S.V. Archontoulis

Leaf photosynthesis and respiration of three bioenergy crops in relation to temperature and leaf nitrogen: how conserved are biochemical model parameters among crop species?

Given the need for parallel increases in food and energy production from crops in the context of global change, crop simulation models and data sets to feed these models with photosynthesis and respiration parameters are increasingly important. This study provides information on photosynthesis and respiration for three energy crops (sunflower, kenaf, and cynara), reviews relevant information for five other crops (wheat, barley, cotton, tobacco, and grape), and assesses how conserved photosynthesis parameters are among crops. Using large data sets and optimization techniques, the C3 leaf photosynthesis model of Farquhar, von Caemmerer, and Berry (FvCB) and an empirical night respiration model for tested energy crops accounting for effects of temperature and leaf nitrogen were parameterized. Instead of the common approach of using information on net photosynthesis response to CO2 at the stomatal cavity (An–Ci), the model was parameterized by analysing the photosynthesis response to incident light intensity (An–Iinc). Convincing evidence is provided that the maximum Rubisco carboxylation rate or the maximum electron transport rate was very similar whether derived from An–Ci or from An–Iinc data sets. Parameters characterizing Rubisco limitation, electron transport limitation, the degree to which light inhibits leaf respiration, night respiration, and the minimum leaf nitrogen required for photosynthesis were then determined. Model predictions were validated against independent sets. Only a few FvCB parameters were conserved among crop species, thus species-specific FvCB model parameters are needed for crop modelling. Therefore, information from readily available but underexplored An–Iinc data should be re-analysed, thereby expanding the potential of combining classical photosynthetic data and the biochemical model.

Inflorescence characteristics, seed composition, and allometric relationships predicting seed yields in the biomass crop Cynara cardunculus

Cynara (Cynara cardunculus) is a perennial C3 herb that has its potential as bioenergy crop. This paper aims (a) to derive empirical relationships to predict cynara seed yield per head and per unit area, avoiding laborious extraction of seeds from the complex structure of its inflorescences; (b) to determine the head‐weight distribution per unit area, the seed composition and the oil profile of cynara seeds; and (c) to estimate the range of cynara biomass, seed and oil yield in representative parts of Greece. We analyzed 16 field experiments, varying in crop age and environmental conditions in Greece. Seed yield per head (SYhead) can be accurately predicted as a linear function of dry head weight (Hw): SYhead=0.429·Hw−2.9 (r2=0.96; n=617). Based on this relationship, we developed a simple two‐parameter equation to predict seed yield per unit area (SY): SY=HN·(0.429·μ−2.9), where μ is the mean head weight (g head−1) and HN is the total number of heads per unit area, respectively. The models were tested against current and published data (n=180 for head‐level; n=35 for unit area‐level models), and proved to be valid under diverse management and environmental conditions. Attainable cynara seed yields ranged from 190 to 480 g m−2 yr−1, on dry soils and on aquic soils (shallow ground water level). This variation in seed yield was sufficiently explained by the analyses of head‐weight distribution per unit area (small, medium and large heads) and variability of seed/head weight ratio at head level. Seed oil concentration (average: 23%) and crude protein concentration (average: 18.7%) were rather invariant across different seed sizes (range: 26–56 mg seed−1) and growing environments.