GCB Bioenergy (Jul 2021)
Physiological analysis of growth and development of winter carinata (Brassica carinata A. Braun)
Abstract
Abstract Brassica carinata is a non‐food, low‐carbon, none‐to‐low indirect land‐use change impact oilseed feedstock grown for sustainable biofuels, bioproducts, and high protein seed meal. Understanding carinata growth and development is critical to the development of best management practices for maximum productivity and profitability of double‐cropped farming systems. Field experiments were conducted during 2017–2018 (Year 1) and 2018–2019 (Year 2) winter–spring growing seasons in Quincy, Florida, to quantify the total aboveground dry matter accumulation (TDM), allocation, growth, nutrient uptake, and seed quality. The two carinata cultivars Avanza 641 and AX17012 accumulated 10826 and 9343 kg TDM ha−1 in Year 1 and 9655 and 10,642 kg TDM ha−1 in Year 2, respectively, at harvest maturity. The proportion of DM in the vegetative parts such as leaves and stems decreased, and the DM in reproductive structures such as silique walls and seeds increased with maturity. Seed yield (SY) was similar between cultivars but differed between years with Year 1 (2732 kg ha−1), producing 29% greater SY than Year 2 (1929 kg ha−1). Carinata primary stem has 17–20 leaf nodes, with 75%–88% of the axillary meristems producing primary and secondary branches. Crop growth rate (CGR) increased from vegetative to pod development for both cultivars in Year 1, while in Year 2, AX17012 and Avanza 641 attained maximum CGR at the pod development and bolting/flowering stages, respectively. Maximum seasonal nutrient uptake in leaves, stems, and siliques generally occurred in the early, mid, and late season, respectively, in both years. Seed weight, oil, monounsaturated fatty acids, C18:3, C20:1, and C22:1 concentrations increased with plant age, whereas protein, glucosinolate, polyunsaturated fatty acids, saturated fatty acids, C18:1, and C18:2 concentrations decreased with plant maturity. These results can be used for crop modeling to predict growth, development, and yield and aid in developing in‐season decision support tools.
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