Interactions between the grasses Phalaris arundinacea, Miscanthus sinensis and Echinochloa crus-galli, and barley and cereal yellow dwarf virusus

The grass species Miscanthus sinensis, Echinochloa crus-galli and Phalaris arundinacea may be useful biomass crops. In glasshouse inoculations with two isolates of Barley yellow dwarf virus (BYDV)-MAV and BYDV-PAV and one of Cereal yellow dwarf virus (CYVD)-RPV , E. crus galli was infected by all three virus isolates, P. arundinacea by BYDV-MAV and CYDV-RPV, but M. sinensis only by BYDV-MAV. All three hosts became very difficult to infect after several weeks’ growth. Symptoms were inconspicuous; dry matter yield losses ranged from c. 20–40%. Aphids acquired all three virus isolates from E. crus-galli, but more efficiently from 5 than 26-week-old plants. Only BYDV-MAV was acquired from P. arundinacea and M. sinensis. Plants of each species and of Avena sativa were grown outdoors between May and July in 1994 and 1995. Young plants of each species were exposed for successive 2-week intervals during the same periods. Vector populations were higher on A. sativa and P. arundinacea than on E. crus-galli and M. sinensis, and more plants of these species became infected. In 1994 only BYDV-MAV was detected. In 1995 BYDV-MAV, BYDV-PAV and CYDV-RPV were all detected; BYDV-MAV was again the virus isolate most frequently found.

Prediction of moisture, calorific value, ash and carbon content of two dedicated bioenergy crops using near-infrared spectroscopy

The potential of near infrared spectroscopy in conjunction with partial least squares regression to predict Miscanthus xgiganteus and short rotation coppice willow quality indices was examined. Moisture, calorific value, ash and carbon content were predicted with a root mean square error of cross validation of 0.90% (R2 = 0.99), 0.13 MJ/kg (R2 = 0.99), 0.42% (R2 = 0.58), and 0.57% (R2 = 0.88), respectively. The moisture and calorific value prediction models had excellent accuracy while the carbon and ash models were fair and poor, respectively. The results indicate that near infrared spectroscopy has the potential to predict quality indices of dedicated energy crops, however the models must be further validated on a wider range of samples prior to implementation. The utilization of such models would assist in the optimal use of the feedstock based on its biomass properties.