Applications of remote sensing are important in improving potato production through the broader adoption of precision agriculture. This technology could be useful in decreasing the potential contamination of soil and water due to the over-fertilization of agriculture crops. The objective of this study was to assess the utility of active sensors (Crop Circle™, Holland Scientific, Inc., Lincoln, NE, USA and GreenSeeker™, Trimble Navigation Limited, Sunnyvale, CA, USA) and passive sensors (multispectral imaging with Unmanned Arial Vehicles (UAVs)) to predict total potato yield and phosphorus (P) uptake. The experimental design was a randomized complete block with four replications and six P treatments, ranging from 0 to 280 kg P ha−1, as

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 u

Image of landsate-7 taken by thematic mapper was used and classified using supervised method. Results of supervised classification indicated presence of nine land cover classes. Salt-soils class shows the highest reflectance value while water bodies' class shows the lowest values. Also the results indicated that soil properties show different effects on reflectance. There was a high significant positive relation of carbonate, gypsum, electric conductivity and silt content, while there was a week positive relation with sand and negative relation with organic matter, water content, bulk density and cataion exchange capacity.

Undesirable growth of potato (Solanum tuberosum L.) crop under an excessive N fertilizer application is the main obstacle presently. This research was conducted to investigate the response of different potato cultivars; Russet Burbank, Shepody, and Superior, and its qualitative characteristics under a series of N rates. Six rates of N fertilization (0–280 kg ha−1) were applied on 11 sites in a randomized complete block design, with four replications. Sites with ≥30 g kg−1 of soil organic matter (OM) produced total tuber yield, marketable yield, and tuber weight per plant 39.5, 45.2, and 54.9%, respectively, higher than sites with ≤30 g kg−1 of OM. Tubers specific gravity increased by 0.18% in the sites with ≥30 g kg−1 of OM.

Landsat-5 Thematic Mapper (TM) has been imaging the Earth since March 1984 and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) was added to the series of Landsat instruments in April 1999. In this paper the two sensors are used to monitoring the agriculture condition and detection the changing in the area of plant covers, the stability and calibration of the ETM+ has been monitored extensively since launch although it is not monitored for many years, TM now has a similar system in place to monitor stability and calibration. By referring to statistical values for the classification process, the results indicated that the state of vegetation in 1990 was in the proportion of 42.8%, while this percentage rose to 52.5% for the same study area in

Crop yield prediction is a critical measurement, especially in the time when parts of the world are suffering from farming issues. Yield forecasting gives an alert regarding economic trading, food production monitoring, and global food security. This research was conducted to investigate whether active optical sensors could be utilized for potato (Solanum tuberosum L.) yield prediction at the mid.le of the growing season. Three potato cultivars (Russet Burbank, Superior, and Shepody) were planted and six rates of N (0, 56, 112, 168, 224, and 280 kg ha−1), ammonium sulfate, which was replaced by ammonium nitrate in the 2nd year, were applied on 11 sites in a randomized complete block design, with four replications. Normalized difference ve

Nitrogen (N) and phosphorus (P) are the most important nutrients for crop production. The N contributes to the structural component, generic, and metabolic compounds in a plant cell. N is mainly an essential part of chlorophyll, the compound in the plants that is responsible for photosynthesis process. The plant can get its available nitrogen from the soil by mineralizing organic materials, fixed-N by bacteria, and nitrogen can be released from plant as residue decay. Soil minerals do not release an enough amount of nitrogen to support plant; therefore, fertilizing is necessary for high production. Phosphorous contributes in the complex of the nucleic acid structure of plants. The nucleic acid is essential in protein synthesis regulation; t

In this study is the phenomenon of desertification risk assessment in the Abu Ghraib area west of Baghdad/Iraq, which has an area of about (384.168 km 2), that the annual mean temperature is more than (22 C). Rainfall was low, ranging from the (200 mm) per year for Iraq and (2.82) mm per year of the study area* temperature is high and evaporation is also high (mm 7.73) per year*, so the climate in general of the dry type and the system of soil moisture is the kind of Aridic (Torric). To this study was to identify three indicators to monitor for the period from 2001-2005 using GIS and these indicators are (soil, groundwater and the nature of land use), using ArcGIS 9.1. The results showed that the risk of desertification was part of the leve

Ground-based active optical sensors (GBAOS) have been successfully used in agriculture to predict crop yield potential (YP) early in the season and to improvise N rates for optimal crop yield. However, the models were found weak or inconsistent due to environmental variation especially rainfall. The objectives of the study were to evaluate if GBAOS could predict YP across multiple locations, soil types, cultivation systems, and rainfall differences. This study was carried from 2011 to 2013 on corn (Zea mays L.) in North Dakota, and in 2017 in potatoes in Maine. Six N rates were used on 50 sites in North Dakota and 12 N rates on two sites, one dryland and one irrigated, in Maine. Two active GBAOS used for this study were GreenSeeker and Holl

Recent phosphorus (P) pollution in the United States, mainly in Maine, has raised some severe concerns over the use of P fertilizer application rates in agriculture. Phosphorus is the second most limiting nutrient after nitrogen and has damaging impacts on crop yield if found to be deficient. Therefore, farmers tend to apply more P than is required to satisfy any P loss after its application at planting. Several important questions were raised in this study to improve P efficiency and reduce its pollution. The objective of this study was to find potential reasons for P pollution in water bodies despite a decrease in potato acreage. Historically, the potato was found to be responsible for P water contamination due to its high P sensitivity a

Data of multispectral satellite image (Landsat- 5 and Landsat-7) was used to monitoring the case of study area in the agricultural (extension and plant density), using ArcGIS program by the method of analysis (Soil adjusted vegetative Index). The data covers the selected area at west of Baghdad Government with a part of the Anbar and Karbala Government. Satellite image taken during the years 1990, 2001 and 2007. The scene of Satellite Image is consists of seven of spectral band for each satellite, Landsat-5(TM) thematic mapper for the year 1990, as well as satellite Landsat-7 (ETM+) Enhancement thematic mapper for the year 2001 and 2007. The results showed that in the period from 1990 to 2001 decreased land area exposed (bare) and increased

One of the main environmental problems which affect extensively the areas in the world is soil salinity. Traditional data collection methods are neither enough for considering this important environmental problem nor accurate for soil studies. Remote sensing data could overcome most of these problems. Although satellite images are commonly used for these studies, however there are still needs to find the best calibration between the data and real situations in each specified area. Landsat satellite (TM & ETM+) images have been analyzed to study soil pollution (Exacerbation of salinity in the soil without the use of abandoned agricultural for a long time) at west of Baghdad city of Iraqi country for the years 1990, 2001 & 2007. All of the th

LandSat Satellite ETM+ image have been analyzed to detect the different depths of regions inside the Tigris river in order to detect the regions that need to remove sedimentation in Baghdad in Iraq Country. The scene consisted of six bands (without the thermal band), It was captured in March ٢٠٠١. The variance in depth is determined by applying the rationing technique on the bands ٣ and ٥. GIS ٩. ١ program is used to apply the rationing technique and determined the results.

In order to take measures in controlling soil erosion it is required to estimate soil loss over area of interest. Soil loss due to soil erosion can be estimated using predictive models such as Universal Soil Loss Equation (USLE). The accuracy of these models depends on parameters that are used in equations. One of the most important parameters in equations used in both of models is (C) factor that represents effects of vegetation and other land covers. Estimating land cover by interpretation of remote sensing imagery involves Normalized Difference Vegetation Index (NDVI), an indicator that shows vegetation cover. The aim of this study is estimate (C) factor values for Part of Baghdad city using NDVI derived from satellite Image of Landsat-7

The Normalized Difference Vegetation Index (NDVI) is commonly used as a measure of land surface greenness based on the assumption that NDVI value is positively proportional to the amount of green vegetation in an image pixel area. The Normalized Difference Vegetation Index data set of Landsat based on the remote sensing information is used to estimate the area of plant cover in region west of Baghdad during 1990-2001. The results show that in the period of 1990 and 2001 the plant area in region of Baghdad increased from (44760.25) hectare to (75410.67) hectare. The vegetation area increased during the period 1990-2001, and decreases the exposed area.

Multi-spectral satellite images of the Landsat satellite by the tow sensitive Thematic Mapper (TM) and Thematic Mapper Enhancement (ETM+), which covered the study area located south east of Iraq. In this research; used the sixth thermal spectral band (Thermal Band) for study the water cover in the AlRazzaza Lake located within the province of Karbala. We intended to study the cover a case of the study area, used satellite images showing the status of region during the period from 1990 to 2001 and 2007. From this study we conclude that cover the water of the study area change in sequence case to decrease during these years.

Phosphorus (P) is an element that is potatoes require in large amounts. Soil pH is a crucial factor impacting phosphorus availability in potato production. This study was conducted to evaluate the influence of P application rates on the P efficiency for tuber yield, specific gravity, and P uptake. Additionally, the relationship between soil pH and total potato tuber yield was determined. Six rates of P fertilization (0–280 kg P ha−1) were applied at twelve different sites across Northern Maine. Yield parameters were not responsive to P application rates. However, regression analysis showed that soil pH was significantly correlated with total potato tuber yield(R2 = 0.38). Sites with soil pH values < 6 had total tuber yields,

n this study, data or X-ray images Fixable Image Transport System (FITS) of objects were analyzed, where energy was collected from the body by several sensors; each sensor receives energy within a specific range, and when energy was collected from all sensors, the image was formed carrying information about that body. The images can be transferred and stored easily. The images were analyzed using the DS9 program to obtain a spectrum for each object,an energy corresponding to the photons collected per second. This study analyzed images for two types of objects (globular and open clusters). The results showed that the five open star clusters contain roughly t

     Nowadays, a strong relationship between the agriculture sectors and digital technologies is really interesting. The article describes how recent intelligent technologies can improve agricultural fields. Mobile applications are software programs created on smartphones, tablets, and computers. Agricultural fields mainly represent the pillar of the economy and the business sector that fulfills the world's food requirements. The United States has a valuable rank in potato production, which depends on this production economically.

Nevertheless, so many insects affect potato yield production quantitatively and qualitatively. So, a smartphone App was created to help potato growers diagnose insects that directly attack potato cro

     The increased food requirement puts intense pressure on the agriculture community to grow more from the same resources resulting in people leaving the farming business. This happened not exclusively due to the industrial pressure to produce more but to the lack of technology adoption among growers. The use of the sensor in agriculture is not new, but its adoption among agriculture producers is a challenge for industry and scientists. This study aimed to determine sensors used in agricultural fields with challenges and prospects. The study found that sensors have successfully been used at the industry level with highly skilled labor; however, their adoption is challenging in rural agriculture systems due to the lack of a support

     The extraction, study, and accurate interpretation of the morphology database of a basin are the basic blocks for building a valid geomorphological understanding of this basin. In this work, a new approach is presented which is to use three different GIS based methods to extract databases with specific geographical information and then use the concept of information intersection to make a realistic geomorphological perspective for the study area.

In the first method, data integration of remote sensing images from Google Map and SRTM DEM images were used to identify Horan basin borders.

In the second method, the principle of data integration was represented by extracting the quantitative values of the morphometric c

The global food supply heavily depends on utilizing fertilizers to meet production goals. The adverse impacts of traditional fertilization practices on the environment have necessitated the exploration of new alternatives in the form of smart fertilizer technologies (SFTs). This review seeks to categorize SFTs, which are slow and controlled-release Fertilizers (SCRFs), nano fertilizers, and biological fertilizers, and describes their operational principles. It examines the environmental implications of conventional fertilizers and outlines the attributes of SFTs that effectively address these concerns. The findings demonstrate a pronounced environmental advantage of SFTs, including enhanced crop yields, minimized nutrient loss, improved nut

Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,