Parameterization of the AquaCrop model for cowpea and assessing the impact of sowing dates normally used on yield

Nunes, Hildo Giuseppe Garcia Caldas; Farias, Vivian D. S.; Costa, Deborah Lp; Pinto, J.V.N.; Moura, Vandeilson Belfort; Teixeira, E.O.; Lima, Marcus José Alves de; Ortega-Farías, Samuel; Souza, Paulo Jorge Oliveira Ponte de

doi:10.1016/j.agwat.2021.106880

Cited by 20 publications

(13 citation statements)

References 27 publications

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“…This adjustment may include the impacts of water and temperature on the final yield. 34 Parameterization of maize crop parameters and model validation The model parameters in the crop file can be divided into conservative and non-conservative parameters. 35 The former change marginally over time and space, whereas the latter vary significantly by location or between different years.…”

Section: Model Simulation Principlementioning

confidence: 99%

Response of the water footprint of maize production to high temperatures in the Huang‐Huai‐Hai region of China

Wang

et al. 2022

J Sci Food Agric

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BACKGROUND: Water footprint (WF) can comprehensively evaluate agricultural water use efficiency under high-temperature weather. Based on the historical meteorological data in the Huang-Huai-Hai (3H) region of China, this study used the percentile threshold method to analyze the distribution of high-temperature events and set three types of meteorological scenarios, namely the actual temperature scenario (S1), the high temperatures in the ear stage scenario (S2), and the high temperatures in the flowering-maturity stage scenario (S3). The growing degree day (GDD) mode and calendar day (CD) mode in the Aqua-Crop model were used to simulate the yield per unit area (Y unit ) of maize under different temperature scenarios and then the crop evapotranspiration (ET c ) and production WF during maize growth period were calculated. RESULTS:The occurrence frequency of extreme high-temperature event in ear stage in the 3H region was lower than that in the flowering-maturity stage. There were significant differences in the WF of maize between S1 and S2 and between S1 and S3 in GDD mode, and significant differences in Y unit , ET c , and WF of maize under three temperature scenarios in the CD mode.CONCLUSION: High temperature events occur in maize growth period, especially in the flowering-maturity stage, will increase the WF of maize. Measures such as changing the planting structure, changing the sowing date of maize and cultivating heatresistant maize varieties could be taken to reduce the negative impacts of high-temperature weather.

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Section: Model Simulation Principlementioning

confidence: 99%

Response of the water footprint of maize production to high temperatures in the Huang‐Huai‐Hai region of China

Wang

et al. 2022

J Sci Food Agric

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“…To determine the water depth, the reference evapotranspiration (ET 0 ) was calculated using the Penman-Monteith equation [9] using data obtained from the meteorological station of the National Institute of Meteorology (INMET), installed 2 km from the experimental area. The ET 0 was multiplied by the crop coefficient (Kc) of each cowpea phase available in the literature [2] to obtain the maximum crop evapotranspiration.…”

Section: Methodsmentioning

confidence: 99%

“…The cowpea production in Brazil is concentrated in northeastern and northern regions and it was introduced in the state of Pará by migrants from northeastern Brazil, with the Vigna genus responsible for 80% of the state production, generating more than 70 thousand direct jobs [1]. However, this crop still has low productivity in the Pará state, reaching approximately 821 kg ha −1 [2] as a function of several factors such as improper seed management, low soil fertility and climatic adversity, mainly the water deficiency [3,4].…”

Section: Introductionmentioning

confidence: 99%

“…As a manner of increasing crop productivity, reducing production costs, enhancing income for rural producers, reducing environmental damage and maximizing the natural resource use, it is essential to adopt technologies, as well as the suitable irrigation management [8]. The proper irrigation depth must be considered to ensure a good water supply, avoiding crop stress and favoring plant growth [2]. Thus, the more detailed knowledge on cowpea development in response to water depths is an important factor to generate low-cost technology with increased local production.…”

Section: Introductionmentioning

confidence: 99%

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Cowpea Ecophysiological Responses to Accumulated Water Deficiency during the Reproductive Phase in Northeastern Pará, Brazil

et al. 2021

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Cowpea (Vigna unguiculata (L.) Walp.) is a leguminous species widely cultivated in northern and northeastern Brazil. In the state of Pará, this crop still has low productivity due to several factors, such as low soil fertility and climatic adversity, especially the water deficiency. Therefore, the present study aimed at evaluating the physiological parameters and the productivity of cowpea plants under different water depths. The experiment was conducted in Castanhal/Pará between 2015 and 2016. A randomized block design was applied with six replications and four treatments, represented by the replacement of 100%, 50%, 25% and 0% of the water lost during crop evapotranspiration (ETc), starting from the reproductive stage. The rates of net photosynthesis (A), stomatal conductance (gs), leaf transpiration (Eleaf), substomatal CO2 concentration (Ci), leaf temperature (Tleaf) and leaf water potential (Ψw) were determined in four measurements at the R5, R7, R8 and R9 phenological stages. Cowpea was sensitive to the water availability in the soil, showing a significant difference between treatments for physiological variables and productivity. Upon reaching a Ψw equal to −0.88 MPa, the studied variables showed important changes, which allows establishing this value as a threshold for the crop regarding water stress under such experimental conditions. The different water levels in the soil directly influenced productivity for both years, indicating that the proper water supply leads to better crop growth and development, increasing productivity.

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“…Furthermore, Hasanzadeh et al (2019) showed that the uppermost seed yield and seed protein content were recorded by sowing cowpea on 15 June compared to sowing on 20 May. Additionally, sowing cowpea in early April is appropriate for significantly improve final crop yields (Nunes et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Optimizing Cowpea Productivity by Sowing Date and Plant Density to Mitigate Climatic Changes

El-Sobky

Hassan

2021

Egypt. J. Agron.

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A DAPTATION to climatic changes by adjusting sowing date and using the optimum planting density can mitigate the negative effects on cowpea productivity. A field experiment was performed during two growing seasons of 2019 and 2020 at the experimental farm of Kafr Al-Hamam Agric. Res. Station, Sharqia Governorate, Egypt. The study aimed to optimize sowing date (31 May, 15 June and 30 June) and planting density (285715, 142860, 95240, 71430 and 57145 plants ha -1 ) that perform better in terms of seed and biomass yields as well as seed quality of cowpea under semi-arid conditions. The late cowpea sowing on 30 June appeared to be produced the higher seed yield contributions and yields ha -1 , crop and harvest index as well as pure seed. In respect of sowing density, intermediate planting density (95240 plants ha -1 ) exhibited the higher seed yield components and yields ha -1 , crop and harvest index as well as pure seed. Results of interaction indicated that late sowing on 30 June attained the maximum seed yield when intermediate planting density of 95240 plants ha -1 was used. Late sowing under lighter (57145 and 71430 plants ha -1 ) and intermediate (95240 plants ha -1 ) planting densities exhibited the highest pure seed as well as the fewest shriveled and infected seeds. Path coefficient analysis showed that number of pods plant -1 had exerted positive and high direct effect on seed yield of cowpea (0.385) and 100-seed weight had positive and moderate direct effect on seed yield of cowpea (0.251).

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Parameterization of the AquaCrop model for cowpea and assessing the impact of sowing dates normally used on yield

Cited by 20 publications

References 27 publications

Response of the water footprint of maize production to high temperatures in the Huang‐Huai‐Hai region of China

Response of the water footprint of maize production to high temperatures in the Huang‐Huai‐Hai region of China

Cowpea Ecophysiological Responses to Accumulated Water Deficiency during the Reproductive Phase in Northeastern Pará, Brazil

Optimizing Cowpea Productivity by Sowing Date and Plant Density to Mitigate Climatic Changes

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