Characterization of Diatraea saccharalis in Sugarcane (Saccharum officinarum) with Field Spectroradiometry

The incorporation of Remote Sensing (RS) in agronomy studies has increased over the last 10 years due to the development of sensors with better spectral and spatial resolutions, using the spectral information to describe the variation in space of vegetation or landscape [1], [2]. The use of RS is effective, fast, non-destructive, and accessible in operational and accurately; provides information of large areas during a growing season on numerous occasions to detect changes in physiological and biochemical processes of plants, even with water, nutritional or derived from pests, weeds and disease stress. Also identify species, determine the state of health and plant vigor, crop inventorying, analyzing the structure of the canopy, all in a wide range of scales. That is, the use of RS to optimize agricultural practices as a function of the spatial and temporal variability within fields, through methods capable of recovering with biophysical variables level accuracy canopy registered by the reflectance [3], [4]. 

The use of RS in agriculture has also specialized particularly hyperspectral, since the length of electromagnetic wave detail in terms of the specific position of the absorption bands, spectral form, spectral variability and similarity or differentiation is seen other vegetation [5]. These sensors, known as spectroradiometers field, are used to obtain spectral signatures in situ, that strengthen the quality of the spatial and temporal analysis; in these optoelectronic systems, the radiance received by the optical components is decomposed into a continuous band of hundreds, which offers a potential improvement in crop assessment [6]. The importance of these portable field sensors lies in the pure obtaining the spectral signature of the measured object, which can be correlated with data from satellite sensors, and if they are equal and simultaneous, you can generate a spectral labeling within the image systematization help automatic pixels from training to differentiate characteristics in crops of the same area [7]. The organization and integration of these firms may be based on the construction of spectral libraries that can account for the variability between plant species, and discrimination between healthy (or no apparent damage) and nutritional deficiencies vegetation. In this regard, [5] reported that there are few relevant studies on the development of spectral libraries for the differentiation of crops and their possible deficiencies and diseases. 

The use of RS in studies of sugarcane cultivation has been implemented in numerous ways, mainly because of the economic importance of culture and its spatial distribution is generally symmetrical and uniform. Some of the applications are classification and mapping of sugarcane, identification of phenological stages and growing degree days, discrimination of varieties, monitoring of irrigation and nutritional stress, detection of damage by insects and diseases, predicting yields and management of crop residues. In all cases, applications that have been implemented are aimed at increasing productivity (yields and crop quality) with reduced production costs for increasingly competitive markets [8], [9].

 According to [10] there are three types of limiting factors on productivity of sugarcane: physiological (phenology, canopy, cell characteristics), environmental (water CO2, radiance, climate, soil fertility.) and agronomic (weeds, pests, diseases, toxicity). Of these, the constraints that most affect productivity are those relating to edafoecological characteristics (32.2%) and management in the management of pests and diseases (20.3%) [11]. The latter process has affected crop cane sugar level vegetative stress, where the spectral response is caused by biochemical cellular level and sheet changes, which in turn have an influence on the pigment systems and content humidity. On the other hand, stress can cause changes in the structure of the coverage, the leaf area index (LAI) and biomass [12]. 

Detection of health of vegetation depends on the relationship between changes of intense red and infrared reflectance and absorption of photosynthetically active radiation (APAR) of the surface of the vegetation [13]. Damage caused by diseases and pests can be measured by changes in chlorophyll content of plants, which can be analyzed for changes in patterns of spectral images taken by satellites. These techniques using multispectral images to identify areas under stress. [14] and [15] they showed that the normalized difference vegetation index (NDVI) was the parameter that showed better correlation in evaluating the health status of crops. 

It is known that many diseases and pests cause changes in leaf pigments in the biochemical components and generate metabolic alterations in infected leaves [16]. These pathological conditions of the plant may influence their spectral characteristics of the leaf tissue and can be detected in the visible and / or near infrared (NIR) of the spectrum. In fact, the visible and infrared regions are known to provide the maximum of information on the level of physiological stress in plants [17]. Therefore, the difference in spectral reflectance between healthy (or without apparent damage) culture and one affected by a disease or pest, used to diagnose the health of the plant [18]. 

The study on the space-time reflectance variation of solar radiation in the visible bands, infrared and vegetation index are important approaches to analyze geographically related problems risk assessment of pest and disease incidence, spread and severity, as well as to support the activities of sampling and monitoring are carried out to protect the cultivation of sugarcane. Therefore, the aim of this study was to characterize the damage caused by Diatraea saccharalis through the analysis of spectral signatures using spectroradiometry field and satellite imagery, as an input in the early detection of the problem plant sugarcane in the Huasteca region, Mexico. The hypothesis raised refers to the use of remote sensing, both satellite and field can be important tools for recognition and characterization of damage caused by pests and diseases in sugarcane, becoming a Space input to help generate regional action plans for environmentally sustainable and more economical management, and enhancing decision-making field technicians. The use of these technologies has advantages in both research and the implementation of precision farming techniques, and while your applications continue to be studied in more developed countries, Mexico has not been able to establish a synergy with conventional jobs country. There disinterest in modeling sugarcane using active optical sensors, and sugarcane area Huasteca, not available a tool to characterize the problems associated with the production of sugar cane and has not generated a methodology remote sensing in order to establish spatial and quantitative aspects relevant as the area occupied by sugarcane cultivation, the productivity level areas supply the mills and farms, the estimated yield of sugarcane and recognition of pest or diseases.