Strawberry powdery mildew (PM) is a serious disease that has significant impact on strawberry pro... more Strawberry powdery mildew (PM) is a serious disease that has significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVM) and knearest neighbors (kNN). Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM disease were acquired under artificial cloud lighting condition. Color cooccurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The classifiers were experimented with i...
Introducing machine vision-based automation to the agricultural sector is essential to meet the f... more Introducing machine vision-based automation to the agricultural sector is essential to meet the food demand of a rapidly growing population. Furthermore, extensive labor and time are required in agriculture; hence, agriculture automation is a major concern and an emerging subject. Machine vision-based automation can improve productivity and quality by reducing errors and adding flexibility to the work process. Primarily, machine vision technology has been used to develop crop production systems by detecting diseases more efficiently. This review provides a comprehensive overview of machine vision applications for stress/disease detection on crops, leaves, fruits, and vegetables with an exploration of new technology trends as well as the future expectation in precision agriculture. In conclusion, research on the advanced machine vision system is expected to develop the overall agricultural management system and provide rich recommendations and insights into decision-making for farmers.
An automated prototype variable rate (VR) sprayer was developed for control of 8 individual nozzl... more An automated prototype variable rate (VR) sprayer was developed for control of 8 individual nozzles on a 6.1 m sprayer boom for in-season, site-specific application of agrochemicals on weeds. The sprayer boom was divided into 8 sections and mounted behind an all-terrain vehicle (ATV) at 76.2 cm above the ground. The variable-rate control system consisted of 8 ultrasonic sensors (one per spray section) mounted on a separate boom in front of the ATV, DICKEY-john Land Manager II controller and flow valve, solenoid valves and an 8-channel variable rate controller interfaced to a Pocket PC (PPC) using wireless Bluetooth ® radio with Windows Mobile ® compatible software. This type of VR sprayer does not use prescription maps, but relies on sensors to provide real-time weed detection information which is used to dispense correct agrochemical rates for the weeds. The sprayer can be used for in-season, spot application (SA) of agrochemicals by activating specific boom sections where the weeds have been detected. Two wild blueberry fields have been selected in central Nova Scotia to evaluate the accuracy of the VR sprayer. Water sensitive papers (targets) were stapled to weeds randomly selected in two tracks of each field. The papers were orientated parallel to the ground. The percent area coverage (PAC) of the sprayed targets with both SA and uniform application was calculated by an imaging system. Non significance of the t-test for uniform versus SA targets PAC indicated that there was no significant bias in the SA and that the SA was accurate. The PAC with both applications ranged from 10.01% to 81.22% and from 5.39% to 72.67% in field 1 and field 2, respectively. Weed heights at selected points were measured and related with percent area coverage to examine the sprayer performance for spray application. Linear regression analysis showed that weed heights were significantly correlated (R 2 ranged from 0.60 to 0.75) with percent area coverage of the targets in selected fields with both applications. It is proposed that herbicide should be applied at early stage of weed growth (weed height ranged from 35 cm to 55 cm and plant height ranged from 12 cm to 30 cm) for appropriate application with these specific VR sprayer arrangements. Based on these results, the VR sprayer was efficient and accurate enough for spot-application of agrochemicals usage in wild blueberry fields.
ABSTRACT The present study assessed the ability of a low cost dual-view computer-vision system (C... more ABSTRACT The present study assessed the ability of a low cost dual-view computer-vision system (CVS) to measure volume and color co-occurrence image textural features of apple slices to find the end of drying process by comparing physical texture parameters and moisture content. Apple slices were dried at three different temperatures (40, 60 and 80 °C) and their volumes were measured with both the CVS and a caliper. The physical texture parameters and image textural features were measured according to the moisture content. While the CVS can be used to measure the volume of the apple slices during the drying process, the volume was not a good indicator of the end of drying because of porosity development. The peak force and initial slope of physical texture showed a significant correlation with H3, H5 and S2 and H3, H5 and S11 of image texture features, respectively. Eleven image texture features correlate well with the moisture content (R2 > 0.9) and also had a high correlation between each other. The uniformity of intensity (I1) of image feature was a good indicator of the end of drying because of the close correlations with moisture content. The drying times according to the moisture content and the uniformity of intensity were 4.31 ± 0.313 h and 4.42 ± 0.125 h, respectively.
Strawberry powdery mildew (PM) is a serious disease that has significant impact on strawberry pro... more Strawberry powdery mildew (PM) is a serious disease that has significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVM) and knearest neighbors (kNN). Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM disease were acquired under artificial cloud lighting condition. Color cooccurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The classifiers were experimented with i...
Introducing machine vision-based automation to the agricultural sector is essential to meet the f... more Introducing machine vision-based automation to the agricultural sector is essential to meet the food demand of a rapidly growing population. Furthermore, extensive labor and time are required in agriculture; hence, agriculture automation is a major concern and an emerging subject. Machine vision-based automation can improve productivity and quality by reducing errors and adding flexibility to the work process. Primarily, machine vision technology has been used to develop crop production systems by detecting diseases more efficiently. This review provides a comprehensive overview of machine vision applications for stress/disease detection on crops, leaves, fruits, and vegetables with an exploration of new technology trends as well as the future expectation in precision agriculture. In conclusion, research on the advanced machine vision system is expected to develop the overall agricultural management system and provide rich recommendations and insights into decision-making for farmers.
An automated prototype variable rate (VR) sprayer was developed for control of 8 individual nozzl... more An automated prototype variable rate (VR) sprayer was developed for control of 8 individual nozzles on a 6.1 m sprayer boom for in-season, site-specific application of agrochemicals on weeds. The sprayer boom was divided into 8 sections and mounted behind an all-terrain vehicle (ATV) at 76.2 cm above the ground. The variable-rate control system consisted of 8 ultrasonic sensors (one per spray section) mounted on a separate boom in front of the ATV, DICKEY-john Land Manager II controller and flow valve, solenoid valves and an 8-channel variable rate controller interfaced to a Pocket PC (PPC) using wireless Bluetooth ® radio with Windows Mobile ® compatible software. This type of VR sprayer does not use prescription maps, but relies on sensors to provide real-time weed detection information which is used to dispense correct agrochemical rates for the weeds. The sprayer can be used for in-season, spot application (SA) of agrochemicals by activating specific boom sections where the weeds have been detected. Two wild blueberry fields have been selected in central Nova Scotia to evaluate the accuracy of the VR sprayer. Water sensitive papers (targets) were stapled to weeds randomly selected in two tracks of each field. The papers were orientated parallel to the ground. The percent area coverage (PAC) of the sprayed targets with both SA and uniform application was calculated by an imaging system. Non significance of the t-test for uniform versus SA targets PAC indicated that there was no significant bias in the SA and that the SA was accurate. The PAC with both applications ranged from 10.01% to 81.22% and from 5.39% to 72.67% in field 1 and field 2, respectively. Weed heights at selected points were measured and related with percent area coverage to examine the sprayer performance for spray application. Linear regression analysis showed that weed heights were significantly correlated (R 2 ranged from 0.60 to 0.75) with percent area coverage of the targets in selected fields with both applications. It is proposed that herbicide should be applied at early stage of weed growth (weed height ranged from 35 cm to 55 cm and plant height ranged from 12 cm to 30 cm) for appropriate application with these specific VR sprayer arrangements. Based on these results, the VR sprayer was efficient and accurate enough for spot-application of agrochemicals usage in wild blueberry fields.
ABSTRACT The present study assessed the ability of a low cost dual-view computer-vision system (C... more ABSTRACT The present study assessed the ability of a low cost dual-view computer-vision system (CVS) to measure volume and color co-occurrence image textural features of apple slices to find the end of drying process by comparing physical texture parameters and moisture content. Apple slices were dried at three different temperatures (40, 60 and 80 °C) and their volumes were measured with both the CVS and a caliper. The physical texture parameters and image textural features were measured according to the moisture content. While the CVS can be used to measure the volume of the apple slices during the drying process, the volume was not a good indicator of the end of drying because of porosity development. The peak force and initial slope of physical texture showed a significant correlation with H3, H5 and S2 and H3, H5 and S11 of image texture features, respectively. Eleven image texture features correlate well with the moisture content (R2 > 0.9) and also had a high correlation between each other. The uniformity of intensity (I1) of image feature was a good indicator of the end of drying because of the close correlations with moisture content. The drying times according to the moisture content and the uniformity of intensity were 4.31 ± 0.313 h and 4.42 ± 0.125 h, respectively.
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Papers by Young Ki Chang