AquaCrop parametrisation for quinoa in arid environments

Abstract

The resilience of quinoa to drought stress conditions makes the crop suitable for the Sahel region. It can support grain production during the dry season and be considered an alternative crop for alleviating food insecurity within the region. Given the importance of this crop outside the indigenous cultivation area, there is a requisite for the development of crop models to facilitate further expansion of quinoa along the Sahel region. Crop water models are of interest due to increasing pressure on water resources, and the portrayal of irrigation scheduling as the best option for water optimisation. The AquaCrop model was selected, as this model simulates crop development and derives both optimal frequencies and net applications of irrigation. Due to limited water resources in the region, different irrigation regimes (full irrigation (FI), progressive drought (PD), deficit irrigation (DI) and extreme deficit irrigation (EDI)) were proposed for analysing yield and biomass responses to water stress conditions. Results suggest that yields were stabilised at around 1.0 Mg ha-1 under PD, thereby prioritising maximum water productivity rather than maximum yields. Water optimisation was attained by watering less at a suggested 310 mm, but with more frequent irrigation events, 28 rather than 20.

Climate resilience of irrigated quinoa in semi-arid West Africa

“…In the present study, the heat-stress coefficient for pollination of quinoa is between 36 and 41°C. Although these values are similar to those reported under controlled climatic conditions and field experiments in Burkina Faso and Mali (Alvar-Beltrán et al 2019b, 2020b, Coulibaly et al 2015, they differ from those given by default (38.5−42.5 °C) in AquaCrop (Geerts et al 2009). Therefore, if critical temperature thresholds for quinoa (36−41°C) continue to be exceeded, yields will decline due to the compounded impact of temperature on crop development, crop transpiration, pollen desiccation and pollen viability.…”

“…Therefore, AquaCrop was considered a suitable model for simulating crop responses to abiotic stresses in terms of seed yields and biomass production (Gobin et al 2017, Garofalo et al 2019). In addition to climate and soil data, other input parameters for operating the AquaCrop model were obtained from a search of the literature and our own past work in the region (Table 2), including: (1) crop information (timing and duration of each phenological phase and canopy cover) from a 2 yr field experiment in Burkina Faso with quinoa under different irrigation schedules (Alvar-Beltrán et al 2019a, 2021; (2) upper heat-stress thresholds (38°C) at which quinoa yields start to decline (Alvar-Beltrán et al 2020a); (3) base temperature of quinoa, established at 3°C (Jacobsen & Bach 1998) and ( 4) seed yield and biomass production values calibrated and validated on AquaCrop (Alvar-Beltrán et al 2020b, Dao et al 2020).…”

Quinoa Phenotyping Methodologies: An International Consensus

“…However, more work on getting DSSAT models calibrated and usable for quinoa is required. Other crop growth models or crop water models such as SALTMED and AquaCrop are good resources for quinoa and already applied (e.g., [ 97 , 98 , 115 , 116 , 117 , 118 , 119 ]). The minimal requirements necessary to use these models must be considered (for AquaCrop see [ 120 ]; [ 121 ]; for SALTMED see [ 122 ]).…”

Identifikasi Nilai Konstanta Daun Tanaman Rambutan dan Jambu Air Berbasis Pengolahan Citra Digital

“…Berdasarkan hasil analisis statistik tersebut menunjukkan bahwa metode prediksi luas daun menggunakan metode dimensi daun dengan menggunakan nilai konstanta yang diperoleh dalam hasil penelitian dapat bekerja sangat baik dan akurat dalam mengukur luas daun untuk masing-masing jenis tanaman. (Alvar-Beltrán et al, 2021;Suprayogi et al, 2014). Hal yang serupa juga berlaku untuk NRMSE, semakin kecil (mendekati 0) nilai NRMSE, maka hasil prediksi akan semakin baik (Alvar-Beltrán et al, 2021;.…”