Remote Sensing as a Precision Farming Tool in the Nile Valley, Egypt

Detecting stress in plants resulting from different stressors including nitrogen deficiency, salinity, moisture, contamination and diseases, is crucial in crop production. In the Nile Valley, crop production is hindered perhaps more fundamentally by issues of water supply and salinity. Predicting stress in crops by conventional methods is tedious, laborious and costly and is perhaps unreliable in providing a spatial context of stress patterns. Accurate and quick monitoring techniques for crop status to detect stress in crops at early growth stages are needed to maximize crop productivity. In this context, remotely sensed data may provide a useful tool in precision farming. This research aims to evaluate the role of in situ hyperspectral and high spatial resolution satellite remote sensing data to detect stress in wheat and maize crops and assess whether moisture induced stress can be distinguished from salinity induced stress spectrally. A series of five greenhouse based experiments on wheat and maize were undertaken subjecting both crops to a range of salinity and moisture stress levels. Spectroradiometry measurements were collected at different growth stages of each crop to assess the relationship between crop biophysical and biochemical properties and reflectance measurements from plant canopies. Additionally, high spatial resolution satellite images including two QuickBird, one ASTER and two SPOT HRV were acquired in south-west Alexandria, Egypt to assess the potential of high spectral and spatial resolution satellite imagery to detect stress in wheat and maize at local and regional scales. Two field work visits were conducted in Egypt to collect ground reference data and coupled with Hyperion imagery acquisition, during winter and summer seasons of 2007 in March (8-30: wheat) and July (12-17: maize). Despite efforts, Hyperion imagery was not acquired due to factors out with the control of this research. Strong significant correlations between crop properties and different vegetation indices derived from both ground based and satellite platforms were observed. RDVI showed a sensitive index to different wheat properties (r > 0.90 with different biophysical properties). In maize, GNDVIbr and Cgreen had strong significant correlations with maize biophysical properties (r > 0.80). PCA showed the possibility to distinguish between moisture and salinity induced stress at the grain filling stages. The results further showed that a combined approach of high (2-5 m) and moderate (15-20) spatial resolution satellite imagery can provide a better mechanistic interpretation of the distribution and sources of stress, despite the typical small size of fields (20-50 m scale). QuickBird imagery successfully detects stress within field and local scales, whereas SPOT HRV imagery is useful in detecting stress at a regional scale, and therefore, can be a robust tool in identifying issues of crop management at a regional scale. Due to the limited spectral capabilities of high spatial resolution images, distinguishing different sources of stress is not directly possible, and therefore, hyperspectral satellite imagery (e.g. Hyperion or HyspIRI) is required to distinguish between moisture and salinity induced stress. It is evident from the results that remotely sensed data acquired by both in situ hyperspectral and high spatial resolution satellite remote sensing can be used as a useful tool in precision farming in the Nile Valley, Egypt. A combined approach of using reliable high spatial and spectral satellite remote sensing data could provide better insight about stress at local and regional scales. Using this technique as a precision farming and management tool will lead to improved crop productivity by limiting stress and consequently provide a valuable tool in combating issues of food supply at a time of rapid population growth

Spectral Characteristics for Estimation Heavy Metals Accumulation in Wheat Plants and Grain

Plants would the start with step of a metal's pathway starting with the dirt on heterotrophic creatures for example, such that animals and humans, thus the substance from claiming metallic follow components for eatable parts of a plant representable accessible load of these metals that might enter those natural way of life through plants. Around metal elements, Cu and Zn would micro nutrients as they are essential in trace concentrations for physiological processes in plants. Furthermore consequently would a critical part from the soil–plant–food continuum. Therefor this study aimed to analysing the performance of multivariate hyperspectral vegetation indices of wheat (Triticum aestivum L.) in estimating the accumulation of these elements in plant dry mutter and the final product of Egyptian wheat crop irrigated with high concentrations of Zn and Cu. We applied five concentrations for each element (0.05, 20, 40, 100, and 150 ppm of Zn) and (0.02, 8, 10, 12, and 15 ppm of Cu) to a controlled greenhouse experiment to examine the effect of these concentrations on plant spectral characteristics and study the possibility of using spectroradiometry measurements for identifying the grain content of these metals. The results demonstrated that The hyperspectral vegetation indices had a potential for monitoring Zn concentration in the plant dry matter. NPCI and PSSR had a highest correlation with Cu phytoaccumulation into the grains with highest significant level (P-Value < 0.01) and (r) values (-0.39, -0.42)

Integration of radiometric ground-based data and high-resolution quickbird imagery with multivariate modeling to estimate maize traits in the nile delta of Egypt

In site-specific management, rapid and accurate identification of crop stress at a large scale is critical. Radiometric ground-based data and satellite imaging with advanced spatial and spectral resolution allow for a deeper understanding of crop stress and the level of stress in a given area. This research aimed to assess the potential of radiometric ground-based data and high-resolution QuickBird satellite imagery to determine the leaf area index (LAI), biomass fresh weight (BFW) and chlorophyll meter (Chlm) of maize across well-irrigated, water stress and salinity stress areas in the Nile Delta of Egypt. Partial least squares regression (PLSR) and multiple linear regression (MLR) were evaluated to estimate the three measured traits based on vegetation spectral indices (vegetation-SRIs) derived from these methods and their combination. Maize field visits were conducted during the summer seasons from 28 to 30 July 2007 to collect ground reference data concurrent with the acquisition of radiometric ground-based measurements and QuickBird satellite imagery. The results showed that the majority of vegetation-SRIs extracted from radiometric ground-based data and high-resolution satellite images were more effective in estimating LAI, BFW, and Chlm. In general, the vegetation-SRIs of radiometric ground-based data showed higher R2 with measured traits compared to the vegetation-SRIs extracted from high-resolution satellite imagery. The coefficient of determination (R2) of the significant relationships between vegetation-SRIs of both methods and three measured traits varied from 0.64 to 0.89. For example, with QuickBird high-resolution satellite images, the relationships of the green normalized difference vegetation index (GNDVI) with LAI and BFW showed the highest R2 of 0.80 and 0.84, respectively. Overall, the ground-based vegetation-SRIs and the satellite-based indices were found to be in good agreement to assess the measured traits of maize. Both the calibration (Cal.) and validation (Val.) models of PLSR and MLR showed the highest performance in predicting the three measured traits based on the combination of vegetation-SRIs from radiometric ground-based data and high-resolution QuickBird satellite imagery. For example, validation (Val.) models of PLSR and MLR showed the highest performance in predicting the measured traits based on the combination of vegetation-SRIs from radiometric ground-based data and high-resolution QuickBird satellite imagery with R2 (0.91) of both methods for LAI, R2 (0.91–0.93) for BFW respectively, and R2 (0.82) of both methods for Chlm. The models of PLSR and MLR showed approximately the same performance in predicting the three measured traits and no clear difference was found between them and their combinations. In conclusion, the results obtained from this study showed that radiometric ground-based measurements and high spectral resolution remote-sensing imagery have the potential to offer necessary crop monitoring information across well-irrigated, water stress and salinity stress in regions suffering lack of freshwater resources

Assessing the Efficiency of Remote Sensing and Machine Learning Algorithms to Quantify Wheat Characteristics in the Nile Delta Region of Egypt

Monitoring strategic agricultural crops in terms of crop growth performance, by accurate cost-effective and quick tools is crucially important in site-specific management to avoid crop reductions. The availability of commercial high resolution satellite images with high resolution (spatial and spectral) as well as in situ spectra measurements can help decision takers to have deep insight on crop stress in a certain region. The research attempts to examine remote sensing dataset for forecasting wheat crop (Sakha 61) characteristics including the leaf area index (LAI), plant height (plant-h), above ground biomass (AGB) and Soil Plant Analysis Development (SPAD) value of wheat across non-stress, drought and salinity-induced stress in the Nile Delta region. In this context, the ability of in situ spectroradiometry measurements and QuickBird high resolution images was evaluated in our research. The efficiency of Random Forest (RF) and Artificial Neural Network (ANN), mathematical models was assessed to estimate the four measured wheat characteristics based on vegetation spectral reflectance indices (V-SRIs) extracted from both approaches and their interactions. Field surveys were carried out to collect in situ spectroradiometry measurements concomitant with the acquisition of QuickBird imagery. The results demonstrated that several V-SRIs extracted from in situ spectroradiometry data and the QuickBird image correlated with the LAI, plant-h, AGB, and SPAD value of wheat crop across the study site. The determination coefficient (R2) values of the association between V-SRIs of in situ spectroradiometry data and various determined wheat characteristics varied from 0.26 to 0.85. The ANN-GSIs-3 was found to be the optimum predictive model, demonstrating a greater relationship between the advanced features and LAI. The three features of V-SRIs comprised in this model were strongly significant for the prediction of LAI. The attained results indicated high R2 values of 0.94 and 0.86 for the training and validation phases. The ANN-GSIs-3 model constructed for the determination of chlorophyll in the plant which had higher performance expectations (R2 = 0.96 and 0.92 for training and validation datasets, respectively). In conclusion, the results of our study revealed that high resolution remote sensing images such as QuickBird or similar imagery, and in situ spectroradiometry measurements have the feasibility of providing necessary crop monitoring data across non-stressed and stressed (drought and salinity) conditions when integrating V-SRIs with ANN and RF algorithms

Influence of Deficit Irrigation and Nitrogen Fertilization on Potato Yield, Water Productivity and Net Profit

Potato is described as a sensitive crop to short periods of irrigation deficit and Nitrogen deficiency.  Farmers usually use excessive amounts of irrigation water and fertilizers to obtain higher yields. Recently, there is a shortage of water resources and therefore it is fundamentally important to employ better irrigation and fertilization management of such crops. A field experiment was undertaken to assess the effects of irrigation regime and Nitrogen fertilization on potato tuber yield, Chlorophyll content and irrigation water productivity of potato crop. Four levels of applied water 1.25, 1.00, 0.75 and 0.50 of the crop evapotranspiration (ETc) were examined with three amounts of Nitrogen (N) 50, 125, and 200 kg ha-1.  The results clearly demonstrated a significant influence of both factors on potato yield. The highest potato yield of 29.3 Mg ha-1 was obtained with the treatment of 1.25 ETc and 200 kg N ha-1. Water productivity was conversely proportion with increasing amount of applied water since the highest average record of 27.2 kg m-3 obtained with lowest amount of applied water. The results further showed an inversely proportional between irrigation regime and water productivity which was reflected on the total profits.  Consequently, the results suggest that potato can be grown in arid and semi-arid environments with acceptable potato yield and quality while saving water and using Nitrogen fertilization more efficiently

Production of drip irrigated squash (Cucurbita Pepo, L.) under different levels of irrigation and uniformity

This study aimed to get the most possible benefit of using deficit irrigation to maximize water productivity of squash, besides investigating the ability of drip irrigation uniformity to reduce the effect of deficit irrigation on squash crop production (Cucurbita pepo - Hybrid Revera). Three levels of irrigation uniformity levels (UL) based on the value of uniformity coefficient (UC) namely excellent (E), very good (VG), and unacceptable (UA) were examined with three irrigation levels based on crop evapotranspiration (ETc) which were full irrigation (FI or 100% ETc) to be compared to two defecit irrigation levels 90% ETc (DI90), and 80% ETc (DI80). Results showed that both UL and DI had significant effect on squash production. There was significant reduction in production values due to the decrease in irrigation water  at all uniformity levels. The greatest value of water productivity (WP) for all UL was obtained at FI followed by DI80 and the least was DI90. The profits of water volume unit showed that the greatest values were for E level. FI recorded the greatest profits under all uniformity levels. Increasing uniformity level led to increase crop production but it could not prevent the significant reduction in squash crop related to defecit irrigation. It is recommended to manage drip irrigation uniformity and irrigation water separately as the high levels of uniformity could not prevent the effect of water shortage regarding the decrease crop production, WP, and profits

Engagement politique et Imaginaire romanesque chez Ahmadou Kourouma et Rachid Mimouni

This research, which unfolds in three stages, provides a reflection about the ideological, but also aesthetic dimension of postcolonial Francophone literature in sub-Saharan Africa and Maghreb. It aims precisely to show how a political and ideological discourse is linked up with a literary and aesthetic practice in the novels of the Ivorian Ahmadou Kourouma and the Algerian Rachid Mimouni. In the first two parts, we examine the different aspects of the political engagement of these two francophone writers belonging to different geographic, political social and cultural areas. It is precisely a question of staging their convictions and ideological positions expressed in the novels of the corpus about the phenomena of dictatorship, ideological drifts and war violence, which marked in Africa the period going from the first years of independence to the first decade of the 21st century. The last part aims at examining how poetics can provide suitable models for thinking politics at both writers. More precisely, studying the structures of narration at work in the novels of the corpus allows to highlight the aesthetic issues of their politically engaged writing which draws as much from the forms of the European novel as from African oral tradition.Cette recherche qui se déploie en trois parties constitue une réflexion sur la dimension idéologique, mais aussi esthétique de la littérature francophone postcoloniale en Afrique subsaharienne et au Maghreb. Elle vise précisément à montrer comment s’articulent dans l’œuvre romanesque de l’Ivoirien Ahmadou Kourouma et de l’Algérien Rachid Mimouni un discours politique et idéologique et une pratique littéraire et esthétique. Les deux premières parties sont consacrées à l’examen de différents aspects de l’engagement politique de ces deux auteurs francophones appartenant à des aires géographiques, politiques, sociales et culturelles différentes. Il s’agit précisément de mettre en lumière leurs convictions et prises de positions idéologiques exprimées dans les romans du corpus à propos des phénomènes de dictature, de dérives idéologiques et de violence guerrière, qui ont marqué en Afrique la période allant des premières années de l’indépendance jusqu’à la première décennie du XXIe siècle. Dans la dernière partie, il est question d’examiner comment la poétique peut proposer des modèles appropriés pour penser la politique chez les deux auteurs. Il s’agit précisément, par une étude des modes de narration à l’œuvre dans les romans du corpus, de montrer les enjeux esthétiques de leur écriture politiquement engagée qui s’inspire autant des formes du roman européen que de l’oralité africaine

Political Engagement and Fiction Writing at Rachid Mimouni and Ahmadou Kourouma

Cette recherche qui se déploie en trois parties constitue une réflexion sur la dimension idéologique, mais aussi esthétique de la littérature francophone postcoloniale en Afrique subsaharienne et au Maghreb. Elle vise précisément à montrer comment s’articulent dans l’œuvre romanesque de l’Ivoirien Ahmadou Kourouma et de l’Algérien Rachid Mimouni un discours politique et idéologique et une pratique littéraire et esthétique. Les deux premières parties sont consacrées à l’examen de différents aspects de l’engagement politique de ces deux auteurs francophones appartenant à des aires géographiques, politiques, sociales et culturelles différentes. Il s’agit précisément de mettre en lumière leurs convictions et prises de positions idéologiques exprimées dans les romans du corpus à propos des phénomènes de dictature, de dérives idéologiques et de violence guerrière, qui ont marqué en Afrique la période allant des premières années de l’indépendance jusqu’à la première décennie du XXIe siècle. Dans la dernière partie, il est question d’examiner comment la poétique peut proposer des modèles appropriés pour penser la politique chez les deux auteurs. Il s’agit précisément, par une étude des modes de narration à l’œuvre dans les romans du corpus, de montrer les enjeux esthétiques de leur écriture politiquement engagée qui s’inspire autant des formes du roman européen que de l’oralité africaine.This research, which unfolds in three stages, provides a reflection about the ideological, but also aesthetic dimension of postcolonial Francophone literature in sub-Saharan Africa and Maghreb. It aims precisely to show how a political and ideological discourse is linked up with a literary and aesthetic practice in the novels of the Ivorian Ahmadou Kourouma and the Algerian Rachid Mimouni. In the first two parts, we examine the different aspects of the political engagement of these two francophone writers belonging to different geographic, political social and cultural areas. It is precisely a question of staging their convictions and ideological positions expressed in the novels of the corpus about the phenomena of dictatorship, ideological drifts and war violence, which marked in Africa the period going from the first years of independence to the first decade of the 21st century. The last part aims at examining how poetics can provide suitable models for thinking politics at both writers. More precisely, studying the structures of narration at work in the novels of the corpus allows to highlight the aesthetic issues of their politically engaged writing which draws as much from the forms of the European novel as from African oral tradition

Estimation of maize properties and differentiating moisture and nitrogen deficiency stress via ground - Based remotely sensed data

Moisture and nitrogen deficiency are major determinant factors for cereal production in arid and semi arid environments. The ability to detect stress in crops at an early stage is crucially important if significant reductions in yield are to be averted. In this context, remotely sensed data has the possibility of providing a rapid and accurate tool for site specific management in cereal crop production. This research examined the potential of hyperspectral and broad band remote sensing for predicting maize properties under nitrogen and moisture induced stress. Spectra were collected from drip irrigated maize subjected to various rates of irrigation regimes and nitrogen fertilization. 60 spectral vegetation indices were derived and examined to predict maize yield and other properties. Highly significant correlations between maize crop properties and various vegetation indices were noticed. RVI and NDVI were found to be sensitive to maize grain yield in both tested seasons. Cred edge demonstrated the strongest significant correlations with maize yield. The correlations with grain yield were found to be strongest at the flowering stage. Penalized linear discriminant analysis (PLDA) showed the possibility to distinguish moisture and nitrogen deficiency stress spectrally. The implications of this work for the use of satellite based remote sensing in arid zone precision agriculture are discussed