Modelling phenology to probe for trade-offs between frost and heat risk in lentil and faba bean

Lake, Lachlan; Chauhan, Y. S.; Ojeda, Jonathan J.; Cossani, C. Mariano; Thomas, Damon; Hayman, Peter; Sadras, Víctor O.

doi:10.1016/j.eja.2020.126154

Cited by 21 publications

(19 citation statements)

References 78 publications

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“…The use of crop models in conjunction with field experiments can improve the understanding of crop yield limitations, identification of genotypes better adapted to T C = 42.823 + 0.579 × Latitude − 0.105 × Longitude their environment, identify gaps in model functions, and improve current forecasting methods to better account for genotype-by-environment interactions and extreme events (Chauhan et al 2017;Lake et al 2021). Prior to our study, the APSIM-chickpea model was calibrated and validated for the historical chickpea cultivar (cv.…”

Section: Discussionmentioning

confidence: 99%

“…If chickpeas experience daytime temperatures below 20 °C and/or night temperatures below 10 °C, then floral abortion may still occur, along with poor pod-filling. Therefore, a combination of these environmental conditions will lead to reduced grain yield if the plant cannot compensate for fewer seeds by increasing seed weight (Srinivasan et al 1998;Clarke and Siddique 2004;Nayyar et al 2005;Kumar et al 2010). These temperature thresholds are problematic not just in Australia but also in other chickpea growing regions, including northern India (Clarke and Siddique 2004;Nayyar et al 2005).…”

Section: Introductionmentioning

confidence: 99%

“…The reproductive phase is sensitive to abiotic stresses, including cold and is crucial in determining the adaptation of various crops, including pulses, to diverse environmental conditions (Lake et al 2021). In addition to extreme temperatures, the soil water status of the crop is known to affect flowering time (Richards et al 2020) significantly, and this parameter is now included in the latest version of APSIM for chickpeas (Classic version 7.10).…”

Section: Introductionmentioning

confidence: 99%

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Modelling the effects of cold temperature during the reproductive stage on the yield of chickpea (Cicer arietinum L.)

Anwar

Luckett

Chauhan³

et al. 2021

Int J Biometeorol

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During the reproductive stage, chilling temperatures and frost reduce the yield of chickpea and limit its adaptation. The adverse effects of chilling temperature and frost in terms of the threshold temperatures, impact of cold duration, and genotype-by-environment-by-management interactions are not well quantified. Crop growth models that predict flowering time and yield under diverse climates can identify combinations of cultivars and sowing time to reduce frost risk in target environments. The Agricultural Production Systems Simulator (APSIM-chickpea) model uses daily temperatures to model basic crop growth but does not include penalties for either frost damage or cold temperatures during flowering and podding stages. Regression analysis overcame this limitation of the model for chickpea crops grown at 95 locations in Australia using 70 years of historic data incorporating three cultivars and three sowing times (early, mid, and late). We modified model parameters to include the effect of soil water on thermal time calculations, which significantly improved the prediction of flowering time. Simulated data, and data from field experiments grown in Australia (2013 to 2019), showed robust predictions for flowering time (n = 29; R2 = 0.97), and grain yield (n = 22; R2 = 0.63–0.70). In addition, we identified threshold cold temperatures that significantly affected predicted yield, and combinations of locations, variety, and sowing time where the overlap between peak cold temperatures and peak flowering was minimal. Our results showed that frost and/or cold temperature–induced yield losses are a major limitation in some unexpected Australian locations, e.g., inland, subtropical latitudes in Queensland. Intermediate sowing maximise yield, as it avoids cold temperature, late heat, and drought stresses potentially limiting yield in early and late sowing respectively.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modelling the effects of cold temperature during the reproductive stage on the yield of chickpea (Cicer arietinum L.)

Anwar

Luckett

Chauhan³

et al. 2021

Int J Biometeorol

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“…Successfully combining these traits may provide genetic gains in yield with less risk of a trade-off between yield in high- and low-yielding environments. Selection for early flowering is desirable in shorter Mediterranean environments, but there is a limit to how far flowering can be advanced against frost risk in the target population of environments ( Lake et al, 2021 ). A longer flowering window can offset yield losses from limited frosts, but regular frosts may be more problematic, particularly in shorter seasons.…”

Section: Discussionmentioning

confidence: 99%

“…Most of the Australian lentil is grown in the medium rainfall areas (350–450 mm year –1 ) of southern Australia, in particular, the sandy loam soils in South Australia and the alkaline gray cracking clays of Victoria. These regions feature winter-dominant rainfall, with a combination of drought, frost, and heat restricting the yield of pulses ( Sadras et al, 2012 ; Lake et al, 2016 , 2021 ). Supported by better agronomy ( Llewellyn et al, 2012 ), pulses in the Mallee have increased from 7% in 2006 to 24% in 2017; this increase was at the expense of fallow, which declined from 18 to 2%, and pasture, which declined from 18 to 12% ( Moodie and Brand, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Australian Lentil Breeding Between 1988 and 2019 Has Delivered Greater Yield Gain Under Stress Than Under High-Yield Conditions

2021

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The contemporary lentil (Lens culinaris ssp. culinaris) industry in Australia started in the late 1980s. Yield in farmers’ fields averages 1.2 t ha–1 nationally and has not increased over three decades. Lack of yield progress can be related to a number of non-mutually exclusive reasons: expansion of lentil to low-yielding environments, lack of genetic gain in yield, lack of progress in agronomic practices, and lack of adoption of superior technologies. The aims of this study were to (i) quantify the genetic gain in lentil yield since 1988, (ii) explore the variation in the expression of genetic gain with the environment, and (iii) identify shifts in crop phenotype associated with selection for yield and agronomic adaptation. We grew a historic collection of 19 varieties released between 1988 and 2019 in eight environments resulting from the factorial combination of two sowing dates, two water regimes, and two seasons. Across environments, yield varied 11-fold from 0.2 to 2.2 t ha–1. The rate of genetic gain averaged 20 kg ha–1 year–1 or 1.23% year–1 across environments and was higher in low-yield environments. The yield increase was associated with substantial shifts in phenology. Newer varieties had a shorter time to flowering and pod emergence, and the rate of change in these traits was more pronounced in slow-developing environments (e.g., earlier sowing). Thermal time from sowing to end of flowering and maturity were shorter in newer varieties, and thermal time from pod emergence to maturity was longer in newer varieties; the rate of change in these traits was unrelated to developmental drivers and correlated with environmental mean yield. Genetic gain in yield was associated with increased grain number and increased harvest index. Despite their shorter time to maturity, newer varieties had similar or higher biomass than their older counterparts because crop growth rate during the critical period increased with the year of release. Genotype-dependent yield increased over three decades in low-yield environments, whereas actual farm yield has been stagnant; this suggests an increasing yield gap requiring agronomic solutions. Genetic improvement in high-yield environments requires improved coupling of growth and reproduction.

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Frost risk in canola and carinata as a function of sowing date in the agricultural central region of South America

Verocai¹,

Castro

Manasliski³

et al. 2022

Agronomy Journal

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Crop cycles in spring canola (Brassica napus L.) and carinata (Brassica carinata A. Braun) are controlled by temperature and photoperiod. In the central region of South America, which accounts for 90% of South American rapeseed crop production, farmers seek to sow as early as possible to maximize yield even though early sowing dates expose crops to a higher probability of frost occurrence that had not been quantified before. Our objective was to model phenology for one spring cultivar of canola ('Rivette') and one of carinata ('Avanza 641') and assess the probability of frost occurrence during flowering and grain filling in the central region of South America. For the estimation of frost risk, we modeled phenology resulting from 15 April to 15 August sowing dates at 12 locations (from 31.16˚to 34.20˚S latitude). We assumed that the critical period spans from 100 to 500 growing degree days (GDD) after flowering. Under early sowing dates, carinata tends to have a longer cycle (200 GDD more than canola) although both crops had a similar cycle length under a late sowing date. Predicted and observed flowering dates showed an average difference of 1.6 and 0.95 d for canola and carinata, respectively. Carinata has a lower probability of suffering frost events, and early sowing dates result in a greater exposure to frost damage. The results of this work will enable farmers and stakeholders to know the potential frost risk when defining a sowing date for canola and carinata. INTRODUCTIONRapeseed crops are among the most important commodities, with an annual worldwide production of 723 million t in 2019-2020. Rapeseed ranks fourth among the most important oilseed crops produced globally, accounting for 6% of a world oil crop market largely led by oil palm (Elaeis guineensis Jacq.) and soybean [Glycine max (L.) Merr.] (FAOSTAT, 2020). Rapeseeds include canola (Brassica napus L.), an edible oil crop with low erucic acid and glucosinolates content Abbreviations: CCC, concordance correlation coefficient; GDD, growing degree days.

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Modelling phenology to probe for trade-offs between frost and heat risk in lentil and faba bean

Cited by 21 publications

References 78 publications

Modelling the effects of cold temperature during the reproductive stage on the yield of chickpea (Cicer arietinum L.)

Modelling the effects of cold temperature during the reproductive stage on the yield of chickpea (Cicer arietinum L.)

Australian Lentil Breeding Between 1988 and 2019 Has Delivered Greater Yield Gain Under Stress Than Under High-Yield Conditions

Frost risk in canola and carinata as a function of sowing date in the agricultural central region of South America

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