Physiology of yield determination in chickpea (Cicer arietinum L.): critical period for yield determination, patterns of environmental stress, competitive ability and stress adaptation

Abstract

Average global chickpea yields are low ( < 1.0 t ha⁻¹), due mainly to a lack of adaptation, particularly to abiotic stresses such as water and temperature. To help address this we conducted five experiments to: (i) determine the critical period for yield determination as background for adaptation to stress; (ii) quantitatively characterise the Australian cropping environment for water and temperature stress and (iii, iv and v) evaluate the association of secondary traits with improved yield and reliability. Research used a set of 20 chickpea lines (fifteen Desi and five Kabuli) chosen for their variability. Experiments were conducted at Roseworthy (34◦52’S, 138◦69’E) and Turretfield (34◦33’S, 138◦49’E) South Australia from 2013 to 2015. All research uses cumulative thermal time or degree days (oCd) to quantify and measure phenology, based on the sum of mean diurnal temperature minus a species specific critical or base temperature. (i) The critical period for yield determination was determined using successive 14-day shade treatments to stress chickpea across the growing season and determine the period of greatest sensitivity. The critical period was found to be similar to field pea and lupin but later than cereals; it was 800 oCd long with the most critical point being 100 – 200 oCd after flowering where yield loss reached up to 70 percent (Chapter 2). (ii) Real yield, weather data, and modelled water stress were used to determine the major types, frequency and distribution of water and temperature stress patterns in the Australian chickpea growing regions (Chapter 3). Three dominant patterns of maximum and minimum temperature and four dominant patterns of water stress were identified. The most frequently occurring temperature environments were associated with the lowest yield, while the most frequently occurring water stress environment types were associated with the second lowest yield. (iii) To determine the relationship between intragenotypic competitive ability and yield, comparisons were made between normal and relaxed density regions of the crop; the associated difference for trait values was considered the response to competition (Chapter 4). A significant negative association between competitive ability and yield was established. Wrights fixation index (Fst) genome scan revealed different genomic regions associated with yield under relaxed and normal competition and identified 14 regions that were implicated in response to competition of yield, seed number and biomass. (iv) We used normalised difference vegetative index (NDVI) with biomass calibration to measure crop growth rate and determine its association with yield. A significant linear relationship was established from 300 oCd before until 200 oCd after flowering (Chapter 5) indicating a tight coupling between crop growth and yield; the relationship was stronger under water stress. (v) To further investigate the drivers of crop growth, relationships between yield, radiation interception (PARint) and use efficiency (RUE) were established (Chapter 6). Yield was associated with seasonal, preflowering, post-flowering PARint across crops and with seasonal and after flowering PARint in the irrigated crops. Yield was positively associated with seasonal and after flowering RUE across crops, all stages in irrigated crops and with seasonal RUE in water stressed crops. The knowledge on the critical period (Chapter 2), and quantitative environmental characterisation (Chapter 3) coupled with the association of yield with secondary traits (Chapters 4 - 6) provide a platform for enhanced agronomy and breeding for the advancement of chickpea adaptation.