Management of Plant Disease Epidemics with Irrigation Practices

Filho, Adalberto Corrêa Café; Lopes, C. A.; Rossato, Maurício

doi:10.5772/intechopen.78253

Cited by 23 publications

(12 citation statements)

References 62 publications

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“…«For the oomycetes and bacteria associated to aerial plant organs, due to their strong dependency on free water and high humidity, drip irrigation might be the appropriate choice. Among the true fungi, the effects of the irrigation system and management differ, and species of dry and wet spores respond distinctly to each individual method» [24]. Nematodes and oomycetes need free water in the soil for their active distribution.…”

Section: Resultsmentioning

confidence: 99%

“…Thus, for oomycetes, bacteria and fungi associated with plant roots, the best method to avoid their reproduction and spreading can be using of sprinklers; for nematodes on the root -drip irrigation and sprinklers. Viruses transmitting with their vectors, can be controlled by sprinkle irrigation, which disrupts the contact of the insect with the plant [24]. The knowledge of the causal agent is important for deciding the irrigation method and is the key to obtain high quality yields.…”

Section: Resultsmentioning

confidence: 99%

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Technology Improvement for Seedling Growing Method of Echinacea Purpurea Under Drip Irrigation

Nv¹,

La²,

Lt³

et al. 2020

JRS

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Development of new technological methods of cultivation of traditional medicinal crops and improvement of existing ones are the main ways to increase production of pharmaceutical raw materials for pharmacy uses.Today, the main limiting factor in the increasing in the Echinacea purpurea production under the conditions of Ukrainian Forest-Steppe zone is lack of moisture during spring and the start of culture vegetation. This lack is caused by global climate changes. Another deterrent is formed by plant diseases leading to losses in yield of raw materials and seeds. Diseases also can cause decrease in of biologically active substances (BAA) content and sometimes even full loss of crops.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Technology Improvement for Seedling Growing Method of Echinacea Purpurea Under Drip Irrigation

Nv¹,

La²,

Lt³

et al. 2020

JRS

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show abstract

“…Therefore, studies need to be made to determine disease development, soil moisture levels and rainfall during those critical periods to assess influences on the pathogen and olive tree yields. Evidentially the response of any given soil-borne disease to the range of ways of managing irrigation varies widely and must be addressed for each individual plant-pathogen system [ 74 ].…”

Section: Discussionmentioning

confidence: 99%

Climatic drivers of Verticillium dahliae occurrence in Mediterranean olive-growing areas of southern Spain

et al. 2020

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Verticillium wilt, caused by the soil-borne fungus Verticillium dahliae, is one of the most harmful diseases in Mediterranean olive-growing areas. Although, the effects of both soil temperature and moisture on V. dahliae are well known, there is scant knowledge about what climatic drivers affect the occurrence of the pathogen on a large scale. Here, we investigate what climatic drivers determine V. dahliae occurrence in olive-growing areas in southern Spain. In order to bridge this gap in knowledge, a large-scale field survey was carried out to collect data on the occurrence of V. dahliae in 779 olive groves in Granada province. Forty models based on competing combinations of climatic variables were fitted and evaluated using information-theoretic methods. A model that included a multiplicative combination of seasonal and extreme climatic variables was found to be the most viable one. Isothermality and the seasonal distribution of precipitation were the most important variables influencing the occurrence of the pathogen. The isothermal effect was in turn modulated by the seasonality of rainfall, and this became less negative as seasonality increases. Thus, V. dahliae occurs more frequently in olive-growing areas where the day-night temperature oscillation is lower than the summer-winter one. We also found that irrigation reduced the influence of isothermality on occurrence. Our results demonstrate that long-term compound climatic factors rather than “primary” variables, such as annual trends, can better explain the spatial patterns of V. dahliae occurrence in Mediterranean, southern Spain. One important implication of our study is that appropriate irrigation management, when temperature oscillation approaches optimal conditions for V. dahliae to thrive, may reduce the appearance of symptoms in olive trees.

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“…The most important methods for controlling early blight are cultural control, which involves effective soil, nutrient, and crop management, as well as the use of fungicidal chemicals. Fungus induces Septoria leaf spot on tomato plants [38,39], which releases tomatinase enzyme, which speeds up the degradation of tomato steroidal glycoalkaloids α-tomatine [40,41]. The fungus induces the target spot disease in tomato plants [42,43].…”

Section: Pathogens Of Tomato Leavesmentioning

confidence: 99%

Automatic and Reliable Leaf Disease Detection Using Deep Learning Techniques

et al. 2021

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Plants are a major source of food for the world population. Plant diseases contribute to production loss, which can be tackled with continuous monitoring. Manual plant disease monitoring is both laborious and error-prone. Early detection of plant diseases using computer vision and artificial intelligence (AI) can help to reduce the adverse effects of diseases and also overcome the shortcomings of continuous human monitoring. In this work, we propose the use of a deep learning architecture based on a recent convolutional neural network called EfficientNet on 18,161 plain and segmented tomato leaf images to classify tomato diseases. The performance of two segmentation models i.e., U-net and Modified U-net, for the segmentation of leaves is reported. The comparative performance of the models for binary classification (healthy and unhealthy leaves), six-class classification (healthy and various groups of diseased leaves), and ten-class classification (healthy and various types of unhealthy leaves) are also reported. The modified U-net segmentation model showed accuracy, IoU, and Dice score of 98.66%, 98.5%, and 98.73%, respectively, for the segmentation of leaf images. EfficientNet-B7 showed superior performance for the binary classification and six-class classification using segmented images with an accuracy of 99.95% and 99.12%, respectively. Finally, EfficientNet-B4 achieved an accuracy of 99.89% for ten-class classification using segmented images. It can be concluded that all the architectures performed better in classifying the diseases when trained with deeper networks on segmented images. The performance of each of the experimental studies reported in this work outperforms the existing literature.

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Management of Plant Disease Epidemics with Irrigation Practices

Cited by 23 publications

References 62 publications

Technology Improvement for Seedling Growing Method of Echinacea Purpurea Under Drip Irrigation

Technology Improvement for Seedling Growing Method of Echinacea Purpurea Under Drip Irrigation

Climatic drivers of Verticillium dahliae occurrence in Mediterranean olive-growing areas of southern Spain

Automatic and Reliable Leaf Disease Detection Using Deep Learning Techniques

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