Earthworms as ecosystem engineers and the most important detritivors in forest soils

Earthworms are considered as soil engineers because of their effects on soil properties and their influence on the availability of resources for other organisms, including microorganisms and plants. However, the links between their impacts on the soil environment and the resulting modification of natural selection pressures on engineer as well as on other organisms have received little attention. Earthworms are known to have a positive influence on the soil fabric and on the decomposition and mineralization of litter by breaking down organic matter and producing large amounts of fasces, thereby mixing litter with the mineral soil. Therefore, they play an important part in changes from one humus from to another according to forest succession patterns. Consequently, they are also expected to be good bio-indicators for forest site quality and are thus useful when planning forest production improvement. Earthworm's populations are as indicator that in exploited regions is destruction indicator and reclamation plans is nature return indicator. In this study we summarized the current knowledge in relation to earthworm's ecology in forest soils as ecosystem engineers.     

Dysregulated Expression of Long Non-Coding RNA MINCR and EZH2 in Colorectal Cancer

Background:As critical regulators, lncRNAs have attracted attention from researchers for diagnostic, prognostic, and therapeutic purposes in human carcinogenesis via interfering with mRNAs such as EZH2. Nevertheless, the potent roles and molecular mechanisms of these RNAs in CRC are not clearly known. Methods:In this study, the tissue expressions of lncRNA MINCR and EZH2 mRNA between colorectal tumors and polyps were compared with the adjacent normal tissues collected from 114 Iranian patients, using real-time PCR method. Furthermore, the correlation of the expression levels of MINCR and EZH2 with other clinical parameters was evaluated. Results:The significant overexpression of MINCR and EZH2 were observed in the CRC tissues compared to control tissues (p < 0.0001). This observation confirmed the association of these expression enhancements with the pathological stage of CRC patients. Conclusion:Our findings revealed that the expression of MINCR significantly alters during CRC development, and it can be identified as a potential biomarker for the detection of CRC.Key Words: Colorectal cancer, EZH2, Long non-coding RNA     

Effect of drought stress on root yield and some morpho-physiological traits in different genotypes of sugar beet (<Emphasis Type="Italic">Beta vulgaris</Emphasis> L.)

To study the effects of different levels of drought stress on root yield and some morpho-physiological traits of sugar beet genotypes, a study was conducted in the research farm of Islamic Azad University of Birjand, Iran in 2013 as strip-split plot experiments based on randomized complete block design. Different levels of drought stress were considered as vertical factor in three levels including normal irrigation, moderate stress, and severe stress. Horizontal factor was assigned to five varieties of sugar beet. Drought stress had a significant effect on root dry weight, total dry weight, root yield, and leaf temperature at 1% probability level and on leaf dry weight, crown dry weight, and harvest index at 5% probability level. Drought stress had an adverse effect on root yield of investigated genotypes of sugar beet. Under normal conditions, the mean of root yield was higher than middle and severe drought stress. Different investigated genotypes of sugar beet responded to drought stress based on their yield potential. The highest positive correlation of root yield was observed with root dry weight (r=0.977**). Stepwise regression analysis and path coefficient analysis showed that root dry weight and petiole dry weight are the most important traits that can affect root yield of sugar beet under drought stress and can used as selection criteria in investigated cultivars of sugar beet. Finally, 7221 genotypes can be considered as tolerant genotypes in the next studies. In comparison, Jolgeh cultivar (as susceptible control) yielded well in areas with normal irrigation, but under moderate and severely stresses its root yield was reduced.     

Potassium Fixation and Release in Some Calcareous Soils under Orange Cultivation

Eurasian Soil Science - Arid and semiarid soils of southern Iran may fix a large content of applied potassium (K), but the fixed K may be gradually supplied to plants. Sixteen representative soils...     

Schistosoma bovis whole egg antigen did not protect Zebu calves against experimental schistosomosis

Six calves were immunized with whole egg antigen of Schistosoma bovis emulsified in Freund's adjuvant. The immune response was monitored by agar-gel immunodiffusion (AGID) and enzyme-linked immunosorbent assay (ELISA). Using AGID and ELISA, antibodies to whole egg antigen were detected in sera from all immunized calves, but not in sera from control calves. The immunized calves and six control calves were challenged 6 months after the beginning of the immunization with 20 000 cercariae of Schistosoma bovis administered percutaneously to the shaved tail. There was no significant difference between the immunized and the control calves as judged by fecal and tissue egg counts, worm recovery and hematological parameters. There was a lack of association between antibody production and protection.     

Cytokine gene expression in chicken cecal tonsils following treatment with probiotics and Salmonella infection

Probiotics are currently employed for control of pathogens and enhancement of immune response in chickens. In this study, we investigated the underlying immunological mechanisms of the action of probiotics against colonization of the chicken intestine by Salmonella enterica subsp. enterica serovar Typhimurium (Salmonella serovar Typhimurium). Birds received probiotics by oral gavage on day 1 of age and, subsequently, received Salmonella serovar Typhimurium on day 2 of age. Cecal tonsils were removed on days 1, 3 and 5 post-infection (p.i.), RNA was extracted and subjected to real-time quantitative RT-PCR for measurement of interleukin (IL)-6, IL-10, IL-12 and interferon (IFN)-gamma gene expression. There was no significant difference in IL-6 and IL-10 gene expression in cecal tonsils of chickens belonging to various treatment groups. Salmonella serovar Typhimurium infection resulted in a significant increase in IL-12 expression in cecal tonsils on days 1 and 5p.i. However, when chickens were treated with probiotics prior to experimental infection with Salmonella, the level of IL-12 expression was similar to that observed in uninfected control chickens. Treatment of birds with probiotics resulted in a significant decrease in IFN-gamma gene expression in cecal tonsils of chickens infected with Salmonella compared to the Salmonella-infected birds not treated with probiotics. These findings reveal that repression of IL-12 and IFN-gamma expression is associated with probiotic-mediated reduction in intestinal colonization with Salmonella serovar Typhimurium.     

Detection and analysis of wheat spikes using Convolutional Neural Networks

Background

Field phenotyping by remote sensing has received increased interest in recent years with the possibility of achieving high-throughput analysis of crop fields. Along with the various technological developments, the application of machine learning methods for image analysis has enhanced the potential for quantitative assessment of a multitude of crop traits. For wheat breeding purposes, assessing the production of wheat spikes, as the grain-bearing organ, is a useful proxy measure of grain production. Thus, being able to detect and characterize spikes from images of wheat fields is an essential component in a wheat breeding pipeline for the selection of high yielding varieties.

Results

We have applied a deep learning approach to accurately detect, count and analyze wheat spikes for yield estimation. We have tested the approach on a set of images of wheat field trial comprising 10 varieties subjected to three fertilizer treatments. The images have been captured over one season, using high definition RGB cameras mounted on a land-based imaging platform, and viewing the wheat plots from an oblique angle. A subset of in-field images has been accurately labeled by manually annotating all the spike regions. This annotated dataset, called SPIKE, is then used to train four region-based Convolutional Neural Networks (R-CNN) which take, as input, images of wheat plots, and accurately detect and count spike regions in each plot. The CNNs also output the spike density and a classification probability for each plot. Using the same R-CNN architecture, four different models were generated based on four different datasets of training and testing images captured at various growth stages. Despite the challenging field imaging conditions, e.g., variable illumination conditions, high spike occlusion, and complex background, the four R-CNN models achieve an average detection accuracy ranging from 88 to \(94\%\) across different sets of test images. The most robust R-CNN model, which achieved the highest accuracy, is then selected to study the variation in spike production over 10 wheat varieties and three treatments. The SPIKE dataset and the trained CNN are the main contributions of this paper.

Conclusion

With the availability of good training datasets such us the SPIKE dataset proposed in this article, deep learning techniques can achieve high accuracy in detecting and counting spikes from complex wheat field images. The proposed robust R-CNN model, which has been trained on spike images captured during different growth stages, is optimized for application to a wider variety of field scenarios. It accurately quantifies the differences in yield produced by the 10 varieties we have studied, and their respective responses to fertilizer treatment. We have also observed that the other R-CNN models exhibit more specialized performances. The data set and the R-CNN model, which we make publicly available, have the potential to greatly benefit plant breeders by facilitating the high throughput selection of high yielding varieties.

     

The comparison of the effectiveness of a modified conformation sensitive gel electrophoresis with denaturing high performance liquid chromatography

Background: Several methods have been developed for detection of sequence variation in genes and each has its advantages and disadvantages. A disadvantage of them is that the simpler, cost-effective methods are commonly perceived as being less sensitive in their detection of sequence variation, whereas those with proven sensitivity have a requirement for complex or expensive laboratory equipment. In this context, we undertook improvements to the conformation sensitive gel electrophoresis (CSGE) method which provides a cost-effective approach to mutation detection and compared the results with scanning carried out using denaturing high performance liquid chromatography (DHPLC) which utilises a dedicated analyser. Methods: We designed PCR primers to amplify the seven protein-coding exons of the human SPP2 gene which encodes secreted phosphoprotein 24 (spp24) such that the amplified products included the immediately-adjacent intronic regions. Five improvements were made to the CSGE method that was used to the scan the PCR-amplified DNA. The scanning was then repeated using DHPLC and the results were compared. Results: Using CSGE, a single nucleotide polymorphism was discovered in exon 2 and another in intron 2 of the gene. Re-scanning of the same regions by DHPLC detected no additional sequence polymorphisms. Conclusion: With modification of the original protocol, CSGE is capable of providing a simple and cost-effective approach to the detection of DNA sequence polymorphisms that appears to be comparable in sensitivity to DHPLC.     

Physical soil properties and slope treatments effects on hydraulic excavator productivity for forest road construction

Effects of moisture, porosity and soil bulk density properties, grubbing time and terrain side slopes on pc 220 komatsu hydraulic excavator productivity were investigated in Miana forests road construction project which located in the northern forest of Iran. Soil moisture and porosity determined by samples were taken from undisturbed soil. The elements of daily works were measured with a digital stop watch and video camera in 14 observations (days). The road length and cross section profiles after each 20 m were selected to estimate earthworks volume. Results showed that the mean production rates for the pc 220 komatsu excavators were 60.13 m3 h(-1) and earthwork 14.76 m h(-1) when the mean depth of excavation or cutting was 4.27 m3 m(-1), respectively. There was no significant effects (p = 0.5288) from the slope classes' treatments on productivity, whereas grubbing time, soil moisture, bulk density and porosity had significantly affected on excavator earthworks volume (p < 0.0001). Clear difference was showed between the earthwork length by slope classes (p = 0.0060). Grubbing time (p = 0.2180), soil moisture (p = 0.1622), bulk density (p = 0.2490) and porosity (p = 0.2159) had no significant effect on the excavator earthworks length.     

Effects of monensin and increasing crude protein in early lactation on performance of dairy cows

Twenty-four Holstein dairy cows were used to evaluate the singular and combined effects of different level of crude protein and monensin treatments during the early lactation on digestion and milk yield of dairy cows. The experiment was designed as completely randomized with a 3x2 factorial arrangement of treatments. The factors were three Concentrations of CP supplement (19.5, 21.4 and 23.4% of dry matter) and two levels of monensin (0 and 350 mg per cow per day). This experiment consist of three periods and each period was 3 week in length. Monensin did not affect DMI, milk yield, lactose and SNF but it reduced milk fat and protein percentage. Monensin premix significantly decreased rumen ammonia but rumen pH and microbial protein synthesis was not affected by monensin treatment. Although, Monensin treatment increased apparent digestibility of DM, NDF, ADF, CP, but they were not significantly. Increasing dietary CP, improved milk and protein production, but did not alter the other components of milk. Digestibility of NDF, ADF, CP were improved by increasing dietary CP. Increasing diet CP from 19.5 to 21.4% did not significantly increase ruminal ammonia, but increasing to 23.4% have significant effect on it. There was a linear relationship between level of crud protein in the diet and urine volume excretion. Microbial protein synthesis was affected by increasing CP level; on this way maximum protein synthesis was achieved in 21.4% CP.