**1. Introduction**

Precision agriculture, site-specific application of inputs tailored to the needs of the crop, is one of the new ways that modern agriculture could potentially maintain or enhance crop yields and minimize environmental pollution. Knowledge about variations in vegetation species and community distribution patterns, alterations in vegetation phenological cycles, and modifications in the plant physiology and morphology provide valuable insight into the climatic, edaphic, geologic, and geophysical characteristics of Earth's areas (Janetos & Justice, 2000). During the past decade remote sensing techniques have been widely used to monitor crops throughout their growing period to help in making decisions for good agricultural practices. Spectral remote sensing methods provide the possibility for early, efficient, objective, and non-destructive evaluation of plant responses to different stress factors of the environment (Campbell et al., 2007; Govender et al., 2009; Li et al., 2010). Field remote sensing applications addressed agriculture and forestry survey, fire detection and fire-fuel mapping, mineral mapping, and atmospheric modelling. Airborne, space-borne and hand-held technologies are commonly used to investigate the spectral responses of plants. Hyperspectral remote sensing makes possible to enhance significantly the spectral measurement capabilities over conventional remote sensing sensor systems, as well as to improve the spectral information content. This entails detailed assessment of the changes in the physiological stage of plants in response to the changes in the environment (Zarco-Tejada et al., 2002; Steele et al., 2008a), detecting of early-stage vegetation stress (Krezhova et al., 2005; Ouyang et al., 2007), discriminating land cover types (Flamenco-Sandoval et al., 2007), leaf pigment concentrations (Coops et al., 2003), modelling quantitative biophysical and yield characteristics of agricultural crops (Delalieux et al., 2009a; Chatzistathisa et al., 2011).

Ground-truth is essential for detecting plant stress, and two commonly used ground-based optical methods, leaf spectral reflectance and chlorophyll fluorescence, are reviewed for their usefulness and practical application. When these methods were combined with remarkable advances in Global Positioning System (GPS) receivers, geographic information systems (GIS), and enhanced crop simulation models, remote sensing technology has the potential to transform the ways that growers manage their lands and implement precision farming techniques (Upchurch, 2003; Hatfield, et al., 2008; Shuanggen & Komjathy, 2010). To obtain accurate and complementary comparative assessments for plant responses to the environmental changes, methods have been applied from different research fields - remote

Spectral Remote Sensing of the Responses of Soybean Plants to Environmental Stresses 217

solution and the nitrogen fixation process in the nodules is the main constraint the crop faces in terms of increasing N uptake when no other abiotic stress that reduces BNF activity occurs. A number of reviews have been published on BNF in legumes (Unkovich & Pate, 2000; Hardarson & Atkins, 2003) and soybean in particular (Hungria et al., 2005, Hungria et al., 2006). However, these summaries were mostly qualitative and did not emphasize the role of BNF and inherent soil fertility in high-yielding soybean systems. Likewise, many studies evaluating the response of soybean to N fertilization show conflicting results that make it difficult to draw a general conclusion about soybean response to N fertilizer (Ray et

In sustained agronomic systems, both the BNF and an adequate management of the organic matter, play important roles. However, the BNF importance as a source of N for agriculture has diminished in recent decades as increasing amounts of fertilizer N have been used for the production of food and cash crop. Currently, it's of great practical importance because the use of nitrogenous fertilizers has resulted in unacceptable levels of water pollution (increasing concentrations of toxic nitrates) and eutrophication of lakes and rivers (Barker & Sawyer, 2005; Salvagiotti et al., 2008). Thus, legumes are also essential to improve the soil fertility and quality of agricultural lands and to reclaim eroded or barren areas, making them crucial for agricultural and environmental sustainability (Saikia & Jain, 2007). However, legume BNF in crop species is very sensitive to environmental constraints such as salinity, drought, and light in particular (Ibanez et al., 2008; Salehi et al., 2008; USDA, 2009). Many fundamental studies are dedicated on how plants detect and respond to stresses in their environment. The stress factors cause changes in the normal physiological processes of all cultural and wild plants. They influence the metabolism, photosynthesis and enzyme activity, and lead to a dramatic reduction of yields and to deterioration of the output quality. The physiological condition of plants is indicative of plant productivity and adaptability to stress and it is a general indication of the environment in which they grow (Alia et al., 2006; Gray et al., 2010). Research on biotic stresses includes the molecular mechanisms used by viruses, bacteria, fungi, and nematodes to incite disease and those used by plants to resist infection (Li et al., 2008; Yang et al., 2009; 2008; Delalieux et al., 2009b). Research on abiotic stresses includes molecular mechanisms by which plants resist such unfavourable conditions as drought, flooding, chilling, light, excess salts, toxic metals, and

Soil salinity is one of the widespread environmental factors and the major factor limiting plant production in many areas of the world. This is especially true in arid and semi-arid regions of the world like some regions of Bulgaria. Salinity influences almost every aspect of the physiology and biochemistry of plants (Arida & Das, 2005). High exogenous salt concentrations affect seed germination, water deficit, cause ion imbalance of the cellular ions resulting in ion toxicity and osmotic stress (Yousfi et al., 2007; Singha et al., 2010). As with most cultivated crops, the salinity response of legumes varies greatly and depends on such factors as climatic conditions, soil properties and the stage of growth. One of the important impacts of salinity on plants is that it essentially creates a physiological drought in plants (Munns, 2002). The ability to monitor or evaluate the efficiency of cropping production systems in saline areas can be significantly improved by applying remote sensing

Light is one of the most important environmental factors regulating plant development and the expression of plant genes. A plant's ability to maximize its photosynthetic productivity depends on its capacity to sense, evaluate, and respond to light quality, quantity, and

pollutants (Flawers, 2004; Jones, 2007; El-Nahry & Hammad, 2009).

techniques (Thenkabail et al., 2004; Campbell et al., 2007).

al., 2005; Osborne & Riedell, 2011).

sensing, plant physiology, biochemistry, virology, etc. Early detection of stress could identify plant physiological condition at larger spatial and temporal scales before visible effects are apparent (Krezhova et al., 2009a; Chatzistathisa et al., 2011).

Soybean *(Glycine max L.)* is one of the most important and valuable agricultural species of legume, as its high protein content is of primary importance for human food and animal feed. Soybean is the leading oilseed crop produced and consumed worldwide. Fat-free soybean meal is a primary, low-cost, source of protein for animal feeds and most prepackaged meals, as well as a good source of protein for the human diet. The soy vegetable oil is another valuable product of processing the soybean crop and a biofuel feedstock (FAOSTAT, 2011).

Soybean yields have steadily increased in the past 30 years owing to a combination of genetic and management improvement. Rapid soybean demand increases in the last decade challenge the reliability of supply, stock levels, and reasonable pricing. In order to meet the demand, there are two alternatives: increase planted hectares or increase yield. Increasing soybean hectares by substituting for other crops (e.g. sunflower in Argentina or cotton in the United States), utilizing pasture (e.g. Santa Fe, Argentina or Mato Grosso, Brazil) or replacing native vegetation (e.g. cerrado in Brazil) has been the most expedient manner to increase soybean output (Masuda & Goldsmith, 2009). Going forward available farmland for soybean production will be limited by decreasing quantities of land not already in production, increased farmland loss for urbanization, heightened sensitivities about agricultural uses of land, and weak property rights in regions such as Africa that constrains the employment of modern agricultural methods (Goldsmith, 2008). Although soybean use for biodiesel production may require expansion of land area devoted to soybean in some parts of the world, such an expansion is not likely in Europe and North America. Hence, yield increases will become the major source for sustaining further increases in soybean production, particularly in these two significant regions of the world. The design of soil and crop management strategies that fully exploit the climatic and genetic yield potential of soybean remains a key challenge to achieve this goal (USDA, 2009).

Gene transformation and genetic engineering are likely to be of assistance in increasing crop yields worldwide, particularly in less-developed areas affected by low crop productivity and malnutrition. Crop transformations restricting the influence of biological pests could contribute to increased crop productivity (Miflin, 2000). Once pests are controlled, either using genetically improved plants or various management options, the further step could be to increase the inherent yielding capability of plants. Yield potential may be increased by improving of the overall physiological capacity of plants and by preventing the negative consequences of abiotic stresses. Increasing leaf photosynthetic rates appear to be a straightforward way of increasing crop yields. Considerable physiological research has been carried out to select and breed for genotypes with superior photosynthetic rates, and was successful in identifying such cultivars in maize, wheat and soybean (Masclaux et al., 2001; Habash et al., 2001; Sinclair et al., 2000). In soybean, the trait is inherited quantitatively (Sall & Sinclair, 1991).

To achieve high yield potential, soybean must sustain high photosynthesis rates and accumulate large amounts of nitrogen (N) in seeds. It exists in leaves primarily as ribulose biphosphate carboxylase/oxygenase and there is generally a strong relationship between N per unit leaf area and photosynthesis (Sinclair, 2004). Biological nitrogen fixation (BNF) and mineral soil or nitrogenous fertilizers are the main sources of meeting the N requirement of high-yielding soybeans. However, antagonism between nitrate concentration in the soil

sensing, plant physiology, biochemistry, virology, etc. Early detection of stress could identify plant physiological condition at larger spatial and temporal scales before visible

Soybean *(Glycine max L.)* is one of the most important and valuable agricultural species of legume, as its high protein content is of primary importance for human food and animal feed. Soybean is the leading oilseed crop produced and consumed worldwide. Fat-free soybean meal is a primary, low-cost, source of protein for animal feeds and most prepackaged meals, as well as a good source of protein for the human diet. The soy vegetable oil is another valuable product of processing the soybean crop and a biofuel feedstock

Soybean yields have steadily increased in the past 30 years owing to a combination of genetic and management improvement. Rapid soybean demand increases in the last decade challenge the reliability of supply, stock levels, and reasonable pricing. In order to meet the demand, there are two alternatives: increase planted hectares or increase yield. Increasing soybean hectares by substituting for other crops (e.g. sunflower in Argentina or cotton in the United States), utilizing pasture (e.g. Santa Fe, Argentina or Mato Grosso, Brazil) or replacing native vegetation (e.g. cerrado in Brazil) has been the most expedient manner to increase soybean output (Masuda & Goldsmith, 2009). Going forward available farmland for soybean production will be limited by decreasing quantities of land not already in production, increased farmland loss for urbanization, heightened sensitivities about agricultural uses of land, and weak property rights in regions such as Africa that constrains the employment of modern agricultural methods (Goldsmith, 2008). Although soybean use for biodiesel production may require expansion of land area devoted to soybean in some parts of the world, such an expansion is not likely in Europe and North America. Hence, yield increases will become the major source for sustaining further increases in soybean production, particularly in these two significant regions of the world. The design of soil and crop management strategies that fully exploit the climatic and genetic yield potential of

Gene transformation and genetic engineering are likely to be of assistance in increasing crop yields worldwide, particularly in less-developed areas affected by low crop productivity and malnutrition. Crop transformations restricting the influence of biological pests could contribute to increased crop productivity (Miflin, 2000). Once pests are controlled, either using genetically improved plants or various management options, the further step could be to increase the inherent yielding capability of plants. Yield potential may be increased by improving of the overall physiological capacity of plants and by preventing the negative consequences of abiotic stresses. Increasing leaf photosynthetic rates appear to be a straightforward way of increasing crop yields. Considerable physiological research has been carried out to select and breed for genotypes with superior photosynthetic rates, and was successful in identifying such cultivars in maize, wheat and soybean (Masclaux et al., 2001; Habash et al., 2001; Sinclair et al., 2000). In soybean, the trait is inherited quantitatively (Sall

To achieve high yield potential, soybean must sustain high photosynthesis rates and accumulate large amounts of nitrogen (N) in seeds. It exists in leaves primarily as ribulose biphosphate carboxylase/oxygenase and there is generally a strong relationship between N per unit leaf area and photosynthesis (Sinclair, 2004). Biological nitrogen fixation (BNF) and mineral soil or nitrogenous fertilizers are the main sources of meeting the N requirement of high-yielding soybeans. However, antagonism between nitrate concentration in the soil

effects are apparent (Krezhova et al., 2009a; Chatzistathisa et al., 2011).

soybean remains a key challenge to achieve this goal (USDA, 2009).

(FAOSTAT, 2011).

& Sinclair, 1991).

solution and the nitrogen fixation process in the nodules is the main constraint the crop faces in terms of increasing N uptake when no other abiotic stress that reduces BNF activity occurs. A number of reviews have been published on BNF in legumes (Unkovich & Pate, 2000; Hardarson & Atkins, 2003) and soybean in particular (Hungria et al., 2005, Hungria et al., 2006). However, these summaries were mostly qualitative and did not emphasize the role of BNF and inherent soil fertility in high-yielding soybean systems. Likewise, many studies evaluating the response of soybean to N fertilization show conflicting results that make it difficult to draw a general conclusion about soybean response to N fertilizer (Ray et al., 2005; Osborne & Riedell, 2011).

In sustained agronomic systems, both the BNF and an adequate management of the organic matter, play important roles. However, the BNF importance as a source of N for agriculture has diminished in recent decades as increasing amounts of fertilizer N have been used for the production of food and cash crop. Currently, it's of great practical importance because the use of nitrogenous fertilizers has resulted in unacceptable levels of water pollution (increasing concentrations of toxic nitrates) and eutrophication of lakes and rivers (Barker & Sawyer, 2005; Salvagiotti et al., 2008). Thus, legumes are also essential to improve the soil fertility and quality of agricultural lands and to reclaim eroded or barren areas, making them crucial for agricultural and environmental sustainability (Saikia & Jain, 2007). However, legume BNF in crop species is very sensitive to environmental constraints such as salinity, drought, and light in particular (Ibanez et al., 2008; Salehi et al., 2008; USDA, 2009).

Many fundamental studies are dedicated on how plants detect and respond to stresses in their environment. The stress factors cause changes in the normal physiological processes of all cultural and wild plants. They influence the metabolism, photosynthesis and enzyme activity, and lead to a dramatic reduction of yields and to deterioration of the output quality. The physiological condition of plants is indicative of plant productivity and adaptability to stress and it is a general indication of the environment in which they grow (Alia et al., 2006; Gray et al., 2010). Research on biotic stresses includes the molecular mechanisms used by viruses, bacteria, fungi, and nematodes to incite disease and those used by plants to resist infection (Li et al., 2008; Yang et al., 2009; 2008; Delalieux et al., 2009b). Research on abiotic stresses includes molecular mechanisms by which plants resist such unfavourable conditions as drought, flooding, chilling, light, excess salts, toxic metals, and pollutants (Flawers, 2004; Jones, 2007; El-Nahry & Hammad, 2009).

Soil salinity is one of the widespread environmental factors and the major factor limiting plant production in many areas of the world. This is especially true in arid and semi-arid regions of the world like some regions of Bulgaria. Salinity influences almost every aspect of the physiology and biochemistry of plants (Arida & Das, 2005). High exogenous salt concentrations affect seed germination, water deficit, cause ion imbalance of the cellular ions resulting in ion toxicity and osmotic stress (Yousfi et al., 2007; Singha et al., 2010). As with most cultivated crops, the salinity response of legumes varies greatly and depends on such factors as climatic conditions, soil properties and the stage of growth. One of the important impacts of salinity on plants is that it essentially creates a physiological drought in plants (Munns, 2002). The ability to monitor or evaluate the efficiency of cropping production systems in saline areas can be significantly improved by applying remote sensing techniques (Thenkabail et al., 2004; Campbell et al., 2007).

Light is one of the most important environmental factors regulating plant development and the expression of plant genes. A plant's ability to maximize its photosynthetic productivity depends on its capacity to sense, evaluate, and respond to light quality, quantity, and

Spectral Remote Sensing of the Responses of Soybean Plants to Environmental Stresses 219

response of a target. The variety of earth's surface materials is enormous, and therefore the recording of their spectral signatures (also known as spectral library) requires substantial financial and time investments. With the development of hyperspectral technology, the spectral resolution of hyperspectral sensors have reached less than 10 nm, which is sufficient for creating a continuous spectral curve from 350-2500 nm to detect subtle changes in the spectral behaviour of the earth objects. For years, efforts have been made to establish such datasets and pool them for general use through spectral libraries. Such spectral libraries are maintained by many organizations including the Johns Hopkins University (JHU), the Jet Propulsion Laboratory (JPL), and the United States Geological Survey (USGS). Many of these datasets are made available with commercial remote sensing image processing

Methods based on reflectance makes use of VIS, near infrared (NIR), and short-wave infrared (SWIR) sensors to form images of the earth's surface by detecting the solar radiation reflected from targets on the ground. These methods rely on making measurements simultaneously in one or more wavebands. Spectrophotometers offer the simplest solution for spectral reflectance measurements. They measure spectrum of light reflected from the whole (mostly circular) field of view of the instrument but not provide any spatial information on the pattern of reflection (West et al., 2003). Earlier studies utilized multispectral sensors with low spatial (60 m to 80 m) and spectral resolution commonly collected in four to seven spectral bands in the VIS and NIR regions. Spectral resolution refers to the number and width of the portions of the electromagnetic spectrum measured by the sensor. A sensor may be sensitive to a large portion of the electromagnetic spectrum but have poor spectral resolution if it captures a small number of wide bands. Spatial resolution defines the level of spatial detail depicted in an image and it is directly related to image pixel size. The spatial property of an image is a function of the design of the sensor in terms of its field of view and the altitude at which it operates above the surface (Smith, 2001a). Early airborne systems included a multispectral camera mounted on board a light aircraft. Spectrometers at this time were bulky, heavy instruments which were not easily

transportable in the field and most measurements were taken in laboratories.

selection, data acquisition procedures and the cost factor.

Remote sensing technologies have advanced significantly over the past 10 to 15 years. With the development of hyperspectral remote sensing technologies, researchers have benefited from significant improvements in the spectral and spatial properties of the data, allowing for more detailed plant and environmental studies (Thenkabail et al., 2004; Blackburn, 2007). These technologies acquire many hundreds of spectral bands across the VIS, NIR, and midinfrared portions of the electromagnetic spectrum from 350 nm to 2500 nm, using satellite, airborne or hand-held devices. Advances in spectrometry and information technologies have resulted in state-of-the-art portable field instruments which allow for the collection of hand-held hyperspectral signatures. There are certain problems in the area of hyperspectral analysis connected with the optimal selection of bandwidth, number of bands and spatial as well as spectral resolutions and some constraints like data storage, communication bandwidth, discrimination/classification accuracy, minimum signal-to-noise ratio, sensor

The spectral reflectance responses are affected by factors such as soil nutrient status, the growth stage of the vegetation, the colour of the soil (which may be affected by recent weather conditions). In some instances, the nature of the interaction between incident

software packages.

**2.1 Spectral reflectance** 

direction. Stratospheric ozone depletion has led to elevated levels of ultraviolet-B (UV-B) radiation (280-320 nm) on the surface of the Earth. Increased UV-B levels have negative effects on human health (Norval et al., 2006) as well as on the plant development, morphology, and physiology (Jia Gio & Wang, 2008). Low influence UV-B radiation stimulates distinct responses, such as the accumulation of UV-absorbing pigments. Low influence of UV-B was also found to stimulate the transcript levels of a robust set of genes involved in stress responses (Rock, 2000). Although the effects of UV-B on plants are well characterized at the physiological level, little is known about the effects of UV-B on underground (root) physiology, particularly in interaction with other environmental factors. An increasing number of studies have been designed to test the interactions of environmental factors on plants, such as the interaction between UV-B and water stress (Cechin et al., 2008), interaction between salinity and Fe deficiency (Zancan et al., 2006), and interaction between UV-B radiation and Fe deficiency (Zancan et al., 2008).

The aim of this chapter is to show some aspects of the recent applications of non-destructive remote sensing techniques, hyperspectral leaf reflectance and chlorophyll fluorescence, for detection and discrimination of the effects of some environmental stresses (salinity and enhanced UV-B radiation) on young soybean plants, as well as the influence of the biological nitrogen fixation on the spectral responses of the plants to stress. To evaluate the effects of a given stress a comparative analysis was performed between the changes of the leaf spectral reflectance and fluorescence data and the stress markers such as phenols, malondialdehyde, thiol groups, proline and hydrogen peroxide, and chlorophyll content that were estimated by biochemical methods.
