Development of Prediction Model for Harvest Moisture Content of Rough Rice Using Meteorological Data and Color Characteristics

2021 ◽  
Vol 37 (6) ◽  
pp. 1063-1071
Author(s):  
Hoon Kim ◽  
Oui Woung Kim ◽  
Jae Woong Han ◽  
Hyo-Jai Lee
Keyword(s):  
Moisture Content ◽  
Prediction Model ◽  
Meteorological Data ◽  
Coefficient Of Determination ◽  
Harvest Time ◽  
Leaf Color ◽  
Rough Rice ◽  
Accumulated Temperature ◽  
Harvest Moisture

HighlightsMoisture content, meteorological data, and leaf color characteristics of rice were investigated by harvest time.The moisture content decreased, and leaf color value increased as days after heading passed.Harvest moisture content prediction models were developed using meteorological data and leaf color.It is necessary to use both leaf color and meteorological data to determine the harvest time.Abstract.In this study, ambient temperature, accumulated temperature, and rice leaf color values were measured before harvest time to develop models for predicting the harvest moisture content (HMC) of short-grain rice. Field tests were conducted on Chuchung and Whang-gum-nu-ri, which are short-grain rice cultivars, at different experimental plots, for four years. As days after heading (DAH) passed, the moisture content (MC) decreased, and leaf color (L*, a*, and b* values) tended to increase. An experimental model that can predict HMC was developed based on the experimental results of 3 years, and the experimental results of the remaining 1 year were used for verification. The coefficient of determination of the HMC prediction model that used ambient and accumulated temperatures was 0.719, and that of the prediction model that used leaf color was as low as 0.418. However, the coefficient of determination of the integrated model that used all the factors, i.e. ambient and accumulated temperatures and leaf color, was as high as 0.915. Therefore, to determine the harvest time using the HMC of rough rice, leaf color, and meteorological data should be used together. Leaf color tended to increase markedly as the DAH increased, but the leaf color values were not similar for the same MC each year. This is because leaf color is influenced not only by MC but also by various cultivation factors such as soil conditions and growth rate during the rice cultivation process. Keywords: Accumulated temperature, Harvest, Harvest moisture content, Leaf color, Rice, Short variety.

scholarly journals Determination of selected physical properties of Brachystegia eurycoma seeds

2009 ◽  
Vol 55 (No. 4) ◽  
pp. 165-169 ◽  
Author(s):  
M.C. Ndukwu
Keyword(s):  
Moisture Content ◽  
Physical Properties ◽  
Bulk Density ◽  
Surface Area ◽  
Angle Of Repose ◽  
Coefficient Of Determination ◽  
Solid Density ◽  
Axial Dimension ◽  
Design And Construction

The research looked at some selected physical properties of <I>Brachystegia eurycoma</I>, such as axial dimension, roundness, sphericity, surface area, bulk density, solid density, porosity, and volume which are essential in the design and construction of the processing and handling equipments of <I>Brachystegia eurycoma</I>. All the above physical properties measured showed some deviations from the average values which is typical of agricultural biomaterials. Solid density showed the highest deviation of 4.04 g/mm<sup>3</sup> while the volume showed the least deviation of 0.01 mm<sup>3</sup> when compared to those of other physical properties. The angle of repose increased with the increase in the moisture content with a coefficient of determination of 0.98.

Determination of Optical Parameters and Moisture Content of Wood with Visible–Near Infrared Spectroscopy

2016 ◽  
Vol 24 (6) ◽  
pp. 571-585 ◽  
Author(s):  
Ataollah Haddadi ◽  
Guillaume Hans ◽  
Brigitte Leblon ◽  
Zarin Pirouz ◽  
Satoru Tsuchikawa ◽  
...  
Keyword(s):  
Moisture Content ◽  
Near Infrared ◽  
Black Spruce ◽  
Scattering Coefficient ◽  
Coefficient Of Determination ◽  
Optical Parameters ◽  
Quaking Aspen ◽  
Near Infrared Reflectance ◽  
Scattering Coefficients

We used the Kubelka-Munk theory equations for calculating the absorption coefficient (Kλ), the scattering coefficient ( Sλ), the transport absorption (σλa), the reduced scattering coefficient [σλs(1 – g)] and the penetration depth (δλ) from visible-near infrared reflectance spectra acquired over thin samples of quaking aspen and black spruce conditioned at three different moisture levels. The computed absorption and scattering coefficients varied from 0.1 mm−1 to 4.0 mm−1 and from 5.5 mm−1 to 10.0 mm−1, respectively. The absorption coefficients varied according to the absorption band, but the scattering coefficients decreased slowly towards high wavelengths. The sample moisture content was then estimated using the partial least squares (PLS) regression method from the Kλ and/or Sλ spectra, and the resulting PLS models were compared to those obtained with raw and transformed [multiplicative scatter corrected (MSC), first and second derivative] absorption spectra. The best PLS models for black spruce, quaking aspen and both species were obtained when only the 800–1800 nm range was used with the raw or MSC spectra. They led to a root mean square error of cross validation ( RMSECV) of 1.40%, 1.09% and 1.23%, respectively, and to a coefficient of determination ( R2CV) higher than 0.94. We also found that the Kλ spectra between 800 nm and 1800 nm can provide PLS models having an acceptable accuracy for moisture content estimation ( R2CV = 0.83 and RMSECV = 2.32%), regardless of the species.

scholarly journals Nondestructive Prediction of Optimal Harvest Time of Cherry Tomatoes Using VIS-NIR Spectroscopy and PLSR Calibration

2011 ◽  
Vol 1 ◽  
pp. 92-96 ◽  
Author(s):  
Hai Qing Yang
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Harvest Time ◽  
Least Squares Regression ◽  
Calibration Models ◽  
Optimal Harvest ◽  
Leave One Out

In situ determination of optimal harvest time of tomatoes is of value for growers to optimize fruit picking schedule. This study evaluates the feasibility of using visible and near infrared (VIS-NIR) spectroscopy to make an intact estimation of harvest time of tomatoes. A mobile, fibre-type, AgroSpec VIS-NIR spectrophotometer (Tec5, Germany), with a spectral range of 350-2200 nm, was used for spectral acquisition of tomatoes in reflection mode. The harvest time of tomatoes was measured by the days before harvest. After dividing spectra into a calibration set (70%) and an independent prediction set (30%), spectra in the calibration set were subjected to a partial least-squares regression (PLSR) with leave-one-out cross validation to establish calibration models. Validation of calibration models on the independent prediction set indicates that the best model can produce excellent prediction accuracy with coefficient of determination (R2) of 0.90, root-mean-square error of prediction (RMSEP) of 2.5 days and residual prediction deviation (RPD) of 3.01. It is concluded that VIS-NIR spectroscopy coupled with PLSR models can be adopted successfully for in situ determination of optimal harvest time of tomatoes, which allows for automatic fruit harvest by a horticultural robot.

Drying of Rough Rice Using Heated Husk for Heat Transfer and Moisture Adsorption

2018 ◽  
Vol 34 (3) ◽  
pp. 605-615 ◽  
Author(s):  
Sammy S. Sadaka ◽  
Griffiths G. Atungulu
Keyword(s):  
Heat Transfer ◽  
Moisture Content ◽  
Rice Husk ◽  
Rice Yield ◽  
Ambient Air ◽  
Coefficient Of Determination ◽  
Drying Rate ◽  
Air Drying ◽  
Rough Rice ◽  
Rice Samples

Abstract. Drying of small size samples usually represents a challenge to rice researchers. Using natural air drying to dry these samples exposes them to the fluctuations of ambient air conditions. Therefore, the goal of this research was to evaluate the suitability of drying small size rough rice samples using heated husk as a heat transfer and moisture adsorbent medium. The proposed drying technique could be an attainable process, particularly because it represents conduction heat and moisture transfer rather than natural air drying. The required amounts of rice husk were placed in aluminum containers and kept in an oven overnight to reach the desired temperature. Heated husk samples were mixed with rough rice and maintained for the desired drying duration; following which, the husk and rough rice mixtures were separated pneumatically. The separated rough rice samples were collected to determine moisture content, drying rate, and rice quality. The highest mixture temperature of 34.0°C was achieved at the highest husk to rough rice ratio of 1:2 and the highest husk temperature of 110°C after 4 minutes. A maximum of 6.4% moisture reduction points was achieved by mixing the rice husk to rough rice by 1:2 on a weight basis and employing heated rice husk at 100°C. The highest drying rate of 5.99%/h was achieved during the first hour of drying with the husk-to-rough rice ratio of 1:2 and the husk temperature of 100°C. Milled rice yield ranged between 63.4% and 72.0% while the head rice yield ranged between 39.9% and 67.9%. An empirical correlation was developed to calculate the normalized moisture content as a function of the husk to rough rice ratio, the husk temperature and drying duration with a coefficient of determination of 0.775 under the studied conditions. Keywords: Conduction drying, Heat transfer medium, Moisture absorbent, Rice husk, Rough rice.

Investigation of electrical characteristics using various electrodes for evaluating the moisture content in wood

BioResources ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. 7040-7055
Author(s):  
Sung-Wook Hwang ◽  
Sung-Yun Hwang ◽  
Taekyeong Lee ◽  
Kyung-Sun Ahn ◽  
Sung-Jun Pang ◽  
...  
Keyword(s):  
Moisture Content ◽  
Electrical Resistance ◽  
Longitudinal Direction ◽  
Coefficient Of Determination ◽  
Larix Kaempferi ◽  
Least Squares Regression ◽  
Electrically Conductive ◽  
The Relationship ◽  
Resistance Data

Electrical resistance and resistivity were measured with various types of electrodes to evaluate the moisture content of wood. The conventional two-pin method, electrically conductive fabrics, and multi-pin electrodes were used to measure the electrical resistance of Japanese larch (Larix kaempferi) wood, and a four-pin probe was used for resistivity measurements. The resistance in the longitudinal direction measured with the two-pin electrode was slightly affected by the dimensions of the wood sample, whereas the resistance measured with the conductive fabric and multi-pin electrodes was clearly affected by the end surface area in contact with the electrode and the length between electrodes. The resistivity calculated from the relationship between the electrical resistance and sample dimensions also showed differences based on the sample dimensions. The least squares regression model trained with the resistance data based on the two-pin method predicted the moisture content with a high coefficient of determination of 0.986. The four-pin probe produced the most stable resistivity regardless of the sample dimensions, making it a feasible approach for the moisture evaluation of large wood members.

scholarly journals Rapid assessment of oil and moisture content in seeds of oil flax using IR spectrometry

2020 ◽  
Vol 3 (183) ◽  
pp. 63-70
Author(s):  
S.G. Efimenko ◽  
◽  
S.K. Efimenko ◽  
Keyword(s):  
Moisture Content ◽  
High Speed ◽  
Oil Content ◽  
Near Infrared ◽  
Coat Color ◽  
Coefficient Of Determination ◽  
Near Infrared Reflectance ◽  
Calibration Models ◽  
Flax Seeds

We used near-infrared reflectance spectroscopy (NIRS) to assess biochemical parameters in whole oil flax seeds, regardless of differences in seed coat color of the samples. At the first stage of work, the set the task to develop calibration models for the MATRIX-I IR analyzer to determine the oil and moisture content in flax seeds. The carried out the research in the laboratory of biochemistry on brown and yellow seed samples of oil flax, grown in 2015-2020 in various agro-ecological conditions of the Russian Federation. We determined the oil content on an AMV 1006M NMR analyzer in accordance with the GOST 8.597- 2010 measurement procedure; we assessed the moisture content by the standard method of GOST 10856- 96. We used the results of determination of the oil and moisture content of the seeds of test lot in accordance with the accuracy indicator of the calibration of GOST 32749-2014 to verify the reliability of the developed models. We received the best indicators of the quality of calibration models (root-mean-square prediction error, coefficient of determination and the value of the residual deviation of prediction for the rank displayed on the graph) by determining the oil content (RMSEP = 0.27 %, R2 = 99.2 and RPD = 11.2) and moisture content (RMSEP = 0.06 %, R2 = 99.9 and RPD = 39). In the OPUS LAB program we developed the “Flax 51” method for mass analysis based on the developed calibration models for the determination of oil and moisture content in whole oil flax seeds (9-20 g) in a sample cell with a diameter of 51 mm. It enables the quick carrying out a preliminary assessment of the breeding material at a high speed – more than 120 samples in 7 hours without seed destruction.

scholarly journals EVALUATION OF THE ACCURACY OF EVPOTRANSPIRATION IN THE EVAPO MOBILE APPLICATION

2021 ◽  
Author(s):  
R. Vozhehova ◽  
◽  
P. Lykhovyd
Keyword(s):  
Graphical Models ◽  
Mobile Application ◽  
Polynomial Regression ◽  
Meteorological Data ◽  
Warm Period ◽  
Cold Period ◽  
Coefficient Of Determination ◽  
Percentage Error ◽  
Irrigation Planning

Abstract The article presents the results of the study on the accuracy of evapotranspiration in the EVAPO mobile application. The aim of the work is to provide recommendations on the effective use of the mobile application for the prompt, low-cost and convenient determination of evapotranspiration and planning the irrigation regime. Materials and methods. The study was conducted in the autumn of 2020 and in the summer of 2021 using meteorological data from Kherson Regional Hydrometeorological Station, which were used for reference calculations of evapotranspiration according to the method recommended by FAO (Penman-Monteith equation) in the ETo Calculator software. The calculated values of the reference evapotranspiration and those obtained in the EVAPO mobile application were compared with each other through the computation of the correlation coefficients, determination coefficients and mean absolute percentage errors to assess the accuracy of the data on the studied agrometeorological index in the mobile application. Statistical calculations and graphical models were performed using Microsoft Excel 365 spreadsheet processor. Polynomial regression was applied to calibrate and enhance the performance of original EVAPO application. Results. It was found that the EVAPO mobile application without additional calibration cannot provide the proper accuracy of the evapotranspiration calculation. During the cold period of the year (October-November) the mean absolute percentage error was 137.02 %, and during the warm period (May-August) it was 41.43 %. The general error of the calculation in the mobile application compared to the ETo Calculator reference values was 88.75 %. At the same time, EVAPO makes it possible to accurately track the trend of evapotranspiration dynamics, the coefficient of determination of the model is 0.86. In the warm period of the year, there is a tendency to overestimate the value of evapotranspiration, and in the cold period of the year, no clear pattern was found. The evapotranspiration values adjusted by the polynomial regression model obtained in the EVAPO mobile application allow their use in operational irrigation planning. Conclusions. The EVAPO mobile application is a convenient, accessible tool for the rapid assessment of evapotranspiration. However, its implementation on the territory of Ukraine cannot be recommended without preliminary calibration for each specific agroclimatic zone due to enormous errors in the estimation of evapotranspiration value.

scholarly journals Prediction of Hourly Solar Radiation in Amman-Jordan by Using Artificial Neural Networks

2017 ◽  
Vol 14 (2) ◽  
Keyword(s):  
Solar Radiation ◽  
Meteorological Data ◽  
Coefficient Of Determination ◽  
Narx Models ◽  
Ann Models ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Nonlinear Autoregressive ◽  
Yearly Data

In this study, three Artificial Neural Network (ANN) models (Feedforward network, Elman, and Nonlinear Autoregressive Exogenous (NARX)) were used to predict hourly solar radiation in Amman, Jordan. The three models were constructed and tested by using MATLAB software. Meteorological data for the years from 2000 to 2010 were used to train the ANN while the yearly data of 2011 was used to test it. It was found that ANN technique may be used to estimate the hourly solar radiation with an excellent accuracy, and the coefficient of determination of Elman, feedforward and NARX models were found to be 0.97353, 0.97376, and 0.99017, respectively. The obtained results showed that NARX model has the best ability to predict the required solar data, while Elman and feedforward models have the lowest ability to predict it.

scholarly journals Methods for overcoming seed dormancy in Ormosia arborea seeds, characterization and harvest time

2014 ◽  
Vol 36 (3) ◽  
pp. 318-325 ◽  
Author(s):  
Aparecida Leonir da Silva ◽  
Denise Cunha Fernandes dos Santos Dias ◽  
Liana Baptista de Lima ◽  
Glaucia Almeida de Morais
Keyword(s):  
Moisture Content ◽  
The Other ◽  
Seedling Production ◽  
Harvest Time ◽  
Dormancy Breaking ◽  
Drying Time ◽  
High Germination ◽  
Mother Plants ◽  
Second Period

Ormosia arborea, a Leguminosae, presents seeds with tegumentary dormancy. The purpose of this study was to evaluate the efficiency of dormancy breaking methods, characterize seeds obtained from different mother plants, and to determine the best period to collect Ormosia arborea seeds. The seeds were harvested from mother plants in two different periods (June and August/2011). The seeds were then subjected to biometrical analyses, determination of moisture content and germination tests. Determination of the soaking curve and evaluation of the dormancy breaking methods were performed using the seeds collected in the second period. The soaking curve confirmed the tegumentary dormancy, and the chemical scarification for 15 minutes was the more adequate procedure to overcome this dormancy. The biometry revealed average values higher than those on literature, and there was difference between both harvesting periods. The mass correlates with the other evaluated parameters, and can be indicated for selecting seeds for seedling production. The two harvesting periods of Ormosia arborea seeds were considered appropriated for seed supplying, due to the high germination potential. Nevertheless, the best period for harvesting is when fruits are already opened, mature, and with low moisture content (no additional drying time needed), what hinders the occurrence of fungi.

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