Use of fungicides for the management of Uromycladium acaciae in Acacia mearnsii plantations, South Africa
- Authors: Payn, Richard Guy
- Date: 2017
- Subjects: Fungicides -- South Africa Acacia mearnsii -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/20500 , vital:29299
- Description: South Africa has ca. 110 000 ha planted to Acacia mearnsii with 85% of the revenue from the species obtained from the timber, and 15% from the bark. Since its detection in 2013, wattle rust (recently identified as Uromycladium acaciae) has spread throughout the black wattle plantation area in KwaZulu-Natal, and from 2015 it was recorded in southern Mpumalanga. The pathogen affects trees of all age classes, causing a reduction in growth, as well as mortality with severe infection. Research has been initiated to determine a number of strategies for the management of the pathogen. These strategies include understanding wattle rust biology and epidemiology, planting tolerant or resistant black wattle, the testing and use of fungicide for management, and remote sensing and process based modelling to assess black wattle loss and high risk areas. These, with the outcomes from this research, will be combined into an overall Integrated Pest Management plan. Of the various strategies, the management of wattle rust with the use of fungicides is important, not only as it will have the potential to reduce the negative impacts of wattle rust, but it will also provide an interim solution until the other research areas provide alternative solutions. To address the current lack of fungicides available (and knowledge around their application) for the management of wattle rust, a series of trials were implemented to screen fungicides for their potential use, extend periods between the re-application of fungicide (if possible), the linking of symptoms to Disease Expression to aid with the timing of application, and the cost:benefits associated with fungicide use. Prior to the initiation of research into managing wattle rust, no fungicides were registered in South Africa for the control of wattle rust. In October / November 2014, three A. mearnsii trials were initiated in the KwaZulu-Natal Midlands and SE Mpumulanga where fungicides were tested at varying rates for the control of wattle rust. Wattle rust had a significant and negative impact on tree growth, irrespective of site and/or previous infection. All fungicides tested and at all the rates applied, proved effective for control. For the most effective control of wattle rust, fungicides should be applied as a preventative, rather than corrective measure. In October 2015 a trial was initiated in southern KwaZulu-Natal to determine the effectiveness of varied application schedules and adjuvants of fungicides for the management of wattle rust. Two trials had initially been initiated but one had to be abandoned due to browsing damage. Wattle rust had a significant impact upon Groundline Diameter and Biomass Index but not Height. All of the adjuvants used and application schedules were effective in managing wattle rust. The most effective fungicide application used will therefore be based upon cost and in a manner that will reduce the likelihood of acquired resistance developing in wattle rust populations. The timing of fungicide application is necessary for optimal use of these fungicides. Fungicide applications could potentially be linked to the emergence of different wattle rust symptoms to optimize fungicide use. Wattle rust symptoms were analysed from the untreated control plots of two trials, one in the KwaZulu-Natal midlands and one in southern KwaZulu-Natal, to determine whether wattle rust Disease expression could be linked to black wattle tree growth. Regression trees were used for the analysis, as linear and multiple regression techniques would be unsuitable for the data. Regression trees were overfitted and attempts at testing the robustness of the model by cross-validation were unsuccessful. No individual symptom emerged as a significant predictor of tree growth, indicating that fungicide application should take place with the onset of any of the wattle rust symptoms tested. The results from six trials testing the use of fungicides for managing wattle rust were compared to assess costs associated with fungicide use. Relative growth for Biomass Index was compared to untreated controls to obtain comparisons within and between sites. Costs versus benefit were compared using a two-way table to determine the most optimum treatment. The largest portion of treatment costs was attributed to the cost of fungicide. No single treatment was found to be optimal for the recommended rate of application. The use of adjuvants increased the cost of treatment, without additional benefit in growth. Control of wattle rust is beneficial, although costly if over-applied. Rotation-end data is required to determine whether fungicide use is economical for managing wattle rust over an extended period of time. As a limited number of fungicides, from a limited number of fungicide groups were screened, the screening of additional fungicides from different fungicide groups will provide an additional selection of fungicides. If these are used in combination or alternation, the likelihood of acquired resistance developing among wattle rust populations will be reduced. Linking fungicide applications with wattle rust epidemiological and climatic data will aid in optimal use of fungicides, by timing applications to coincide with epidemiological and climatic cues. Rotation end research comparing final yield on fungicide treated versus untreated black wattle is needed to fully understand the economics of fungicide use. This will also aid in the understanding of the impact of wattle rust on tree age.
- Full Text:
- Date Issued: 2017
- Authors: Payn, Richard Guy
- Date: 2017
- Subjects: Fungicides -- South Africa Acacia mearnsii -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/20500 , vital:29299
- Description: South Africa has ca. 110 000 ha planted to Acacia mearnsii with 85% of the revenue from the species obtained from the timber, and 15% from the bark. Since its detection in 2013, wattle rust (recently identified as Uromycladium acaciae) has spread throughout the black wattle plantation area in KwaZulu-Natal, and from 2015 it was recorded in southern Mpumalanga. The pathogen affects trees of all age classes, causing a reduction in growth, as well as mortality with severe infection. Research has been initiated to determine a number of strategies for the management of the pathogen. These strategies include understanding wattle rust biology and epidemiology, planting tolerant or resistant black wattle, the testing and use of fungicide for management, and remote sensing and process based modelling to assess black wattle loss and high risk areas. These, with the outcomes from this research, will be combined into an overall Integrated Pest Management plan. Of the various strategies, the management of wattle rust with the use of fungicides is important, not only as it will have the potential to reduce the negative impacts of wattle rust, but it will also provide an interim solution until the other research areas provide alternative solutions. To address the current lack of fungicides available (and knowledge around their application) for the management of wattle rust, a series of trials were implemented to screen fungicides for their potential use, extend periods between the re-application of fungicide (if possible), the linking of symptoms to Disease Expression to aid with the timing of application, and the cost:benefits associated with fungicide use. Prior to the initiation of research into managing wattle rust, no fungicides were registered in South Africa for the control of wattle rust. In October / November 2014, three A. mearnsii trials were initiated in the KwaZulu-Natal Midlands and SE Mpumulanga where fungicides were tested at varying rates for the control of wattle rust. Wattle rust had a significant and negative impact on tree growth, irrespective of site and/or previous infection. All fungicides tested and at all the rates applied, proved effective for control. For the most effective control of wattle rust, fungicides should be applied as a preventative, rather than corrective measure. In October 2015 a trial was initiated in southern KwaZulu-Natal to determine the effectiveness of varied application schedules and adjuvants of fungicides for the management of wattle rust. Two trials had initially been initiated but one had to be abandoned due to browsing damage. Wattle rust had a significant impact upon Groundline Diameter and Biomass Index but not Height. All of the adjuvants used and application schedules were effective in managing wattle rust. The most effective fungicide application used will therefore be based upon cost and in a manner that will reduce the likelihood of acquired resistance developing in wattle rust populations. The timing of fungicide application is necessary for optimal use of these fungicides. Fungicide applications could potentially be linked to the emergence of different wattle rust symptoms to optimize fungicide use. Wattle rust symptoms were analysed from the untreated control plots of two trials, one in the KwaZulu-Natal midlands and one in southern KwaZulu-Natal, to determine whether wattle rust Disease expression could be linked to black wattle tree growth. Regression trees were used for the analysis, as linear and multiple regression techniques would be unsuitable for the data. Regression trees were overfitted and attempts at testing the robustness of the model by cross-validation were unsuccessful. No individual symptom emerged as a significant predictor of tree growth, indicating that fungicide application should take place with the onset of any of the wattle rust symptoms tested. The results from six trials testing the use of fungicides for managing wattle rust were compared to assess costs associated with fungicide use. Relative growth for Biomass Index was compared to untreated controls to obtain comparisons within and between sites. Costs versus benefit were compared using a two-way table to determine the most optimum treatment. The largest portion of treatment costs was attributed to the cost of fungicide. No single treatment was found to be optimal for the recommended rate of application. The use of adjuvants increased the cost of treatment, without additional benefit in growth. Control of wattle rust is beneficial, although costly if over-applied. Rotation-end data is required to determine whether fungicide use is economical for managing wattle rust over an extended period of time. As a limited number of fungicides, from a limited number of fungicide groups were screened, the screening of additional fungicides from different fungicide groups will provide an additional selection of fungicides. If these are used in combination or alternation, the likelihood of acquired resistance developing among wattle rust populations will be reduced. Linking fungicide applications with wattle rust epidemiological and climatic data will aid in optimal use of fungicides, by timing applications to coincide with epidemiological and climatic cues. Rotation end research comparing final yield on fungicide treated versus untreated black wattle is needed to fully understand the economics of fungicide use. This will also aid in the understanding of the impact of wattle rust on tree age.
- Full Text:
- Date Issued: 2017
Using computer vision to categorize tyres and estimate the number of visible tyres in tyre stockpile images
- Authors: Eastwood, Grant
- Date: 2017
- Subjects: Tires -- Specifications Tires -- Recycling , Tires -- Maintenance and repair
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/16022 , vital:28313
- Description: Pressures from environmental agencies contribute to the challenges associated with the disposal of waste tyres, particularly in South Africa. Recycling of waste tyres in South Africa is in its infancy resulting in the historically undocumented and uncontrolled existence of waste tyre stockpiles across the country. The remote and distant locations of such stockpiles typically complicate the logistics associated with the collection, transport and storage of waste tyres prior to entering the recycling process. In order to optimize the logistics associated with the collection of waste tyres from stockpiles, useful information about such stockpiles would include estimates of the types of tyres as well as the quantity of specific tyre types found in particular stockpiles. This research proposes the use of computer vision for categorizing individual tyres and estimating the number of visible tyres in tyre stockpile images to support the logistics in tyre recycling efforts. The study begins with a broad review of image processing and computer vision algorithms for categorization and counting objects in images. The bag of visual words (BoVW) model for categorization is tested on two small data sets of tread tyre images using a random sub-sampling holdout method. The categorization results are evaluated using performance metrics for multiclass classifiers, namely the average accuracy, precision, and recall. The results indicated that corner-based local feature detectors combined with speeded up robust features (SURF) descriptors in a BoVW model provide moderately accurate categorization of tyres based on tread images. Two feature extraction methods for extracting features for use in training neural networks (NNs) for tyre count estimations in tyre stockpiles are proposed. The two feature extraction methods are used to describe images in terms of feature vectors that can be used as input for NNs. The first feature extraction method uses the BoVW model with histograms of oriented gradients (HOG) features collected from overlapping sub-images to create a visual vocabulary and describe the images in terms of their visual word occurrence histogram. The second feature extraction method uses the image gradient magnitude, gradient orientation, and edge orientations of edges detected using the Canny edge detector. A concatenated histogram is constructed from individual histograms of gradient orientations and gradient magnitude. The histograms are then used to train NNs using backpropogation to approximate functions from the feature vectors describing the images to scalar count estimations. The accuracy of visible object count predictions are evaluated using NN evaluation techniques to determine the accuracy of predictions and the generalization ability of the fit model. The count estimation experiments using the two feature extraction methods for input to NNs showed that fairly accurate count estimations can be obtained and that the fit model could generalize fairly well to unseen images.
- Full Text:
- Date Issued: 2017
- Authors: Eastwood, Grant
- Date: 2017
- Subjects: Tires -- Specifications Tires -- Recycling , Tires -- Maintenance and repair
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/16022 , vital:28313
- Description: Pressures from environmental agencies contribute to the challenges associated with the disposal of waste tyres, particularly in South Africa. Recycling of waste tyres in South Africa is in its infancy resulting in the historically undocumented and uncontrolled existence of waste tyre stockpiles across the country. The remote and distant locations of such stockpiles typically complicate the logistics associated with the collection, transport and storage of waste tyres prior to entering the recycling process. In order to optimize the logistics associated with the collection of waste tyres from stockpiles, useful information about such stockpiles would include estimates of the types of tyres as well as the quantity of specific tyre types found in particular stockpiles. This research proposes the use of computer vision for categorizing individual tyres and estimating the number of visible tyres in tyre stockpile images to support the logistics in tyre recycling efforts. The study begins with a broad review of image processing and computer vision algorithms for categorization and counting objects in images. The bag of visual words (BoVW) model for categorization is tested on two small data sets of tread tyre images using a random sub-sampling holdout method. The categorization results are evaluated using performance metrics for multiclass classifiers, namely the average accuracy, precision, and recall. The results indicated that corner-based local feature detectors combined with speeded up robust features (SURF) descriptors in a BoVW model provide moderately accurate categorization of tyres based on tread images. Two feature extraction methods for extracting features for use in training neural networks (NNs) for tyre count estimations in tyre stockpiles are proposed. The two feature extraction methods are used to describe images in terms of feature vectors that can be used as input for NNs. The first feature extraction method uses the BoVW model with histograms of oriented gradients (HOG) features collected from overlapping sub-images to create a visual vocabulary and describe the images in terms of their visual word occurrence histogram. The second feature extraction method uses the image gradient magnitude, gradient orientation, and edge orientations of edges detected using the Canny edge detector. A concatenated histogram is constructed from individual histograms of gradient orientations and gradient magnitude. The histograms are then used to train NNs using backpropogation to approximate functions from the feature vectors describing the images to scalar count estimations. The accuracy of visible object count predictions are evaluated using NN evaluation techniques to determine the accuracy of predictions and the generalization ability of the fit model. The count estimation experiments using the two feature extraction methods for input to NNs showed that fairly accurate count estimations can be obtained and that the fit model could generalize fairly well to unseen images.
- Full Text:
- Date Issued: 2017
Yield responses, mineral levels of forages and soil in old arable land planted to four legume pasture species in Lushington communal area, South Africa
- Authors: Gulwa, Unathi
- Date: 2017
- Subjects: Forage plants -- South Africa -- Eastern Cape Minerals in animal nutrition Communal rangelands -- South Africa -- Eastern Cape
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10353/2799 , vital:28091
- Description: This study was conducted in the old arable land located in Lushington communal area in the Eastern Cape province of South Africa. The objectives of the study were to assess the effect of legume introduction on biomass yield, forage and soil mineral levels of the arable lands planted to four leguminous pastures in four seasons. Planting was done in March and October 2008 in Lushington. All legumes were subjected to grow under rain fed conditions. Trifolium vesiculosum (arrowleaf clover), Lespedeza cuneata (sericea lespedeza), Trifolium repens (white clover) and Lotus corniculatus (birdsfoot trefoil) are the four forage legume species that were sampled for the purposes of this study. The four legume species persisted out of the fourteen species that were initially tested for adaptability and persistence in the environmental conditions of Lushington communal area. The legumes, grasses and soils from these legume plots were sampled to determine the effect of legume introduction on the forage yield, mineral contents of the companion grasses and soils over four seasons. Plant and soil samples were collected once in spring (November) 2013, summer (February), autumn (March) and winter (May) 2014 for biomass production, macro and micronutrients determination. Results indicated that legume inclusion and season affected (P < 0.05) the total dry matter (TDM) yield production. Plots with Lespedeza cuneata had the highest TDM (1843 kg/ha) and control plots had the least dry matter production (1091 kg/ha). Summer season provided the highest (P < 0.05) TDM compared to the other seasons. Both legume and grass quality was also affected (P < 0.05) by legume inclusion in different seasons. Accordingly, grasses harvested from Trifolium repens plot showed higher CP level (10.90 percent) than those harvested from other plots whereas the lowest grass CP content (6.90 percent) was measured in the control treatment. L. cuneate had the highest (P < 0.05) CP level (11.00 percent) and T. repens had the least CP (6.63 percent) level. Grasses harvested in autumn had the highest (P < 0.05) CP level (12.50 percent) and those harvested in winter had the least CP level (4.60 percent). Similarly, all legume pastures harvested in spring had superior (P < 0.05) CP (10.80 percent) levels and those harvested in winter had the least CP (3.50 percent) level. Legume inclusion had an effect (P < 0.05) on both grass and legume macro nutrient contents. Trifolium repens plot had the highest grass K (1.07 percent), Ca (1.50 percent) and Mg (1.83 percent), whereas there were lower K (0.12 percent), Ca (1.25 percent) and Mg (1.08 percent) contents in grasses harvested from the control and T. vesiculosum plots, respectively. In legumes, macro nutrient concentrations: K (0.68 percent), Ca (1.75 percent) were superior in the T. vesiculosum plot in comparison to other plots. Season also affected (P < 0.05) both grass and legume macro nutrient content. There was higher K (0.90 percent), Ca (1.30 percent) and Mg (0.94 percent) content in grasses harvested in autumn whereas there were lower levels in winter harvests. In legumes, superior K (0.74 percent) and Mg (1.87 percent) content were attained during spring while the least were measured in winter (0.07 percent) and autumn (0.75 percent), respectively. Likewise, both legume inclusion and season had an significant effect (P < 0.05) on the forages micronutrient levels. During spring, there was superior soil P content (36.28 mg/kg) while during autumn; there was less P (22.58 mg/kg) content. The highest SOC level (1.49 percent) was measured in the T. repens plot whereas the lowest SOC (1.15 percent) was attained in the control plot. The results of this study showed that grass legume mixtures produced forages with high nutrient content and herbage yield. Legume planting in the old arable lands has a potential to improve soil quality parameters such as soil P and SOC content.
- Full Text:
- Date Issued: 2017
- Authors: Gulwa, Unathi
- Date: 2017
- Subjects: Forage plants -- South Africa -- Eastern Cape Minerals in animal nutrition Communal rangelands -- South Africa -- Eastern Cape
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10353/2799 , vital:28091
- Description: This study was conducted in the old arable land located in Lushington communal area in the Eastern Cape province of South Africa. The objectives of the study were to assess the effect of legume introduction on biomass yield, forage and soil mineral levels of the arable lands planted to four leguminous pastures in four seasons. Planting was done in March and October 2008 in Lushington. All legumes were subjected to grow under rain fed conditions. Trifolium vesiculosum (arrowleaf clover), Lespedeza cuneata (sericea lespedeza), Trifolium repens (white clover) and Lotus corniculatus (birdsfoot trefoil) are the four forage legume species that were sampled for the purposes of this study. The four legume species persisted out of the fourteen species that were initially tested for adaptability and persistence in the environmental conditions of Lushington communal area. The legumes, grasses and soils from these legume plots were sampled to determine the effect of legume introduction on the forage yield, mineral contents of the companion grasses and soils over four seasons. Plant and soil samples were collected once in spring (November) 2013, summer (February), autumn (March) and winter (May) 2014 for biomass production, macro and micronutrients determination. Results indicated that legume inclusion and season affected (P < 0.05) the total dry matter (TDM) yield production. Plots with Lespedeza cuneata had the highest TDM (1843 kg/ha) and control plots had the least dry matter production (1091 kg/ha). Summer season provided the highest (P < 0.05) TDM compared to the other seasons. Both legume and grass quality was also affected (P < 0.05) by legume inclusion in different seasons. Accordingly, grasses harvested from Trifolium repens plot showed higher CP level (10.90 percent) than those harvested from other plots whereas the lowest grass CP content (6.90 percent) was measured in the control treatment. L. cuneate had the highest (P < 0.05) CP level (11.00 percent) and T. repens had the least CP (6.63 percent) level. Grasses harvested in autumn had the highest (P < 0.05) CP level (12.50 percent) and those harvested in winter had the least CP level (4.60 percent). Similarly, all legume pastures harvested in spring had superior (P < 0.05) CP (10.80 percent) levels and those harvested in winter had the least CP (3.50 percent) level. Legume inclusion had an effect (P < 0.05) on both grass and legume macro nutrient contents. Trifolium repens plot had the highest grass K (1.07 percent), Ca (1.50 percent) and Mg (1.83 percent), whereas there were lower K (0.12 percent), Ca (1.25 percent) and Mg (1.08 percent) contents in grasses harvested from the control and T. vesiculosum plots, respectively. In legumes, macro nutrient concentrations: K (0.68 percent), Ca (1.75 percent) were superior in the T. vesiculosum plot in comparison to other plots. Season also affected (P < 0.05) both grass and legume macro nutrient content. There was higher K (0.90 percent), Ca (1.30 percent) and Mg (0.94 percent) content in grasses harvested in autumn whereas there were lower levels in winter harvests. In legumes, superior K (0.74 percent) and Mg (1.87 percent) content were attained during spring while the least were measured in winter (0.07 percent) and autumn (0.75 percent), respectively. Likewise, both legume inclusion and season had an significant effect (P < 0.05) on the forages micronutrient levels. During spring, there was superior soil P content (36.28 mg/kg) while during autumn; there was less P (22.58 mg/kg) content. The highest SOC level (1.49 percent) was measured in the T. repens plot whereas the lowest SOC (1.15 percent) was attained in the control plot. The results of this study showed that grass legume mixtures produced forages with high nutrient content and herbage yield. Legume planting in the old arable lands has a potential to improve soil quality parameters such as soil P and SOC content.
- Full Text:
- Date Issued: 2017