Investigation formaize inbred lines resistance to <Emphasis Type="Italic">Maize Rough Dwarf Virus</Emphasis>(MRDV)

Maize rough dwarf virus (MRDV) is the most important disease affecting maize growth in Iran. In the present study, the putative resistance capacity of 35 maize inbred lines against the causal agents of MRDVwas studied under natural field infection in 2010 and 2011. The viral transmitter was a plant hopper known as Laodelphax steriatellus. Early sowing provided suitable temperatures for vector propagation and transmission and therefore natural infection under field conditions. Sowing single rows of SC704 as vector spreader between every five rows of inbred lines caused adequate vector propagation and viral transmission. This shows that viral infection was sufficient and possible resistance was linked to viral resistance, not failure, in vector transmission. In principal component biplot, plant height vector had wide angles with the vectors for disease severity index and MRDV incidence that showed the negative association of plant height with MRDV disease. The percentage of natural infection to MRDV in susceptible control(SC704) was about 64%. The genotypes A679, K3547/3, K3545/6, K3653/2, and B84 were more susceptible to MRDV. Only the line K3640/3 had low disease incidence and severity and it can be considered as resistant for possible use in genetic studies. Results showed that an early sowing of maize in temperate regions increases the chance of transmitting viruses via their vector.     

Predicting performance of broiler chickens from dietary nutrients using group method of data handling-type neural networks

1. Successful artificial neural network (ANN) applications have been found for many areas. One sub-model of ANNs is the group method of data handling-type neural networks (GMDH-type NNs). The use of self-organising networks leads to successful application in a broad range of areas. However, the use of such methods is not common in poultry science. 2. Broiler chicken nutrition is recognised as a biological system consisting of a complex set of interconnected variables. The adequate information on nutrients (variables), such as metabolisable energy (ME) and amino acid requirements, can help to establish specific feeding programmes, defining optimal performance and reducing production costs. 3. This study addressed the question of whether GMDH-type NNs can be used to estimate the performance of broiler chickens (output) based on specified variables-inputs (dietary crude protein (CP), ME, ME/CP, methionine (Met), lysine (Lys), ME/Met and ME/Lys)-for a commercial broiler chicken farm. The recorded data from 10 broiler chicken flocks were obtained, from March 2003 to April 2005, corresponding to 52 data lines. 4. The results suggested that the GMDH-type NNs may provide an effective means of recognising the patterns in data and accurately predicting the performance of broiler chickens based on investigating inputs. In addition the polynomial equations obtained can be used to optimise the performance of broilers.     

Associations of prepartum body condition score with occurrence of clinical endometritis and resumption of postpartum ovarian activity in dairy cattle

This study was performed to investigate the effect of periparturient body condition score on the occurrence of clinical endometritis and postpartum resumption of ovarian activity in dairy cows. Eighty-seven lactating Holstein cows, fed with a total mixed ration diet, were included into the study. Body condition scoring (using a 5-point scale with quarter-point divisions) was performed by the same investigator using the visual technique every 2 weeks, from 2 weeks before until 6 weeks after calving. Palpation of the reproductive tract and ultrasonographic assessment of ovaries for detection of corpus luteum using a rectal linear probe was also performed at 2, 4, and 6 weeks after calving. Cows with clinical endometritis had significantly lower body condition score (BCS) than normal cows at all weeks pre- and postcalving, and cows that did not ovulate until 45 days after calving had a significantly lower BCS pre- and postpartum. Cows that did not ovulate until 45 days after calving also lost more BCS from 2 weeks before to 4 weeks after calving. Besides, first ovulation after calving take occurred later in cows with clinical endometritis compared to normal cows (P?<?0.05). In conclusion, low BCS is a risk factor for postpartum endometritis and delayed cyclicity in dairy cows. BCS loss from dry-off to early lactation and occurrence of clinical endometritis can significantly affect postpartum ovarian activity.     

Comparison of Different Methods of Estimating Saffron Yield Based on Soil Properties in Golestan Province

ABSTRACT

Evaluation of the relationship between soil properties and saffron yield estimation may contribute to agricultural planning in finding suitable lands for the growth of this valuable product. This study aimed to investigate the performance of artificial neural network (ANN), multiple linear regression (MLR), and adaptive neuro-fuzzy inference system (ANFIS) in terms of saffron yield estimation in some lands of Golestan province, Iran. To this end, 100 areas under saffron cultivation were selected. For rapid and low-cost saffron yield estimation, six different models were designed based on soil properties as inputs using MLR, ANN, and ANFIS methods. According to the results, ANN showed the highest accuracy (R² = 0.58–0.89) in estimating saffron yield as compared to MLR (R² = 0.41–0.47) and ANFIS (R² = 0.41–0.69) models. A comparison of the results obtained from the six models defined in these three methods indicated that Model 4 (R² _Reg = 0.45, R² _ANFIS = 0.57, R² _ANN = 0.87), with the inputs, organic phosphorus, potassium, and calcium carbonate, was the best model in terms of accuracy and speed in estimating saffron yield phosphorus. The RI indexes for ANN in the model were 50% and 34% relative to MLR and ANFIS, respectively, demonstrating the higher accuracy of ANN in saffron yield estimation. The study results can be used to identify lands suitable for saffron cultivation in the study area using organic phosphorus and organic matter levels in the soil.     

Drought tolerance variability in S<Subscript>1</Subscript> pollinator lines developed from a sugar beet open population

Drought tolerance is one of the most important objectives of sugar beet breeding programs in semi-arid regions, particularly during the last decade. Due to global climate changes and limitations of agricultural irrigation water, varieties with drought tolerance are taken into consideration in order to avoid yield losses due to drought. In this study, drought tolerance of 76 S₁ lines (full-sib families) that had been extracted from a genetically broad base multigerm sugar beet open pollinated population, were examined. Test crosses were made between the lines as pollinators and a cytoplasmic male sterile (CMS) single cross. The consequent hybrids along with checks were evaluated during 2007 and 23 more tolerant hybrids during 2008, in two adjacent experiments under drought stress and non-stress conditions. Drought tolerance indices calculated based on sugar yield, such as mean productivity (MP), geometric mean productivity (GMP) and stress tolerance index (STI) were used to assess hybrids responses to drought. The results showed significant genetic differences for root yield and sugar yield under both conditions. Drought tolerance indices displayed significant genetic variability for sugar yield among the hybrids. Many hybrids were drought tolerant as compared with the original base population as indicated by their high STI. The estimates of heritability for sugar yield in stress and non-stress conditions were much close to each other (0.31 and 0.34, respectively). Whereas, for root yield the heritability estimate in stress condition (0.46) was relatively higher than that in non-stress condition (0.34). Significant differences were observed among the selected hybrids for root yield and sugar yield, indicating genotypic variability for pollinator lines derived from the population. There were no significant differences for sugar content. For increasing the drought tolerance potential in a breeding population and developing drought-tolerant varieties by male parent, the drought-tolerant lines could be used.     

Enriched Artemia with L-lysine and DL-methionine on growth performance,stress resistance,and fatty acid profile of Litopenaeus vannamei postlarvae

A 15-day study was conducted to evaluate the effect of enrichment of Artemia metanauplii with four different emulsions, including: (A) Easy-DHA Selco; (B) Easy-DHA Selco + L-lysine (4 g/L); (C) Easy-DHA Selco + DL-methionine (4 g/L); and (D) Easy-DHA Selco + L-lysine (2 g/L) + DL-methionine (2 g/L) on growth and stress resistance of white leg shrimp Litopenaeus vannamei larvae (from Mysis I to postlarvae12). It is noticed that shrimp PL in group B had the highest wet (36.1 ± 3.1 mg) and dry (1116.7 ± 60.0 µg) weights as well as stress resistance to fresh water (64.0 ± 5.5%).     

Screening wheat germplasm for seedling root architectural traits under contrasting water regimes: potential sources of variability for drought adaptation

In this study, we selected 180 accessions from different wild relatives of wheat (Aegilops–Triticum species) and tested them in the presence of a tolerant and a sensitive control variety under well-watered and drought-stressed conditions. The results of analysis of variance for dry masses and all measured root traits showed that water regimes, accession and species main effects were highly significant. Drought stress significantly declined shoot dry mass (59.42%), root length (37.85%) and the total number of branch roots (36.25%), but increased the root-to-shoot ratio (75.00%), specific root length (64.19%) and root tissue density (29.46%). Principal component analysis for 182 individuals and 12 species groups identified two components that explained 75.67 and 82.39% of the total variation in dry mass and root traits under drought-stressed conditions, respectively. Taking together, our results identified 12 accessions with superior tolerance to drought stress. Remarkably, four species of wild relatives – Ae. cylindrica (DC genome), Ae. neglecta (UM genome), Ae. speltoides (B genome) and Ae. tauschii (D genome) – responded well to drought stress. The potential of these species could be used for molecular analysis such as marker assisted selection and gene mapping, ultimately aimed at breeding for root traits with improved adaptation to drought environments.     

Moisture Content and Oil Uptake in Potatoes (Cultivar Satina) During Deep-Fat Frying

In this study, the effect of ultrasonic sound (at 20- and 40-kHz frequency for 15 min) and drying (at 60 °C for 15 min) pretreatments on the moisture content and oil uptake of potato slices (cultivar Satina) during deep frying were studied. The potato slices were fried at temperatures of 170 and 190 °C for 5, 7 and 10 min. Samples pretreated with ultrasound at 20 kHz had higher moisture contents than those receiving the 40-kHz pretreatment. The highest moisture content was obtained at 20 kHz and frying at 170 °C for 5 min. On the other hand, samples pretreated with ultrasound at 40 kHz had higher effective water diffusivity coefficient and activation energy than those pretreated at 20 kHz. The highest effective water diffusivity coefficient was obtained at 40 kHz and frying at 190 °C for 5 min, whereas the highest activation energy belonged to pretreatment with 40 kHz and frying at 170 °C for 10 min. The range for effective water diffusivity coefficient was 6.95?×?10^?8 to 8.80?×?10^?8 m² s^?1 and that for activation energy was 13.161 to 16.307 kJ mol^?1. In addition, samples pretreated at 40 kHz had a lower oil uptake than those pretreated at 20 kHz. The highest oil uptake took place at 20 kHz, with frying at 170 °C for 10 min. Regression analysis revealed that an exponential model was best for predicting variations in moisture content and oil uptake of potato slices.