Retrieving the Bioenergy Potential from Maize Crops Using Hyperspectral Remote Sensing

Abstract

Biogas production from energy crops by anaerobic digestion is becoming increasingly important. The amount of biogas that can be produced per unit of biomass is referred to as the biomethane potential (BMP). For energy crops, the BMP varies among varieties and with crop state during the vegetation period. Traditional ways of analytical BMP determination are based on fermentation trials and require a minimum of 30 days. Here, we present a faster method for BMP retrievals using near infrared spectroscopy and partial least square regression (PLSR). PLSR prediction models were developed based on two different sets of spectral reflectance data: (i) laboratory spectra of silage samples and (ii) airborne imaging spectra (HyMap) of maize canopies under field (in situ) conditions. Biomass was sampled from 35 plots covering different maize varieties and the BMP was determined as BMP per mass (BMP FM , Nm 3 biogas/t fresh matter (Nm 3 /t FM)) and BMP per area (BMP area , Nm 3 biogas/ha (Nm 3 /ha)). We found that BMP FM significantly differs among maize varieties; it could be well retrieved from silage samples in the laboratory approach (R cv 2 = 0.82, n = 35), especially at levels >190 Nm 3 /t. In the in situ approach PLSR prediction quality declined (R cv 2 = 0.50, n = 20). BMP area , on the other hand, was found to be strongly correlated with total biomass, but could not be satisfactorily predicted using airborne HyMap imaging data and PLSR.

Quantifying the Robustness of Vegetation Indices through Global Sensitivity Analysis of Homogeneous and Forest Leaf-Canopy Radiative Transfer Models

“…Characteristics are available in Table 1. Despite the number of missions currently under development, the choice of the EnMAP sensor is due to the large amount of information available from a wide variety of articles [67][68][69][70][71][72][73], in addition to all the possibilities offered by its large number of bands. Although this mission has not been launched yet, it is of interest to analyze the sensitivity of EnMAP-suited VIs in preparation of future vegetation monitoring applications.…”

Spectroscopic Determination of Aboveground Biomass in Grasslands Using Spectral Transformations, Support Vector Machine and Partial Least Squares Regression

“…Aboveground biomass (AGB) can be defined in terms of fresh matter weight or dry matter weight, these two variables being strongly related, as well as water content [2]. The possibility of estimating the vegetation biomass and its modelling can aid in crop and bioenergy management [3], regarding the estimation of the yield and the management of its residuals [4]. It is also crucial due to its direct relationship with carbon and the holistic study of these systems as carbon sinks [5].…”

Advances in Remote Sensing of Agriculture: Context Description, Existing Operational Monitoring Systems and Major Information Needs

“…The whole system is still very dynamic [30,37]. The paper of Udelhoven et al (this issue) [38] exemplifies how remote sensing can be used to map the bioenergy potential of maize crops. Rangeland identification and monitoring is, for example, described in [39].…”

“…The challenge will be to integrate the above mentioned indicators so that complementary information can be derived. Although the described examples were mostly based on globally available (medium to coarse resolution) data sets, it is clear that additional information at high spatial resolution is available and should be integrated (plus ground sensors) (see for example [14,15,38,[43][44][45]47] in this special issue). Thus, besides investments in the agricultural sector, the related monitoring components should be strengthened.…”