Assessment of Iranian wheat germplasm for salinity tolerance using analysis of the membership function value of salinity tolerance (MFVS)

Journal of Crop Science and Biotechnology - Salinity stress is one of the most important abiotic stresses which reduce crop production worldwide. In this study, 17 morphological and agronomic...     

Leaf macro- and micro-morphological altitudinal variability of Carpinus betulus in the Hyrcanian forest (Iran)

We investigated the altitudinal variation of Carpinus betulus L. in the Hyrcanian forest using leaf macro-morphological and micro-morphological traits. We collected a total of 1600 leaves from two locations. In each location, we sampled six populations along an altitudinal gradient ranging from 100 m to 1,150 m. We found that trees in the higher elevations have smaller leaf lamina than those in the lower elevations. In contrast, leaf mass per area was high at low altitudes and increased newly at the higher ones. Stomatal dimension was negatively correlated with elevation, while stomatal density was positively correlated with elevation. We also found that two transects showed the same plasticity trend. Leaf area showed the highest plasticity, while the number of veins showed the lowest plasticity. This study shows that altitude, and related temperature and rainfall, represents an important driving force in Carpinus betulus leaf morphological variation. Moreover, our results suggest that leaf area, leaf mass per area and stomatal density could influence the species responses to different ecological conditions.     

车载电源多电动机测试平台耦合分析与解耦控制研究

为研究纯电动汽车车载电源性能在环测试,提出了由异步电动机-直流电动机组成的测试平台,是集机、电、磁于一体的复杂机电耦合系统。首先对该测试平台进行了机电耦合分析,建立了其机电耦合模型。根据α阶积分逆系统原理构建了伪线性系统,实现了对该复杂机电耦合系统的线性化。在此基础上,将自适应模糊神经网络与逆系统结合,构造出自适应模糊神经网络逆系统对原系统进行解耦控制。仿真和实验结果表明:自适应模糊神经网络逆系统控制取得了较好的解耦效果;异步电动机的反馈转速和直流电动机的反馈转矩均较好地跟踪了参考转速和参考转矩。此外,通过该测试平台可得到在整个循环工况中与异步电动机相连的电池电压、电流以及功率的变化曲线,为复合电源的在环测试提供了理论依据。     

Healing ability and diameter growth of lime-trees (<Emphasis Type="Italic">Tilia begonifolia</Emphasis> Stev.) following logging wounds

Lime-trees (Tilia begonifolia Stev.) have countless ecological and economical values in the northern forests of Iran. Bole wounds on residual trees are commonly caused by logging. The healing ability of bole wounds and the effect of bole wounds on diameter growth in lime-trees were assessed in a natural mixed uneven-age stand. The susceptibility to decay in relation to the wound severity was also evaluated. Condition and location of lime-trees before and after selective logging were determined through systematic plot sampling. The position of each lime-tree was identified on a topographical map using the global positioning system. After 10 years from wound occurrence, tree and wound characteristics were also re-measured. Overall, 68 stems (9.7 stem ha^?1) of lime-trees were found in the sampled area, 25 stems (36.8%) were damaged in the form of bole wound, and 43 stems (63.2%) were undamaged. Statistical differences between wounded or non-wounded lime-trees in terms of diameter and height were not found. Most of the wounds occurred at the height of < 1 m; the average wound size was 370.5 cm². Wound severity was related to wound size and wound position. Wound width healing rate was 6.2 mm year^?1. The wound shape was found to be a healing factor as the healing rate by width was higher than that by length. Healed wounds were only 12, 60% of bole wounds resulted in decay. Diameter growth of wounded trees was 43.5% lower than undamaged trees. The average annual diameter growth decreased by increasing wound severity. The results indicated the lime-tree is a very sensitive species to damage caused by logging (bole wound). Single-tree selection cutting needs more careful logging operations to reduce damage on residual lime-trees in order to safeguard this species, valuable in ecologic and economic terms.     

Time Prediction Models and Cost Evaluation of Cut-To-Length (CTL) Harvesting Method in a Mountainous Forest

Time equations are derived for felling with chainsaw, skidding with cable wheeled skidder, loading with grapple hydraulic loader and trucking of logs within a cut-to-length harvesting method. The continuous time study method was applied to collect data for felling, skidding, loading and a transportation model. Multiple regression analysis via SPSS software was applied to develop the time models. Felling time was found to be highly dependent on diameter at breast height. Skidding distance, winching distance, slope of the trail and piece volume were significant variables for the skidding time prediction model. The loading time model was developed considering piece volume. Transportation distance and load volume were used as independent variables in modeling the transportation time. The net production of felling was estimated at 12 trees/h (56.65 m³/h). The net production rates for skidding, loading and traveling averaged 18.51, 41.90 and 3.32 m³/h respectively. The total cost of harvesting from stand to mill was estimated 19.70 €/m³. The skidding phase was the most expensive component of the cut-to-length method. The bucking and delimbing components were less costly than the other logging phases. The results of this study can be used for harvesting planning and productivity optimization.     

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.