Molecular identification of bacterial and fungal pathogens in certain disease-free shrimp

At present, the aquaculture industry to provide proper instructions in the field of health management, including production of Specific Pathogen Free shrimp (SPF), require sensitive and reliable methods for the detection and identification of pathogenic microorganisms. Molecular methods which used in the detection of microorganisms have a high discriminatory power in the taxonomy and in relation to libraries in the world. On the other hand, the accurate identification of microorganisms, providing the genetic data bank of shrimp pathogens and maintenance of these strains is the step to promote further research on the mechanisms of pathogenesis of pathogens, diagnosis, treatment, prevention of disease, identify indigenous production kits, diagnosis re emerging and emerging diseases and their origin. Therefore, in this project, by using ribotyping technique, native isolated pathogenic bacteria and fungi were identified and recorded in the gene bank database center. During sampling of shrimp and water of Specific Pathogen Free shrimp center, 40 bacterial strains were isolated, which 8 of them had the most frequency and identification based on 16S rDNA sequencing was performed. Bacteria identified are: Vibrio nigripulchritudo strain IS013(GenBank:KP843725), Vibrio brasiliensis strain IS014 (GenBank:KR186076), Vibrio rotiferianus strain IS015 (GenBank:KR186077), Vibrio azureus strain IS012 (GenBank:KJ018724.1), Vibrio owensii strain IS016 (GenBank:KR186078), Agarivorans gilvus strain IS017 (GenBank:KR186079), Vibrio brasiliensis IS018 (GenBank:KR186080) and Vibrio alginolyticus strain IS019 (GenBank:1817854), which were recorded in The World Bank genes. In this study fungal isolates were not detected

How fast do gully headcuts retreat?

© 2016 Elsevier B.V. Gully erosion has important on and off site effects. Therefore, several studies have been conducted over the past decades to quantify gully headcut retreat (GHR) in different environments. Although these led to important site-specific and regional insights, the overall importance of this erosion process or the factors that control it at a global scale remain poorly understood. This study aims to bridge this gap by reviewing research on GHR and conducting a meta-analysis of measured GHR rates worldwide. Through an extensive literature review, GHR rates for 933 individual and actively retreating gullies have been compiled from more than 70 study areas worldwide (comprising a total measuring period of >19 600 years). Each GHR rate was measured through repeated field surveys and/or analyses of aerial photographs over a period of at least one year (maximum: 97 years, median: 17 years). The data show a very large variability, both in terms of gully dimensions (cross-sectional areas ranging between 0.11 and 816 m2 with a median of 4 m2) and volumetric GHR rates (ranging between 0.002 and 47 430 m3 year- 1 with a median of 2.2 m3 year- 1). Linear GHR rates vary between 0.01 and 135 m year- 1 (median: 0.89 m year- 1), while areal GHR rates vary between 0.01 and 3628 m2 year- 1 (median: 3.12 m2 year- 1). An empirical relationship allows estimating volumetric retreat rates from areal retreat rates with acceptable uncertainties. By means of statistical analyses for a subset of 724 gullies with a known contributing area, we explored the factors most relevant in explaining the observed 7 orders of magnitudes of variation in volumetric GHR rates. Results show that measured GHR rates are significantly correlated to the runoff contributing area of the gully (r2 = 0.15) and the rainy day normal (RDN; i.e. the long-term average annual rainfall depth divided by the average number of rainy days; r2 = 0.47). Other factors (e.g. land use or soil type) showed no significant correlation with the observed GHR rates. This may be attributed to the uncertainties associated with accurately quantifying these factors. In addition, available time series data demonstrate that GHR rates are subject to very large year-to-year variations. As a result, average GHR rates measured over short (100%) uncertainties. We integrated our findings into a weighted regression model that simulates the volumetric retreat rate of a gully headcut as a function of upstream drainage area and RDN. When weighing each GHR observation proportional to its measuring period, this model explains 68% of the observed variance in GHR rates at a global scale. For 76% of the monitored gullies, the simulated GHR values deviate less than one order of magnitude from their corresponding observed value. Our model clearly indicates that GHR rates are very sensitive to rainfall intensity. Since these intensities are expected to increase in most areas as a result of climate change, our results suggest that gully erosion worldwide will become more intense and widespread in the following decades. Finally, we discuss research topics that will help to address these challenges

Development of novel green pesticide system by using cold plasma to control Plodia interpunctella in pistachio

Iran is the most important exporter of pistachios in the world. One of pistachio export challenges is the damage of pistachio by warehouse pests. Many efforts have been made to discover alternative methods of nontoxic pest control. To study the effect of the cold plasma jet on Plodia interpunctella of pistachio nut, three treatment variables were used by argon/air ratio, the plasma exposure time, and the power supply voltage. The results showed that increasing the power supply voltage has the greatest effect on the increased mortality of P. interpunctella compared to other variables. Also, the effect of the equal combination of air and argon gases was much higher than the effect of each alone. According to the optimal points obtained in mortality of P. interpunctella, plasma exposure time of 14.04 min, the voltage of 19.99 kV, and argon/air ratio of 51.65 cause the greatest increased mortality of P. interpunctella. Novelty impact statement: Cold plasma can remove and control Plodia interpunctella. This method can be used as an alternative method to replace Conventional methods of pest control. Plasma exposure time of 14.04 min, the voltage of 19.99 kV, and argon/air ratio of 51.65 cause the greatest increased mortality of Plodia interpunctella. © 2021 Wiley Periodicals LLC

Land Subsidence Susceptibility Mapping Using Interferometric Synthetic Aperture Radar (InSAR) and Machine Learning Models in a Semiarid Region of Iran

Most published studies identify groundwater extraction as the leading cause of land subsidence (LS). However, the causes of LS are not only attributable to groundwater extraction. Other land-use practices can also affect the occurrence of LS. In this study, radar interferometric techniques and machine learning (ML) models were used for the prediction, susceptibility zoning, and prioritization of influential variables in the occurrence of LS in the Bakhtegan basin. The LS rate was characterized by applying an interferometric synthetic aperture radar (InSAR). The recursive feature elimination (RFE) method was used to detect and select the dominant combination of indicators to prepare an LS susceptibility map. Three ML models, including random forest (RF), k-nearest neighbors (KNN), and classification and regression trees (CART), were used to develop predictive models. All three models had acceptable performance. Among the ML models, the RF model performed the best (i.e., Nash–Sutcliffe efficiency, Kling–Gupta efficiency, correlation coefficient, and percent bias metrics of 0.76, 0.78, 0.88, and 0.70 for validating phase, respectively). The analysis conducted on all three ML model outputs showed that high and very high LS susceptibility classes were located on or near irrigated agricultural land. The results indicate that the leading cause of land LS in the study region is not due to groundwater withdrawals. Instead, the distance from dams and the proximity to anticlines, faults, and mines are the most important identifiers of LS susceptibility. Additionally, the highest probability of LS susceptibility was found at distances less than 18 km from synclines, 6 to 13 km from anticlines, 23 km from dams, and distances less than 20 to more than 144 km from mines. The validated methods presented in this study are reproducible, transferrable, and recommended for mapping LS susceptibility in semiarid and arid climate zones with similar environmental conditions

How fast do gully headcuts retreat?

Gullies can be a dominant sediment source at field and catchment scales. Over the past decades, several studies have been conducted that quantify gully headcut retreat (GHR) in different environments. Although this led to important site-specific and regional insights, the overall importance of this erosion process or the factors that control it at a global scale remain poorly understood. This study aims to bridge this gap by conducting a meta-analysis of measured GHR rates worldwide. Through an extensive literature review, GHR rates for ca. 900 individual actively retreating gullies (comprising a total measuring period of > 19 000 years) from more than 50 study areas worldwide have been compiled. Each GHR rate was measured by means of repeated field surveys and/or analyses of aerial photographs over a period of at least one year. The collected data shows a very large variability, both in terms of gully dimensions (cross-sectional areas ranging between 0.11 and 816 m2 with a median of 4 m2) and GHR rates (ranging between 0.003 and 47 000 m3/y with a median of 2.2 m3/y). Linear GHR rates vary between 0.01 and 70 m/y (median: 0.82 m/y). By means of statistical analyses for a subset of 689 gullies with a known contributing area, we explored which factors are most relevant in explaining the observed 6 orders of magnitudes of variation in volumetric GHR rates. Results show that measured GHR rates are significantly correlated to the runoff contributing area of the gully (r2 = 0.13) and the average rainfall depth on a rainy day (i.e. the long-term average annual rainfall depth divided by the average number of rainy days; r2 = 0.39). Combined, these two factors explained 57% of the observed variability in average GHR rates. Other factors (e.g. land use or soil type) showed no significant correlation with the observed GHR rates. This may be attributed to the uncertainties associated with accurately quantifying these factors. In addition, a large part of the remaining unexplained variance may be due to measuring periods that are too short to fully capture the large temporal variability that are typical for GHR rates. This is illustrated by the fact that catchment area and average rainfall depth on a rainy day explain nearly 70% of the observed variation in GHR rates for gullies monitored over a periodpublisher: Elsevier articletitle: How fast do gully headcuts retreat? journaltitle: Earth-Science Reviews articlelink: http://dx.doi.org/10.1016/j.earscirev.2016.01.009 content_type: article copyright: Copyright © 2016 Elsevier B.V. All rights reserved.status: publishe