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

Çeşitli azot ve ekim oranları altında kanola-örtü bitkisi-yabancı ot sisteminin verim kaybının modellenmesi

Possible use of cereal cover crops as a sustainable alternative weed control option in canola fields through optimizing cover crop and its density in canola-weed-cover cropping tripartite systems was modeled using a gamma density function with four parameters. The effect of competition between main crop (canola), cover crop (wheat or barley) and weeds on canola yield was studied in an experiment conducted in 2012/2013. Each cover crop was sown in four seeding rates: 0, 25, 50 and 75 percent under two nitrogen rates of 75 and 150 kg ha-1 . Weed suppression measured as canola relative yield was associated with the increase of seeding rate of cover crop according to a modified gamma density function. Parameters alpha, kappa, eta and lambda summarized the effect of N application on yield response under no cover crop conditions, measure of treatment effect on the curve amplitude, the plant density at which crop yield maximizes and the curve slope at the right tail which was an indication of the treatment effect on the rate of yield reduction beyond the seeding rate that maximized the crop yield, respectively. Model diagnostics and agreement analysis showed that the modified gamma density function described the functional response of the main crop to seeding rate of the cover crop equally well across a variety of treatment effects. Response curve analysis showed that in both levels of nitrogen, canola yield was more responsive to barley as cover crop when compared to winter wheat.Kanola arazilerinde yabancı otlar ile mücadelede tahılların örtü bitkisi olarak kullanımları ve kullanım yoğunluğu dört parametreli gama yoğunluk fonksiyonu kullanılarak modellenmiştir. 2012/2013 yıllarında ana bitki (kanola), örtü bitkisi (buğday veya arpa) ve yabancı otların birbiri ile yarışının kanola verimi üzerine etkisi çalışılmıştır. Her bitki dört farklı ekim sıklığı (% 0, 25, 50 ve 75) ve iki farklı (75 ve 150 kg ha-1 azot) ile ekilmiştir. Gama yoğunluk fonksiyonu ile kanolanın veriminin örtü bitkisinin ekim sıklığına bağlı olması durumundan yararlanılarak yabancı ot baskılanması hesaplanmıştır. Alfa, kappa, eta ve lambda parametreleri sırasıyla örtü bitkisi olmadığı durumda azotun verime etkisini, eğri üzerinde uygulamanın etkisini, ana ürün veriminin maksimum olduğu bitki yoğunluğunu ve uygulamanın verim kaybına etkisini gösteren eğriyi özetlemektedir. Modelleme sonucunda gama yoğunluk fonksiyonu ana bitkinin ekim sıklığına tepkisini tanımlayabilmiştir. Çalışma sonuçları, tüm azot seviyelerinde kanola veriminin arpaya buğdaydan daha fazla tepki gösterdiğini ortaya çıkarmıştır

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

Efficacy evaluation of sulfosulfuron, metsulfuron-methyl plus sulfosulfuron, mesosulfuron-methyl plus ıodosulfuron-methyl and ıodosulfuron plus mesosulfuron herbicides in winter wheat (triticum aestivum L.)

In order to investigate the effect of sulfosulfuron, metsulfuron-methyl plus sulfosulfuron, mesosulfuron-methyl plus iodosulfuronmethyl and iodosulfuron plus mesosulfuron on weed control and wheat biological and grain yield, a two-year field experiment was conducted in Shiraz, Iran, during 2011-2012 and 2012-2013 growing seasons. The experimental design was randomized complete blocks with four replications. Treatments were sulfosulfuron at 18, 20.25 and 22.5 g a.i. ha -1 , metsulfuron-methyl plus sulfosulfuron at 28, 32 and 36 g a.i. ha -1 , mesosulfuron-methyl plus iodosulfuron-methyl at 14.4, 18 and 21.6 g a.i. ha -1 , iodosulfuron plus mesosulfuron at 18, 24 and 30 g a.i. ha -1 and two weedy and weed free checks. Compared with the weedy check, application of herbicides in both growing seasons reduced weed biomass and increased wheat biological and grain yield. Among herbicide treatments, metsulfuron-methyl plus sulfosulfuron at 36 g a.i. ha -1 reduced weed dry matter by 98. 6% and 97.55% in 2011-2012 and 2012-2013, respectively, and the lowest weed dry matter was observed with this treatment. In both years, maximum wheat biological yield was obtained in weed free check that was not significantly different from metsulfuron-methyl plus sulfosulfuron at 36 g a.i. ha -1 . The highest wheat grain yield was obtained with metsulfuron-methyl plus sulfosulfuron at 36 g a.i. ha -1

Prediction of the burden of road traffic injuries in Iran by 2030: Prevalence, death, and disability-adjusted life years

Purpose: Road traffic accidents pose a global challenge with substantial human and economic costs. Iran experiences a high incidence of road traffic injuries, leading to a significant burden on society. This study aims to predict the future burden of road traffic injuries in Iran until 2030, providing valuable insights for policy-making and interventions to improve road safety and reduce the associated human and economic costs. Methods: This analytical study utilized time series models, specifically autoregressive integrated moving average (ARIMA) and artificial neural networks (ANNs), to predict the burden of road traffic accidents by analyzing past data to identify patterns and trends in Iran until 2030. The required data related to prevalence, death, and disability-adjusted life years (DALYs) rates were collected from the Institute for Health Metrics and Evaluation database and analyzed using R software and relevant modeling and statistical analysis packages. Results: Both prediction models, ARIMA and ANNs indicate that the prevalence rates (per 100,000) of all road traffic injuries, except for motorcyclist road injuries which have an almost flat trend, remaining at around 430, increase by 2030. Based on estimations of both models, the rates of death and DALYs due to motor vehicle and pedestrian road traffic injuries decrease. For motor vehicle road injuries, estimated trends decrease to approximately 520 DALYs and 10 deaths. Also, for pedestrian road injuries these rates reached approximately 300 DALYs and 6 deaths, according to the models. For cyclists and other road traffic injuries, the predicted DALY rates by the ANN model increase to almost 50 and 8, while predictions conducted by the ARIMA model show a static trend, remaining at 40 and approximately 6.5. Moreover, these rates for the prediction of death rate by the ANN model increased to 0.6 and 0.1, while predictions conducted by the ARIMA model show a static trend, remaining at 0.43 and 0.07. According to the ANN model, the predicted rates of DALY and death for motorcyclists decrease to 100 and approximately 2.7, respectively. On the other hand, predictions made by the ARIMA model show a static trend, with rates remaining at 200 and approximately 3.2, respectively. Conclusion: The prevalence of road traffic injuries is predicted to increase, while the death and DALY rates of road traffic injuries show different patterns. Effective intervention programs and safety measures are necessary to prevent and reduce road traffic accidents. Different interventions should be designed and implemented specifically for different groups of pedestrians, cyclists, motorcyclists, and motor vehicle drivers

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