Nitrogen (N) fertilizer rate is important for high yield and good quality of potato tubers. In this dissertation, I seek to study the response of different potato cultivars under different N fertilizer rates and how that can impact tuber quality, examine the performance of active optical sensors in improving a potato yield prediction algorithm, and evaluate the ability of active optical sensors (GreenSeeker (GS) and Crop Circle (CC)) to optimize a N recommendation algorithm that can be used by potato growers in Maine. This research was conducted at 11 sites over a period of two years (2018–2019) in Aroostook County, Maine; all sites depended on a rainfed system. Three potato cultivars, Russet Burbank, Superior, and Shepody, were planted under six rates of N (0-280 kg ha-1), ammonium sulfate and ammonium nitrate, and were applied in a randomized complete block design (RCBD) with four replications. Active optical sensor readings (normalized difference vegetation index (NDVI)) were collected weekly after the fourth leaf stage began. The coefficient of determination (R2) between soil organic matter (OM) content and total tuber yield for all sites combined was 0.78**. Sites with ≥ 30 g kg-1 of soil OM produced higher total tuber yield, marketable yield, and tuber weight per plant (39.45%, 45.22%, and 54.94%, respectively) than sites with ≤ 30 g kg-1 of OM. Specific gravity increased by 0.18% in the sites with ≥ 30 g kg-1 of OM. The total tuber yield for the three cultivars was maximized at 168 kg N ha-1. Vegetation indices measurements obtained at stages of 16 or 20 fully expanded leaves were significantly correlated with tuber yield, which can be used in the yield prediction model. Sensor measurements obtained at the 20th leaf stage were significantly correlated with tuber yield, with the exponential model showing the best fit for the regression curve. The recommended N rate calculated based on in-season sensor readings was reduced by approximately 12–14% compared to the total N rate that growers currently apply based on the conventional approach.
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The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.
The time series of statistical methods mission followed in this area analysis method, Figuring certain displayed on a certain period of time and analysis we can identify the pattern and the factors affecting them and use them to predict the future of the phenomenon of values, which helps to develop a way of predicting the development of the economic development of sound
The research aims to select the best model to predict the number of infections with hepatitis Alvairose models using Box - Jenkins non-seasonal forecasting in the future.
Data were collected from the Ministry of Health / Department of Health Statistics for the period (from January 2009 until December 2013) was used
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KE Sharquie, AA Noaimi, MM Al-Salih, Saudi Medical Journal, 2008 - Cited by 56
Sea level rise (SLR) due to climate change is affecting the coastline, causing shoreline changes, the degradation of mangrove forests, and the destruction of coastal resources. This is the cause of a huge amount of mangrove degradation in many parts of the Ganges–Brahmaputra–Meghna delta. A total of 90% of people have been forced to migrate from the island due to extreme weather conditions. In this study, remote sensing (RS) and geographic information system (GIS) techniques were used for LULC change and shoreline shift analyses of Ghoramara Island. LULC classification was carried out using thirty years of Landsat datasets with intervals of ten years (1990 and 2000) and intervals of five years (2005, 2010, 2015, and 2020). The classific
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This study evaluated the influence of administering different levels of L-arginine into eggs of 0-day-old Japanese quail embryos. On day 0 of incubation, 480 eggs (120 for each treatment group) were injected with 0% arginine (C group), 1% arginine (T1), 2% arginine (T2) or 3% arginine (T3). After hatching, 336 quail chicks (84 chicks produced from each in ovo injection treatment) were placed in an experimental quail house and allocated to four treatment groups of three replicates, with 16 quail chicks for each replicate. Traits involved in this study were hatchability rate, initial body weight (7 days of age), final body weight (42 days old), feed intake, weight gain, feed conversion ratio and blood serum glucose, protein, cholesterol, tota
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Introduction: Cutaneous leishmaniasis (CL) is a common protozoan disease in Iraq characterized by localized ulcers, primarily on exposed skin. This study aimed to investigate the hematological parameters of infected patients using a complete blood count (CBC) in the endemic area of Diyala Governorate, northeast of Baghdad. This has been studied in newly diagnosed, untreated individuals and patients receiving sodium antimony gluconate. Methodology: Hematological screening was performed on blood samples from 161 patients with microscopically diagnosed cutaneous leishmaniasis before and after treatment. Anti-Leishmania IgG was also assessed by ELISA in seropositive and seronegative subjects. Results: The newly diagnosed, untreated pati
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