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    New Zealand willows (Salix spp.), their metabolites and their plant-herbivore interactions : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Ecology at Massey University, Manawatu, New Zealand
    (Massey University, 2024-12-19) De Oliveira Mota, Claryssa
    New Zealand is a unique environment which affects how species behave, survive and interact with each other. Introduced species of willow (Salix spp) are used in New Zealand for various purposes, and several varieties (clones) have been developed (Gunawardana et al., 2014; McIvor, 2013). Various insect species attack willows in New Zealand. It is not yet known how the New Zealand environment would affect the secondary metabolites and species resistance to insect pests in willows, and host preferences of some pests have not yet been characterized. In my thesis I aimed to characterize chemistry (metabolites and volatile organic compounds) in several willow clones, as well as differences in clone preference in insect pests – giant willow aphid (GWA) Tuberolachnus salignus Gmelin, 1790 (Hemiptera: Aphididae) and red gall sawfly Pontania proxima Serville, 1823 (Hymenoptera: Tenthredinidae). The incidence and chemical aspects of galling by P. proxima on New Zealand willow clones has not yet been characterised. This information is vital for the selection of resistant cultivars and to understand potential indirect impacts on other insect species (e.g., natural enemies of competing herbivores). Chapter 1 is a literature review on plant secondary metabolites and their role in plant defence against insect herbivores, as well as review of willow insect pests with emphasis on P. proxima and giant willow aphid. This chapter questions how much we know about willows in New Zealand, what differences they present from the willows from other parts of the world, and how the New Zealand environment affects the insects that feed on willows. Do insect pests preferers the same species/clones in New Zealand as in other parts of the world? What makes P. proxima and GWA prefer certain clones? What makes some clones resistant and others susceptible? In Chapter 2, I explored the levels of damage caused by P. proxima to willow clones. Twelve willow clones (PN221, PN249, PN721, PN693, PN357, PN676, NZ1040, NZ1130, PN218, PN356, PN736 and PN742) used in New Zealand were selected and surveyed for P. proxima damage. Willows showed a range of resistance levels to P. proxima. These levels of resistance show as differences in P. proxima larval development (explored in Chapter 3), damage level and gall size. For example, clones PN221 and PN249 did not present galls, while clones PN736 and PN742 presented the highest level of damage in our field survey. Other clones had an intermediate level of damage, and some clones present with malformed galls. The survey also found that top sections of shoots had a significantly higher level of damage, while location and side of the plant had no effect, possibly because the experimental field was homogeneous in sun exposure and other abiotic factors such as soil fertility. Gall induction is still a mystery in the Salix spp - P. proxima system, mainly because the cecidogenic factor is not yet known. The clones used in Chapter 2 were further investigated in Chapter 3 to link plant resistance to P. proxima development and growth. Larval development was investigated and measured, and the phenolic and nutrient content of willow leaves was quantified. The resistance of willow clones to P. proxima appears to be guided by a combination of physical and chemical attributes of the plants. Overall, P. proxima appears to prefer clones with a lower phenolic content and lower leaf pilosity. This preference, however, is in contrast with previous European studies in which P. proxima showed preference for a higher level of phenolics. Plant phenology seems also to play a role in preference, with P. proxima preferring to oviposit in clones which develop earlier in the season, even if those clones do not offer optimal conditions for larval development. Among the studied clones, PN 221 and PN 249 (S. purpurea) showed the highest resistance levels to P. proxima with no galls. Among the clones that developed galls, PN676 (S. alba, female) was the clone that produced the smallest larva and is therefore considered more resistant. The fact that P. proxima has shifted its preference from willows with a high content of phenolic glycosides in its native range to willows with a low content of phenolic glycosides in New Zealand may be due to low predator pressure in New Zealand. Further studies are needed to investigate this shift and test this hypothesis. In Chapter 4, I investigated the metabolomics profiles of six willow clones (PN220, PN249, PN386, NZ04-106-073, PN218 and NZ1040) and whether the differences in metabolites influence the preference of insect pests to the six clones. With the metabolomic profile we are expecting to see differences in chemistry between the clones and their influence on the plants’ pest resistance. The most important compounds found were apigenin, isorhamnetin-3-O-glucoside, procyanidin B2, epicatechin, petunidin-3-O-β-glucopyranoside, kaempferide, kaempferol-3-glucuronide, quercetin-7-O-rhamnoside, unknown 1, isorhamnetin, peonidin-3-O-β-D-glucoside, luteolin-7-O-glucoside, procyanidin B1 and isorhamnetin-3-O-rutinoside. Due to the limited number of clones and limited number of replicates, I cannot draw definitive conclusions about the pattern of secondary metabolites in relation to resistance to the two insect herbivores – P. proxima and GWA. To our knowledge the direct effect of those metabolites on P. proxima and GWA was never tested. The resistance to P. proxima and GWA appears to be more correlated with phenological and morphological features of willow plants than with their chemistry. Chapter 5 is an investigation of the volatile profile of willow clones studied in Chapter 4. With the metabolomic and volatile profile we hoped to elucidate whether the chemistry of the clone influences clone resistance to P. proxima and GWA. These volatile organic compounds (VOCs) included two green leaf volatiles (GLVs), (Z)-3-Hexenyl acetate and (Z)-3-Hexenyl-α-methylbutyrate; one monoterpenes, (Z)-β-Ocimene; and eight sesquiterpenes, β-Elemene α-Cubebene, Copaene, Germacrene D, (Z)-β-Caryophyllene, (E)-α-Bergamotene, (α)-Farnesene, δ-Cadinene. The results show that willow clones have highly species-specific VOC blends, a conclusion backed up by other authors. Due to the limited number of clones and limited number of replicates, it was not possible to draw definitive conclusions about the pattern of volatile emissions in relation to resistance to the two insect herbivores – P. proxima and GWA. Resistance to P. proxima and GWA appears to be more correlated with phenological and morphological features of willow plants than with their VOC emissions. Chapter 6 is the recapitulation of the conclusions of the experimental chapters and relating it with the existing literature. The twelve willows tested in chapters 2-5 showed a range of metabolites, leaf volatiles (VOCs), and resistance levels to P. proxima which manifested as differences in P. proxima larval development, damage level and gall size. Overall, P. proxima appears to prefer clones with a lower phenolic content and lower leaf pilosity and those that develop earlier in the season. The VOCs in willow clones appear to be species-specific and are not clearly linked to insect resistance. We suggest that the levels of phenolic compounds and pilosity together better explain the preference of oviposition of P. proxima. The highest amount of secondary metabolites was found in clones NZ04-106-073 (S. lasiolepis × S. viminalis, Female), PN676 (S. alba L., Female) and PN221 (S. purpurea L., Male). NZ04-106-073 also showed the highest emission of VOCs. The most susceptible clones to P. proxima were PN736 (S. fragilis L., Male) and PN742 (S. fragilis L., Male). Tree willows are preferred by P. proxima to shrubs. Among the studied clones, PN221 and PN249 (both S. purpurea) showed the highest resistance levels to P. proxima with no galls. Among the clones that developed galls, PN676 (S. alba, female) was the clone that produced the smallest larvae and is therefore considered more resistant.
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    Improving weed control options for ryegrass/clover pastures that contain plantain (Plantago lanceolata) : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy (PhD) in Plant Science at Massey University, Manawatū, New Zealand
    (Massey University, 2023) Shrivastav, Nidhi
    The inclusion of narrow-leaved plantain (Plantago lanceolata) in the traditional pasture system of perennial ryegrass (Lolium perenne) and white clover (Trifolium repens) is preferred by many New Zealand farmers nowadays to assist with nitrogen loss mitigation and to improve summer production. Control of weeds using selective herbicides becomes more difficult after adding extra species to a grass/clover sward. The work in this thesis investigated weed control options for ryegrass/clover pastures in New Zealand that contain plantain. This included determining the tolerance of plantain to different herbicides and identifying the herbicide options most effective for weeds. There has been some breeding of phenoxy herbicide tolerance into the Agritonic cultivar of plantain in New Zealand. In this thesis, the level of tolerance in Agritonic plantain was compared with Tonic plantain to MCPB, MCPA, MCPB/MCPA mix, 2,4-D and 2,4-DB in two glasshouse experiments. The tolerance generally appeared to be 1.3 to 3.4-fold, so not large but potentially useful. The thesis also investigated the tolerance of plantain, white clover and perennial ryegrass to a range of herbicides applied to a mixed sward of these species at an early stage of establishment in spring. The effectiveness of the herbicides was also assessed for controlling weeds that established within the swards using two field trials. Half of the recommended rate of MCPB was less damaging to both cultivars of plantain than the recommended rates of MCPB and MCPB/MCPA, but could not control most of the weeds present. The recommended rate of MCPB/MCPA had very little detrimental effect on young clover or Agritonic plantain and gave good weed control. Flumetsulam was fairly safe to use in the plantain-based pasture though it suppressed plantain initially, which recovered after 3-6 months in each trial. Bentazone was safe for the plantain, ryegrass and clover and suppressed most of the weeds, but only if there was no rainfall in the hours after herbicide application. Mowing after each harvest controlled redroot, black nightshade and fathen and also suppressed docks temporarily. The most effective weed control strategy that was also selective involved a combination of bentazone + half rates of MCPB/MCPA followed by mowing which gave useful control of weeds including docks for many months. The mechanism of tolerance of Agritonic plantain to 2,4-D was investigated using radiolabeled herbicide (¹⁴C-2,4-D) in two experiments. Absorption/translocation and metabolism of the herbicide was studied in both this cultivar and Tonic plantain for comparison. The tolerance to 2,4-D in Agritonic plantain appeared to involve reduced translocation of the herbicide, though reduced absorption may have also contributed. Two glasshouse experiments were conducted to test the tolerance of mature plantain plants (both Agritonic and Tonic) to application of some herbicides suitable for use in weed wipers (glyphosate, clopyralid, aminopyralid, dicamba, picloram and triclopyr) to the seed-heads, simulating potential contact during wiper application to pasture weeds. Aminopyralid and a low rate of glyphosate were found to be the least damaging treatments and should be safe to use for weed wiping within swards containing plantain. A high rate of glyphosate and a glyphosate/metsulfuron mix caused the most damage to plantain, and this damage was greater following simulated rainfall after application.
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    Deep learning-based approaches for plant disease and weed detection : a thesis by publications presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Engineering, Massey University, Auckland, New Zealand
    (Massey University, 2022) Saleem, Muhammad Hammad
    To match the ever-growing food demand, the scientific community has been actively focusing on addressing the various challenges faced by the agricultural sector. The major challenges are soil infertility, abrupt changes in climatic conditions, scarcity of water, untrained labor, emission of greenhouse gases, and many others. Moreover, plant diseases and weeds are two of the most important agricultural problems that reduce crop yield. Therefore, accurate detection of plant diseases and weeds is one of the essential operations to apply targeted and timely control measures. As a result, this can improve crop productivity, reduce the environmental effects and financial losses resulting from the excessive application of fungicide/herbicide spray on diseased plants/weeds. Among various ways of plant disease and weed detection, image-based methods are significantly effective for the interpretation of the distinct features. In recent years, image-based deep learning (DL) techniques have been reported in literature for the recognition of weeds and plant diseases. However, the full potential of DL has not yet been explored as most of the methods rely on modifications of the DL models for well-known and readily available datasets. The current studies lack in several ways, such as addressing various complex agricultural conditions, exploring several aspects of DL, and providing a systematic DL-based approach. To address these research gaps, this thesis presents various DL-based methodologies and aims to improve the mean average precision (mAP) for the identification of diseases and weeds in several plant species. The research on plant disease recognition starts with a publicly available dataset called PlantVillage and comparative analyses are conducted on various DL feature extractors, meta-architectures, and optimization algorithms. Later, new datasets are generated from various local New Zealand horticultural farms, named NZDLPlantDisease-v1 & v2. The proposed datasets consist of healthy and diseased plant organs of 13 economically important horticultural crops of New Zealand, divided into 48 classes. A performance-optimized DL model and a transfer learning-based approach are proposed for the detection of plant diseases using curated datasets. The weed identification has been performed on an open-source dataset called DeepWeeds. A two-step weed detection pipeline is presented to show the performance improvement of the deep learning model with a significant margin. The results for both agricultural tasks achieve superior performance compared to the existing method/default settings. The research outcomes elaborate the practical aspects and extended potential of DL for selected agricultural applications. Therefore, this thesis is a benchmark step for cost-effective crop protection and site-specific weed management systems (SSWM).