ECOPERSIA
Volume:11 Issue: 3, Summer 2023

The aim of this study was to investigate nutritional and phytochemical changes of A. jesdianum leaves on different planting dates.

The same wild bulbs were cultivated in the October/January 2017 and harvested  on 25 April, 2018. Essential oils were analyzed by Gas Chromatography (GC)and Gas chromatography mass spectrometry (GC-MS). Also, total protein, vitamin C, non-structural sugars, antioxidant activity and nutritional elements of the shoots were measured.

The main compounds of the leaf essential oil in October, November, December and January were Dimethyl trisulfide (12.11%, 15.1%, 12.4% and 10.2%). The results showed that the morphological traits of A. jesdianum in different planting dates have a significant difference(P > 0.05). The highest germination (68.33%), shoot height (31.33 cm), root leagth (16.33 cm), aerial dry weight (3.50 g), bulb diameter (3.76 cm), bulb fresh weight (12.66 g), bulb dry weight (6.40 g), leaf length (24.4 cm) and leaf width (1.43 cm) were recorded in November plants. As well as bulbs cultivated in November had the highest , amount of potassium (13.7 mg.g-1 DW), iron (2.5 μg.g-1 DW), copper (0.43 μg.g-1 DW), zinc (2.1 μg.g-1 DW) and manganese (2 μg.g-1 DW) compared to other planting dates. The highest amount of vitamin C (86.33 mg.100g-1 FW), antioxidant potency (IC50=37.00 μg.mL-1 , phenolic (77.00 mg galic acid.100 mg-1 DW), flavonol (66.66 mg rutin.100 mg-1 DW), and flavonoid (136.33 mg rutin.100 mg-1 DW) were obtained in the planted samples in November.

In this study, the antioxidant properties of hydrolyzed protein from longtail tuna dark muscle with commercial enzymes (alcalase, alkaline protease, and evatase) were investigated.

Protein hydrolysates from tuna dark muscle were prepared by different enzymes Degree of hydrolysis (DH) was performed by TCA technique. The five aliquots at 60, 180, 240, 300, and 360 min were gathered during hydrolysis. The antioxidant activity of aliquots was monitored by in vitro assays (DPPH inhibition ability and Ferric (Fe3+) reducing power).

The antioxidant activities of protein hydrolysate from tuna dark muscle (TDM) increase with increasing time and DH. Alcalase hydrolyzed protein (AHP) generally showed higher antioxidative activity than evatase hydrolyzed protein (EHP) and alkaline protease hydrolyzed protein (APHP). Among the samples (concentration 3 mg.ml-1), AHP at 360 min significantly exhibited the highest ability to scavenge DPPH radical (72.6 %). Furthermore, AHP and APHP significantly showed a minimum IC50 value of 1.1 mg.ml-1 at 240 and 360 min hydrolysis. APHP significantly exhibited the highest ferric reducing power of 0.83 at 300 min and 0.76 at 240 min. AHP and APHP significantly showed the highest ferric reducing power of 0.74 at 360 min (p < 0.05).

This study confirmed that protein hydrolysate from TDM could be a good source of antioxidant peptides. In addition, the antioxidant activity of hydrolyzed protein relay on protease type and hydrolysis condition.

Access paths to natural attractions in protected areas must be designed and developed considering their impacts on the environment. Visitors' movement in the areas where are highly sensitive to soil erosion may cause destructive impacts on trails such as widening, increasing susceptibility to erosion, and damaging surrounding vegetation. This research aims to suggest a sustainable trail network (off-road vehicles and hiking trails) in Sarigol National Park and Protected Area,

 The study has been carried out based on the least-cost path algorithm, and comparing the results with existing recreation trails. The required field information including the width of 431 trails and 15 environmental factors affecting the trail width was obtained through the study area. Analysis of Covariance has been used for estimating the potential of pathwidth expansion. The accuracy of the model was assessed by root mean square error which is 29cm for hiking trails and 126cm for off-road vehicles trails.

One optimized off-road vehicles trail and one optimized hiking trails in the study are were suggested using degradation map and least cost patch model. The findings of the present study indicated that existing paths are located in areas with high susceptibility to widening because of crowding.

Drought limits plant growth and productivity throughout the world. Narrow-leaved plantain (Plantago lanceolata L.) is widely used to treat some human diseases and reduce antibiotic nutrition. This study aimed to examine the response of four local ecotypes of P. lanceolata to different drought stress levels in a field experiment.

A split-plot design was conducted using a randomized complete block design (RCBD) with three replications at the farm of Research Institute of Forests and Rangelands, Karaj, Iran, 2018. The main factor was drought stress at three levels (D1= normal irrigation, D2= drought stress after the flowering stage with supplemental irrigation at the filling stage, and D3= stop irrigation after flowering. The second factor contained four ecotypes: G1-Arak, G2-Khoramabad, G3-Meshkinshahr1, and G4-Meshkinshar2. Data were collected and statistically analyzed for grain yield and yield components.

Results showed a significant effect of drought stress and ecotype on all traits except root lengths (p<0.05). The ecotype × drought stress interaction effects were significant for spike number per plant, leaf number per plant, leaf width, and plant height (p<0.05). The mean values of grain yield in D1, D2, and D3 were 729.41, 660.81, and 595.95 kg.h-1, respectively.

The highest grain yield of 670.92 kg.h-1 was obtained from G1-Arak. This ecotype produced higher grain yields under mild and severe stress than the other ecotypes and was recommended for breeding improved varieties.

In this study, the response of individual trees and the stand structure to windstorm damage were investigated in a mixed broad-leaf forest stands located in Darabkola Forest, Sari, northern Iran. A field survey was conducted over an area of 2612 ha of the given stands.

A full inventory was performed for all trees with diameter at breast height≥ 10cm and all damaged (i.e., snapped, snags, branch loss, broken trunk or uprooted) trees were identified within the study area. Tree height was measured using Laser Distance Meter for trees more than 10 m high and a Clinometer for all trees <10m. The percentage of trees damaged was the dependent variable; but, independent variables included number, mean height (m), total basal area (m2) and volume trees (m3). Independent t-test was performed to compare the mean of trees based on diameter classes. Also, the affection of height on susceptibility to windstorm effects was tested by comparing mean trees height within each class.

The number of the damaged trees varied with species, ranging from 0.04 % (2 individuals) in Tilia begonifolia Stev to 53.7 % (2709 individuals) in Fagus orientalis L. Among the damaged trees 5054 recorded, 2231 (44.20 %) had been snapped and 787 (15.6 %) uprooted, and 2028 (40.20 %) were snags. Among the species, Fagus orientalis L. (47.7 %), Alnus subcordata C. A. Mey. (19.7 %) and Carpinus betulus L. (18.8 %) were most susceptible to uprooting, whereas Populus caspica Bornm, Quercus castaneifolia C. A. Mey. and Ulmus glabra Huds. were the least susceptible to uprooting. The species differed significantly in their susceptibility to snapping. Trees ≥60cm dbh were more likely to be snapped (78 %) or snags (69 %), whereas trees <60 cm dbh were more presumably to be uprooted (50 %). Also, about one third (33 %) of total trees larger than 60 cm (D.B.H) have showed distinct effects and individual trees >20 m were more commonly uprooted. The number of snapped trees, snags and uprooted trees had a sharp increase in trees taller than 20m.

Our finding showed that Oriental beech and Common hornbeam to be species that were most susceptible to both being snapped and snagged, whereas Caucasian alder had the most uprooting damage among the other species. Overall, features like species, D.B.H, height and height to diameter ratio (H/D.B.H), were intensively related with the type and severity of windstorm damage. The findings showed that windstorms cause substantial structural effects in mixed stands of beech and hornbeam.

The objective of the current study was to evaluate the effectiveness of various extraction techniques, namely supercritical carbon dioxide (SC-CO2), ultrasound, and enzymatic methods, in comparison to the conventional wet reduction method, in terms of oil yield, quality attributes, and fatty acid composition in common kilka oil.

Mentioned methods were used to extract fish oil. Then, their quality oxidation, including PV, TBA, FFA, and CD, and fatty acid composition were evaluated.

The study's findings revealed that the SC-CO2 extraction method exhibited the most favorable outcome in terms of extraction yield, achieving a remarkable rate of 89.6%. The lowest oxidation indexes including PV (1.78 ± 0.19 mmol.kg-1), TBA (0.54 ± 0.03 mg MA.kg-1), FFA (35.49 ± 0.52 mg FFA.g TAG-1), and CD (7.61 ± 0.34 %) was found in oil extracted with SC-CO2 method. The fatty acid profile of oil extracted by SC-CO2 exhibited higher polyunsaturated fatty acid (PUFA) (29.81 ± 0.27) and lower saturated fatty acid (SFA) (27.64 ± 0.20) and monounsaturated fatty acid (MUFA) (34.78 ± 0.67) than those obtained by the other extraction methods (p > 0.05). The n-3/n-6, PUFA/SFA, and EPA + DHA/C16 ratios were higher for oil extracted by SC-CO2 than the other three methods.

The common kilka oil, extracted through supercritical carbon dioxide (SC-CO2), can be regarded as an abundant source of crucial polyunsaturated fatty acids belonging to the n-3 series.

This study aimed to propose an effective model for estimating soil moisture by integrating the optical trapezoid method with a deep learning Long Short-Term Memory (LSTM) model. The performance of the proposed model was compared with two other methods, i.e., Partial Least Squares (PLS) regression and Group Method of Data Handling (GMDH) multivariate neural network.

This study combined the optical trapezoid method with deep learning models to propose an effective model for soil moisture estimation in the Maragheh watershed. A total of 499 in-situ soil moisture data were collected. Relative moisture content was calculated using the optical trapezoid method and imported into the LSTM model, along with other inputs such as spectral indices and DEM-based derived variables. The performance of the mentioned models was assessed both with and without the optical trapezoid method to evaluate its efficacy on the performance of AI models.

The results demonstrate that the combined model of deep learning LSTM and the optical trapezoid method achieves satisfactory performance, with an R2 of 0.95 and a RMSE of 1.7%. The PLS and GMDH methods performed moderately, both without the involvement of the optical trapezoid method and in the combined mode.

This study shows that the optical trapezoid method can improve the performance of deep-learning models in estimating soil moisture. However, considering the significant difference in computational costs among these models, choosing the appropriate model depends on the user's objectives and desired level of accuracy and precision.