| 1. |
- Ahmad, Waqas, et al.
(författare)
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Analysis of long term meteorological trends in the middle and lower Indus Basin of Pakistan-A non-parametric statistical approach
- 2014
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Ingår i: Global and Planetary Change. - : Elsevier BV. - 0921-8181 .- 1872-6364. ; 122, s. 282-291
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Tidskriftsartikel (refereegranskat)abstract
- The Indus basin of Pakistan is vulnerable to climate change which would directly affect the livelihoods of poor people engaged in irrigated agriculture. The situation could be worse in middle and lower part of this basin which occupies 90% of the irrigated area. The objective of this research is to analyze the long term meteorological trends in the middle and lower parts of Indus basin of Pakistan. We used monthly data from 1971 to 2010 and applied non-parametric seasonal Kendal test for trend detection in combination with seasonal Kendall slope estimator to quantify the magnitude of trends. The meteorological parameters considered were mean maximum and mean minimum air temperature, and rainfall from 12 meteorological stations located in the study region. We examined the reliability and spatial integrity of data by mass-curve analysis and spatial correlation matrices, respectively. Analysis was performed for four seasons (spring-March to May, summer-June to August-fall-September to November and winter-December to February). The results show that max. temperature has an average increasing trend of magnitude +0.16, +0.03, 0.0 and +0.04 degrees C/decade during all the four seasons, respectively. The average trend of min. temperature during the four seasons also increases with magnitude of +0.29, +0.12, +0.36 and +0.36 degrees C/decade, respectively. Persistence of the increasing trend is more pronounced in the min. temperature as compared to the max. temperature on annual basis. Analysis of rainfall data has not shown any noteworthy trend during winter, fall and on annual basis. However during spring and summer season, the rainfall trends vary from -1.15 to +0.93 and -3.86 to +2.46 mm/decade, respectively. It is further revealed that rainfall trends during all seasons are statistically non-significant. Overall the study area is under a significant warming trend with no changes in rainfall.
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| 2. |
- Arif, Usman
(författare)
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Effect of wounding and light exposure on sterol, glycoalkaloid, and calystegine levels in potato plants (Solanum tuberosum L. group Tuberosum)
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Steroidal glycoalkaloids (SGA) are neurotoxic substances that are present in some members of the Solanaceae family, including crop species like potato (Solanum tuberosum L.) and tomato. The SGA level in the potato tuber is a genetic trait, but certain environmental factors such as wounding and light exposure can increase SGA levels several-fold, which may render tubers unsuitable for human consumption. There is little information about SGA biosynthesis. The sterol cholesterol is commonly regarded as a SGA precursor, but there is little evidence for this view. To increase our understanding of the SGA biosynthesis and its molecular regulation, a microarray screen was performed using tubers from two potato cultivars subjected to wound and light treatments. Along with an alteration of sterol and SGA levels, the treatments were associated with an up-regulation of a small set of genes in sterol and SGA metabolism, including a gene encoding for the sterol reductase DWF1. DWF1 genes were found in two differentially regulated subtypes; DWF1 and DWF1-like (DWF1-L). Alteration of DWF1 and DWF1-L expression in transgenic potato showed a role for these genes in sterol and SGA synthesis. Also up-regulated in the microarray study were three transaminase-like genes, and role of StTAM1 in SGA synthesis was investigated by overexpression in transgenic potato. This resulted in elevated SGA levels, indicating the presence of a transamination in SGA synthesis. The genetic variation and stress responsiveness in Swedish potato cultivars regarding SGA and calystegine alkaloids (CA) level was determined by subjecting tubers to wounding, light exposure and elevated temperature. Only light and wounding increased SGA levels, and variation in the response was observed among the cultivars. CA levels were not stress-regulated, indicating that SGA and CA synthesis are not interrelated. These results show that the SGA level in potato tubers are regulated by a concerted action of a small set of key genes acting at different steps in the sterol and SGA pathways. Results also demonstrate a genetic variation in stress responsiveness among Swedish potato cultivars, and have identified the most sensitive ones. Results could in the near future be used to improve post-harvest handling of potato cultivars.
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| 3. |
- Just, Kadri, et al.
(författare)
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Infectivity of Tomato yellow leaf curl virus isolated from imported tomato fruit in Estonia
- 2017
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Ingår i: Žemdirbystė. - : LITHUANIAN RESEARCH CENTRE AGRICULTURE & FORESTRY. - 1392-3196 .- 2335-8947. ; 104:1, s. 47-52
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Tidskriftsartikel (refereegranskat)abstract
- There is a risk that Tomato yellow leaf curl virus (TYLCV) and its vector, whiteflies of the Bemisia tabaci species complex, will become established in greenhouses in temperate regions of the world, including northern Europe. In this study, TYLCV isolated from imported tomato fruit in Estonia (originating from Spain) was shown to be able to infect plants of tomato and Nicotiana benthamiana using Agrobacterium-mediated inoculation with an infectious clone as well as using biolistic delivery of products from rolling circle amplification (RCA). A 1.8-mer genomic construct of TYLCV was engineered and efficiently agroinfiltrated into plants of tomato and N. benthamiana, and induced symptoms characteristic of natural infection. With Agrobacterium-mediated inoculation, the infection efficiency was 100% for both tomato and N. benthamiana, whereas biolistic inoculation using RCA products resulted in efficiencies of 57% and 36%, respectively. Particle bombardment with monomeric linear genome failed to produce any infection in tomato or N. benthamiana. The genome of TYLCV amplified from tomato fruit was infectious confirming that tomato fruit may serve as a source of virus inoculum. This is the first report of agroinfiltration and particle bombardment assay using TYLCV DNA derived from infected tomato fruit tissue.
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| 4. |
- Just, Kadri, et al.
(författare)
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Monitoring infection of tomato fruit by Tomato yellow leaf curl virus
- 2016
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Ingår i: Plant Pathology. - : Blackwell Publishing. - 0032-0862 .- 1365-3059.
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Tidskriftsartikel (refereegranskat)abstract
- Fruit constitutes a strong sink organ and thus accumulates infecting viruses, but there is limited information about the infection process of viruses in fruit. Tomato yellow leaf curl virus (TYLCV, genus Begomovirus, family Geminiviridae) is one of the most important viruses affecting the production of tomato fruit. Using real-time quantitative PCR, TYLCV was shown to accumulate with increasing titres in early developing tomato fruit tissues from anthesis until 21 days post-anthesis. In situ hybridization demonstrated that TYLCV DNA and transcripts of the coat protein gene localized specifically to the phloem tissue of young fruit as well as sepals and petals. Embryos of developing seeds were also found to be infected. Expression of a host histone H4 gene was used as a marker for S-phase and the gene was also found to be expressed in phloem cells of young tomato fruit. The results indicate that TYLCV is transported to developing tomato fruit, where the virus titre gradually increases because of movement and probably also due to virus replication. In this study, the accumulation and localization of TYLCV in early developing tomato fruit are monitored for the first time.
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| 5. |
- Merino, Irene, et al.
(författare)
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Metabolomic and transcriptomic analyses identify external conditions and key genes underlying high levels of toxic glycoalkaloids in tubers of stress-sensitive potato cultivars
- 2023
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Ingår i: Frontiers in Plant Science. - 1664-462X. ; 14
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: High levels of toxic steroidal glycoalkaloids (SGAs) in potato tubers constitute a recognized food quality problem. Tuber SGA levels vary between potato cultivars and can increase after post-harvest stresses such as wounding and light exposure. A few cultivars, e.g., ‘Magnum Bonum’ and ‘Lenape,’ have been withdrawn from commercial sales due to excessive SGA levels during some cultivation years. However, these sudden SGA increases are diffucult to predict, and their causes are not understood. To identify external and genetic factors that underlie sudden SGA increases in certain potato cultivars, we have here in a 2-year study investigated ‘Magnum Bonum’ and five additional table potato cultivars for their SGA levels after wounding and light exposure. Results and methods: Results showed that ‘Magnum Bonum’ has an unusual strong SGA response to light exposure, but not to wounding, whereas ‘Bintje’ displayed an opposite regulation. Levels of calystegine alkaloids were not significantly altered by treatments, implicating independent metabolic regulation of SGA and calystegine levels also under conditions of high SGA accumulation. Metabolomic and transcriptomic analyses identified a small number of key genes whose expression correlated with SGA differences between cultivars. Overexpression of two key genes in transgenic low-SGA potato cultivars increased their leaf SGA levels significantly. Discussion: The results show that a strong response to light can underlie the SGA peaks that occasionally occur in certain potato cultivars and indicate that a between-cultivar variation in the expression of single SGA key genes can account for cultivar SGA differerences. We propose that current attempts to mitigate the SGA hazard will benefit from an increased consideration of cultivar-dependent SGA responses to post-harvest conditions, particularly light exposure. The identified key SGA genes can now be used as a molecular tool in this work.
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| 6. |
- Nahar, Nurun, et al.
(författare)
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Transcript profiling of two potato cultivars during glycoalkaloid-inducing treatments shows differential expression of genes in sterol and glycoalkaloid metabolism
- 2017
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Steroidal glycoalkaloids (SGA) are sterol-derived neurotoxic defence substances present in several members of the Solanaceae. In the potato (Solanum tuberosum), high SGA levels may render tubers harmful for consumption. Tuber SGA levels depend on genetic factors, and can increase as a response to certain stresses and environmental conditions. To identify genes underlying the cultivar variation in tuber SGA levels, we investigated two potato cultivars differing in their SGA accumulation during wounding or light exposure; two known SGA-inducing treatments. Using microarray analysis coupled to sterol and SGA quantifications, we identified a small number of differentially expressed genes that were associated with increased SGA levels. Two of these genes, encoding distinct types of sterol Delta(24)-reductases, were by sense/antisense expression in transgenic potato plants shown to have differing roles in sterol and SGA metabolism. The results show that an increased SGA level in potato tubers during both wounding and light exposure is mediated by coordinated expression of a set of key genes in isoprenoid and steroid metabolism, and suggest that differences in this expression underlie cultivar variations in SGA levels. These results may find use within potato breeding and quality assessment.
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| 7. |
- Petersson, Erik, et al.
(författare)
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Glycoalkaloid and Calystegine Levels in Table Potato Cultivars Subjected to Wounding, Light, and Heat Treatments
- 2013
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Ingår i: Journal of Agricultural and Food Chemistry. - : American Chemical Society (ACS). - 0021-8561 .- 1520-5118. ; 61:24, s. 5893-5902
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Tidskriftsartikel (refereegranskat)abstract
- Potato tubers naturally contain a number of defense substances, some of which are of major concern for food safety. Among these substances are the glycoalkaloids and calystegines. We have here analyzed levels of glycoalkaloids (alpha-chaconine and a-solanine) and calystegines (A(3), B-2, and B-4) in potato tubers subjected to mechanical wounding, light exposure, or elevated temperature: stress treatments that are known or anticipated to induce glycoalkaloid levels. Basal glycoalkaloid levels in tubers varied between potato cultivars. Wounding and light exposure, but not heat, increased tuber glycoalkaloid levels, and the relative response differed among the cultivars. Also, calystegine levels varied between cultivars, with calystegine B-4 showing the most marked variation. However, the total calystegine level was not affected by wounding or light exposure. The results demonstrate a strong variation among potato cultivars with regard to postharvest glycoalkaloid increases, and they suggest that the biosynthesis of glycoalkaloids and calystegines occurs independently of each other.
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| 8. |
- Saad, Ali, et al.
(författare)
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Bearing Fault Detection Scheme Using Machine Learning for Condition Monitoring Applications
- 2023
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Ingår i: Proceedings of the International Conference on Mechanical, Automotive and Mechatronics Engineering (ICMAME 2023). - : ICMAME. - 9786250015261
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Bearings are the significant components among the rolling machine elements subjected to high wear and tear. The timely detection of faults in such components rotating at higher frequencies can save substantial maintenance costs and production setbacks. Physical examination and fault detection by human experts is always challenging at runtime. Predictive maintenance and real-time condition monitoring are gaining higher utility with the advent of suitable instrumentation and machine learning classifiers. A convolutional neural network (CNN) based bearing fault detection scheme is developed in this research work. The acquired sensory data of vibration signals are converted into the frequency domain and then fed to the classifier for spectral feature extraction and fault classification. The CNN architecture is trained and tested using a bearing dataset available online. The model is further tested and validated with the data acquired from an indigenously designed bearing test rig. The proposed scheme has successfully detected inner and outer race faults and no fault or normal state. This multiclass fault classification has shown promising results with 97.68% accuracy, 96.9% precision, 99.14% sensitivity, 98.01% F1-score, and 93.65% specificity. The achieved results validate the utility of the proposed detection system. Hence the presented scheme has deployment potential for real-time condition monitoring and predictive maintenance applications.
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| 9. |
- Usman, Ali, et al.
(författare)
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Machine Learning Composite-Nanoparticle-Enriched Lubricant Oil Development for Improved Frictional Performance—An Experiment
- 2023
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Ingår i: Lubricants. - : MDPI. - 2075-4442. ; 11:6
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Tidskriftsartikel (refereegranskat)abstract
- Improving the frictional response of a functional surface interface has been a significant research concern. During the last couple of decades, lubricant oils have been enriched with several additives to obtain formulations that can meet the requirements of different lubricating regimes from boundary to full-film hydrodynamic lubrication. The possibility to improve the tribological performance of lubricating oils using various types of nanoparticles has been investigated. In this study, we proposed a data-driven approach that utilizes machine learning (ML) techniques to optimize the composition of a hybrid oil by adding ceramic and carbon-based nanoparticles in varying concentrations to the base oil. Supervised-learning-based regression methods including support vector machines, random forest trees, and artificial neural network (ANN) models are developed to capture the inherent non-linear behavior of the nano lubricants. The ANN hyperparameters were fine-tuned with Bayesian optimization. The regression performance is evaluated with multiple assessment metrics such as the root mean square error (RMSE), mean squared error (MSE), mean absolute error (MAE), and coefficient of determination (R2). The ANN showed the best prediction performance among all ML models, with 2.22 × 10−3 RMSE, 4.92 × 10−6 MSE, 2.1 × 10−3 MAE, and 0.99 R2. The computational models’ performance curves for the different nanoparticles and how the composition affects the interface were investigated. The results show that the composition of the optimized hybrid oil was highly dependent on the lubrication regime and that the coefficient of friction was significantly reduced when optimal concentrations of ceramic and carbon-based nanoparticles are added to the base oil. The proposed research work has potential applications in designing hybrid nano lubricants to achieve optimized tribological performance in changing lubrication regimes.
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