onion impedance gradually increases throughout the experiment as drying time proceeds (Fig.…”

Section: Resultsmentioning

confidence: 99%

Model of dehydration and assessment of moisture content on onion using EIS

et al. 2019

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Onion is perishable and thereby subject to drying during unrefrigerated storage. Its moisture content is important to ensure optimum quality in storage. To track and analyze the dynamics of natural dehydration in onion and also to assess its moisture content, noninvasive and nondestructive methods are preferred. One of them is known as electrical impedance spectroscopy (or EIS in short). In the first phase of our experiment, we have used EIS, where we apply alternating current with multiple frequency to the object (onion in this case) and generate impedance spectrum which is used to characterize the object. We then develop an equivalent electrical circuit representing onion characteristics using a computer assisted optimization technique that allows us to monitor the response of onion undergoing natural drying for a duration of 3 weeks. The developed electrical model shows better congruence with the impedance data measured experimentally when compared to other conventional models for plant tissue with a mean absolute error of 0.42% and root mean squared error of 0.55%. In the second phase of our experiment, we attempted to find a correlation between the previous impedance data and the actual moisture content of the onions under test (measured by weighing) and developed a mathematical model. This model will provide an alternative tool for assessing the moisture content of onion nondestructively. Our model shows excellent correlation with the ground truth data with a deterministic coefficient of 0.9767, root mean square error of 0.02976 and sum of squared error of 0.01329. Therefore, our two models will offer plant scientists the ability to study the physiological status of onion both qualitatively and quantitatively.

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Impedance analysis of Labisia pumila plant water status

Cited by 21 publications

References 11 publications

Evaluation of the Growth and the Yield of Eggplant Crop Under Different Irrigation Depths and Magnetic Treatment of Water

Evaluation of the Growth and the Yield of Eggplant Crop Under Different Irrigation Depths and Magnetic Treatment of Water

Field Spectroscopy: A Non-Destructive Technique for Estimating Water Status in Vineyards

Model of dehydration and assessment of moisture content on onion using EIS

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