Distinguishing Growth Stages of Wheat Crop by Remote Sensing Techniques and Time Series Analysis

Remote sensing has attracted the attentions by providing a broad and comprehensive view of the world. The use of remote sensing in various fields such as agriculture is constantly expanding. Spectral bands in visible and infrared ranges can be used to discriminate between phenomena and ground cover by computing various spectral indices. Investigating plant physiology is essential to know the physiological and ecological aspects of plant functions. In this study, images of Sentinel-2 satellite were used to compute spectral indices and correlate them with phenological stages of wheat crop in two agricultural centers in Fars province, Iran. Zadoks scale is one of the most reputed methods to state growth stages of wheat crop. The Zadoks scale uses two-digit codes to demonstrate different phenological processes. In this study, nine growing stages were carefully identified using ground truth method. After calculating two spectral indices of normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI) on satellite images of various dates during the growing season, NDVI and SAVI time series were generated. Each time series image consisted of nine bands, each band being an image obtained from a wheat growing stage. Study the trend between NDVI and SAVI indices and the Zadoks scale showed that the phenological stages of wheat can be identified using remote sensing technology

Split nitrogen sources effects on nitrogen use efficiency, yield and seed quality of safflower (Carthamus tinctorius L.)

The effects of nitrogen (N) on crop yields have historically been assessed with field trials, but selection and use of the best sources and optimal timing N applications have a significant role in realizing the maximum potential of oilseeds quality and quantity. This study was conducted to determine the combine effects of N sources (ammonium nitrate (AN), ammonium sulfate (AS), sulfur coated urea (SCU), and urea (U)) and split N fertilization ((1/4,3/4,0), (1/3,1/3,1/3), (1/2,1/2,0), and (1/3,2/3,0)) on safflower (Carthamus tinctorius L.) some growth characters, yield and seed quality, and N use efficiency based on a split plot design with three replications at the experimental research station, Shiraz University in 2015 and 2016. The highest safflower dry matter (5140.93 kg ha-1), seed yield (3303.52 kg ha-1) and protein yield (694.95 kg ha-1) were achieved with the application of AN fertilizer in a split pattern of 1/2,1/2,0 (applying half of the N at sowing time and the rest at stem elongation), while the highest oil yield (753.09 kg ha-1) was observed by U fertilizer and similar split pattern. Applying AN fertilizer and split patterns of 1/3,2/3,0 (applying one third of the N at sowing and two thirds of the N at stem elongation) and 1/4,3/4,0 (applying one quarter of the N at sowing and three quarters at stem elongation) maximized safflower N uptake efficiency (NUpE) (0.78 kg kg-1). However, the highest N utilization efficiency (NUtE) (43.70 kg kg-1) was obtained when AN fertilizer in a split pattern of 1/2,1/2,0 was applied. On the contrary, applying AS and SCU fertilizers was less effective on safflower performance by all split patterns. It is concluded that applying AN fertilizer in a split pattern of 1/3,2/3,0 and or U fertilizer in a split pattern of 1/2,1/2,0 not only enhanced safflower growth, yield and seed quality improved, but also increased the N use efficiency of safflower

STATISTICAL THERMODYNAMICS APPROACH TO THE PREDICTION OF THERMODYNAMIC PROPERTIES OF HYDROCARBONS AND HYDROCARBON MIXTURES.

STATISTICAL THERMODYNAMICS APPROACH TO THE PREDICTION OF THERMODYNAMIC PROPERTIES OF HYDROCARBONS AND HYDROCARBON MIXTURES

Impact of sowing date and tillage method on morphophysiological traits and yield of corn

Environmental variations related with different sowing dates have an altering effect on the growth and development of corn plants. A field experiments were conducted to evaluate the effect of sowing date and tillage method on corn growth and yield. The treatments included two tillage systems (conventional and no tillage) and seven sowing dates (11-May, 18-May, 25-May, 1-Jun, 8- Jun, 15-Jun and 22-Jun). The interaction between tillage method and sowing date showed that the highest kernel yield (KY), biological yield (BY) and harvest index (HI) were observed at first sowing date and conventional tillage method and the lowest KY, HI and BY were obtained in no-tillage method and latest sowing date in both years. Delay in sowing from 11-May to 22-Jun decreased significantly the plant height, leaf number, leaf area index and yield by 6.43, 7.98, 17.36 and 42.7% in 2014 and 7.93, 8.87, 14.88 and 40.01% in 2015, respectively. The highest crop growth rate (CGR) was observed in conventional tillage (56 and 49 (g day 1m -2 )) as compared to no-tillage (45.7 and 46.5(g day-1m -2 )) in 2014 and 2015, respectively. The leaf area index (LAI) had a positive and significant correlation with corn height, leaf number and yield

Assessing and mapping multi-hazard risk susceptibility using a machine learning technique

The aim of the current study was to suggest a multi-hazard probability assessment in Fars Province, Shiraz City, and its four strategic watersheds. At first, we construct maps depicting the most effective factors on floods (12 factors), forest fires (10 factors), and landslides (10 factors), and used the Boruta algorithm to prioritize the impact of each respective factor on the occurrence of each hazard. Subsequently, flood, landslides, and forest fire susceptibility maps prepared using a Random Forest (RF) model in the R statistical software. Results indicate that 42.83% of the study area are not susceptible to any hazards, while 2.67% of the area is at risk of all three hazards. The results of the multi-hazard map in Shiraz City indicate that 25% of Shiraz city is very susceptible to flooding, while 16% is very susceptible to landslide occurrences. For four strategic watersheds, it is notable that in the Dorodzan Watershed, landslides and floods are the most important hazards; whereas, flood occurrences cover the largest area of the Maharlou Watershed. In contrast, the Tashk-Bakhtegan Watershed is so sensible to floods and landslides, respectively. Finally, in the Ghareaghaj Watershed, forest fire ranks as the strongest hazard, followed by floods. The validation results indicate an AUC of 0.834, 0.939, and 0.943 for the flood, landslide, and forest fire susceptibility maps, respectively. Also, other accuracy measures including, specificity, sensitivity, TSS, CCI, and Gini coefficient confirmed results of the AUC values. These results allow us to forecast the spatial behavior of such multi-hazard events, and researchers and stakeholders alike can apply them to evaluate hazards under various mitigation scenarios.(VLID)482587