Comparison of different classical and molecular methods to identify superior self-compatible almond (Prunus dulcis Mill.) genotypes and evaluation of their traits

Almond [Prunus amygdalus Batsch syn. Prunus dulcis (Mill.) D.A.Webb] trees are either self- or cross-incompatible, which results in lower fruit set and yields. Flower bagging, fluorescence microscopy, and polymerase chain reaction (PCR) were used to discriminate between self-compatible genotypes obtained from crosses of the self-incompatible female parents (‘121’ and ‘4’) with the self-compatible male parent (‘Tuono’). This study was performed on 80 almond genotypes. The results of this study showed that, in the first cross (‘121’ × ‘Tuono’), genotypes 5, 11, 13, 14, 17, 20, 27, 29, 31, 35, and 38 were identified as being self-compatible and, in the second cross (‘4’ × ‘Tuono’), genotypes 1, 2, 10, 11, 12, 15, 21, 23, 25, 32, 37, 38, and 40 were found to be self-compatible. There were some promising genotypes based on self-compatibility and nut and kernel characteristics; for example, genotype 40 had the highest mean fruit and kernel weights at 2.9 and 1.3 g, respectively. PCR can be used to identify self-compatible genotypes at the juvenile stage. Flower bagging under favourable climatic conditions not only discriminated between self-compatible almond genotypes, but can also be used to measure fruit set percentages. Flower bagging and fluorescence microscopy can be used to determine the level of self-incompatibility. Fluorescence microscopy identified self-incompatible genotypes, even under unfavourable conditions. In general, a combination of all three methods is recommended to increase the accuracy of detecting self-compatible genotypes of almond.     

Temperature-dependent development of <Emphasis Type="Italic">Diglyphus isaea</Emphasis> (Hymenoptera: Eulophidae) on <Emphasis Type="Italic">Liriomyza sativae</Emphasis> (Diptera: Agromyzidae) on cucumber

The development of Diglyphus isaea (Walker), a parasitoid of leafminers, was studied under laboratory conditions at seven constant temperatures (10, 15, 20, 25, 30, 35, and 40°C) on Liriomyza sativae Blanchard reared on cucumber (Cucumis sativus L.). The total development period (oviposition to adult emergence) decreased with increasing temperature between 15 and 35°C. In 10 and 40°C no development rate was found in D. isaea, so that it may be claimed that these temperatures fall outside the temperature range for development. Linear regression was used to describe the relationship between development rate and temperature. For egg to adult development, males of D. isaea required 153.8 degree-days (DD) above the theoretical threshold of 9.2°C and females required 161.3 DD above 9.4°C. Data were fitted to four nonlinear temperature-dependent models. Evaluation of the models took place based on the following criteria: fit to data, number and biological value of the fitted coefficient, and accuracy on the estimation of the thresholds. It could be concluded that the Briere-1 and Briere-2 models are suitable for estimating the minimum, maximum and optimal temperature thresholds of D. isaea. Thermal requirements and temperature thresholds can be used to predict the occurrence, number of generations and population dynamics of D. isaea.     

Responses of cucumber plant to NH4 and NO3 nutrition: The relative addition rate technique vs. cultivation at constant nitrogen concentration

Different N sources (NO₃⁻, NH₄⁺, or NH₄NO₃) at different relative addition rates (RAR) were supplied to cucumber (Cucumis sativus L.), a species sensitive to NH₄⁺ toxicity. For comparison, cucumber plants were also grown at constant concentrations of 1 and 5 mM NH₄⁺ or 5 mM NO₃⁻. The fresh weight of NH₄⁺-fed plants at RAR 0.15 and RAR 0.25 day⁻¹ was similar to that of NO₃⁻-fed plants, while at RAR 0.35 or RAR 0.45 day⁻¹ growth reduction occurred. When available as a constant concentration, NH₄⁺ decreased plant growth at 5 mM. It is concluded that at low rates of N supply the relative addition rate technique can be used for growing cucumber plants with NH₄⁺ as sole N source without deleterious effects.     

Fabrication of hollow nanofibrous structures using a triple layering method for vascular scaffold applications

This study aims to develop a new approach for fabricating hollow nanofibrous yarns by engineering a triple-layer structure (polyvinyl alcohol (PVA) multifilament core surrounded by a layer of PVA nanofibers and a polylactic acid (PLA) nanofiber outer layer). After fabrication of this 3-layer structure, the core portion was extracted, leaving the outer layer intact after dissolving the PVA nanofibers in water. To determine the optimum thickness of the outer layer, hollow nanofiber yarns with five different thicknesses were produced. A hollow nanofiber yarn was also produced using a common method to enable comparison of the methods. In the common method, a core sheath yarn consisting of a PVA multifilament core and a PLA nanofiber outer layer was fabricated, and a hollow yarn was produced by placing the core yarn in hot water. The results revealed facilitation of core extraction from the yarn body of the new 3-layer structure, which occurred due to rapid dissolution of the middle layer. The wicking behavior in the hollow yarn fabricated using the novel method followed the Locus Washburn equation and that of the hollow yarn produced from the core sheath yarn deviated from it. The results demonstrated that tensile properties of hollow nanofiber yarns were improved by increasing the thickness. Furthermore, hemolysis and cytotoxicity assays indicated that the fabricated hollow nanofibrous structure is non-toxic and blood compatible, indicating its potential for use in biomedical applications such as vascular scaffolds.     

Spatial modeling of soil salinity using multiple linear regression,ordinary kriging and artificial neural network methods

Salinity as an important property of soil plays a major role in reducing the fertility in the world. Accurate information about the spatial change of soil salinity is essential for sustainable soil management and utilization in agriculture lands. For this purpose, 150 soil samples were collected from Dashte-e-Tabriz Iran and tested and soil salinity was estimated by land surface parameters including elevation, aspect, length of slope, wetness index, slope and normalized difference vegetation index as basic parameters. In order to model and predict the salinity, ordinary kriging (OK), artificial neural networks (ANN) and multiple linear regressions (MLR) were used. Accuracy of models was evaluated by the coefficient of determination (R²), root mean square error (RMSE) and mean absolute error (MAE). Based on Pearson correlation, elevation, normalized difference vegetation and wetness indices were selected for soil salinity spatial modeling from six land surface parameters. The results showed that the ANN had the lowest RMSE and highest R2. The values of R2, RMSE and MAE were 0.36, 25.89 and 17.06 for regression and 0.56, 17.70 and 13.05 for OK and 0.69, 16.06 and 11.60 for ANN, respectively, which indicated more accuracy of ANN in comparison with MLR and OK.     

Resistance in field populations of <Emphasis Type="Italic">Amrasca devastans</Emphasis> (Hemiptera: Cicadellidae) to new insecticides in Southern Punjab,Pakistan

Cotton jassid, Amrasca devastans (Distant), is an economically important pest of various crops (i.e. cotton, okra, brinjal) and has the potential to become resistant against insecticides due to the intense use of insecticides in the region which entails high selection pressure. To monitor the resistance levels against recently used new chemistry insecticides (nitenpyram, spirotetramat, chlorfenapyr, fipronil, emamectin benzoate, sulfoxaflor, and flonicamid), four field populations of A. devastans collected from Khanewal, Multan, Muzaffargarh and Lodhran districts were examined by leaf dip bioassays. The results revealed the 32.95–136.47 fold resistance to nitenpyram, 23.03–56.74 fold to spirotetramat, 10.84–31.33 fold to chlorfenapyr, 1.20–9.43 fold to fipronil, 3.27–43.77 fold to emamectin benzoate, 0.66–2.81 fold to sulfoxaflor and 0.59–1.25 fold to flonicamid in different field populations, compared to the susceptible strain. Based on present study findings, it may be suggested to discontinue the use of nitenpyram, spirotetramat, chlorfenapyr and emamectin benzoate for which the populations were resistant and the rotational use of fipronil, sulfoxaflor and flonicamid for which the populations were susceptible. Proactive resistance management approaches such as judicious use of insecticides with proper dose selection, time of spray on early stages and correct method of application are necessary to prevent the development of resistance.     

Soil structure changes due to different land-use practices in the central Zagruos region,Iran

In this study, the effect of land-use treatments and the feasibility of fractal dimension to quantify soil aggregate stability were investigated in the central Zagrous, Iran. For this purpose, the non-linear fractal dimension (D_nl), linear fractal dimension (D_l) and the mean weight diameter (MWD) of aggregates were compared. Soil samples from three sites with four adjacent land-use types, namely: forest area (F), cultivated lands adjacent to forest (CAF), pasture (P) and cultivated lands adjacent to pasture (CAP) were collected. Results showed that soils under cultivated lands had higher bulk density (BD) (1.30–1.38 Mg m^?3) compared to the adjacent soils under forest (1.19 Mg m^?3) and pasture (1.21 Mg m^?3). In the 0–15 cm layer, soil organic matter (SOM) content in the cultivated plots were respectively 30% and 31% lower compared to the forest and pasture soils. The lowest CVs belonged to D_nl (5–8%) demonstrating that D_nl was more accurate than D_l (8–14%) and MWD (30–53%) methods. CAP had the largest value of D_nl, while P had the smallest value of D_nl. Difference of D_nl between forest and pasture was not significant, whereas both of them significantly differed from CAF and CAP. D_l did not differ significantly between forest and CAF. There were significant differences between forest and pasture for the measured MWD. Both fractal dimensions had negative correlation with MWD, SOM, hydraulic conductivity (HC) and macroaggregates (>0.25 mm) and positive correlation with BD and total porosity (TP).     

Beta-lactoglobulin structure and retinol binding changes in presence of anionic and neutral detergents

Bovine beta-lactoglobulin (beta-LG) in vivo (in milks) has been found in complexes with lipids such as butyric and oleic acids. To elucidate the still unknown structure-function relationship in this protein, the structural changes of beta-lactoglobulin variant A (beta-LG A) in the presence of anionic surfactant such as sodium n-dodecyl sulfate (SDS) and in the presence of nonionic surfactant such as Triton X-100 have been investigated. Subsequently, the retinol binding by beta-LG has been investigated in the presence of various amounts of these surfactants as its binding indicator. The results of UV-vis and fluorescence studies show a higher denaturating effect of SDS at acid pH that can be due to greater positive charges of beta-LG at this pH indicating also the nonspecific hydrophobic interactions of Triton X-100 with beta-LG at all studied pHs. Isothermal titration calorimetry (ITC) measurements indicate the endothermic nature of beta-LG/SDS interactions and the exothermic nature of Triton X-100/beta-LG interactions. The analysis of the binding data demonstrates the absence of considerable changes in retinol binding properties of beta-LG in the presence of various amounts of these surfactants. This implies that surfactant binding does not change the conformation of beta-LG in the regions defining the retinol-binding site.     

Integration of ANP and Fuzzy set techniques for land suitability assessment based on remote sensing and GIS for irrigated maize cultivation

Land suitability assessment can inform decisions on land uses suitable for maximizing crop yield while making best use, but not impairing the ability of natural resources such as soil to support growth. We assessed the suitability of maize to be produce in 12,000 ha land of Dasht-e-Moghan region of Ardabil province, northwest of Iran. Suitability criteria included soil depth, gypsum (%), CaCO₃ (%), pH, electrical conductivity (EC), exchangeable sodium percentage (ESP), slope (%) and climate data. We modified and developed a novel set of techniques to assess suitability: fuzzy set theory, analytic network process (ANP), remote sensing and GIS. A map of suitability was compared a map created using a traditional suitability technique, the square root method. The coefficient of determination between the land suitability index and observed maize yield for square root and ANP-fuzzy methods was 0.747 and 0.919, respectively. Owing to greater flexibility to represent different data sources and derive weightings for meaningful land suitability classes, the ANP-fuzzy method was a superior method to represent land suitability classes than the square root method.