Performance Evaluation of AquaCrop Model in Processing Tomato Biomass, Fruit Yield and Water Stress Indicator Modelling

Takács, Sándor; Csengeri, Erzsébet; Pék, Zoltán; Bíró, Tibor; Szuvandzsiev, P.; Palotás, Gábor; Helyes, Lájos

doi:10.3390/w13243587

Cited by 8 publications

(6 citation statements)

References 39 publications

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“…For example [19,20], reported ET underestimation when maize in Northeast China is stressed, while Mengistu et al's [17] study found a better ET agreement for cotton under water stress than not stressed. The above results were due to the reason that AquaCrop clarifies the process of canopy cover decrease at crop senescence [25,26]. It also supported by Mukherjee et al [46] suggested that the level of plant water stress affected the model performance.…”

Section: Statically Validation Performance Of Aquacropmentioning

confidence: 67%

“…Advances in Agriculture canopy cover during the water stress sensitive stages of tomato. Takács et al [26] and Cheng et al [28] also confirmed that the model overestimated CC, DY, and BM during the midseason (flowering and yield formation) stage of the crop supported with the Dev value being negative. Some researchers believe that the AquaCrop model overestimates and underestimates biomass and canopy cover in the middle of the crop growth stage.…”

Section: Statically Validation Performance Of Aquacropmentioning

confidence: 76%

“…This practice has been carried out in different climatic and agronomic conditions on the yield and productivity of different crops in different areas, such as potato [15,17,18], maize [19,20], cassava [21], chickpea [22], canola [23], and tomato [24,25,26,27,28]. However, most of these studies have investigated the applicability of the AquaCrop model under reduced water application of independent of growth stages and also the model performance varied with variations of crop types, climate, locations, irrigation seasons [29], the soil texture affects the model performance [30], some reports were found in the literature concerning the calibration of this model for arid climates on tomato crop.…”

Section: Introductionmentioning

confidence: 99%

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Performance Evaluation of AquaCrop Model of Tomato under Stage Wise Deficit Drip Irrigation at Southern Ethiopia

Yersaw,

Ebstu,

Areru

et al. 2024

Advances in Agriculture

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Crop modeling is a powerful tool for predicting yield and water productivity. The aim of the study was to calibrate and validate the AquaCrop model for tomato under staged deficit drip irrigation in Ethiopia. The AquaCrop model was calibrated and validated by using the observed data of canopy cover, biomass, dry yield, and soil water content. The results showed that the model was accurate in predicting canopy cover, biomass, and dry yield under different water levels. The overall performance in simulating canopy cover of AquaCrop, biomass, and soil water content showed a good match between measured and simulated data. The calibration results indicated good performance on canopy cover with 0.96 ≤ r ≤ 1.00, 2.9% ≤ RMSE ≤ 8.0%, 7.5% ≤ CV (RMSE) ≤ 21.1%, 0.91 ≤ EF ≤ 0.99, and 0.98 ≤ d ≤ 1.00. On biomass, the model calibration values were 0.99 ≤ r ≤ 1.00, 0.3 t/ha ≤ RMSE ≤ 0.8 t/ha, 8.3% ≤ CV (RMSE) ≤ 25.2%, 0.92 ≤ EF ≤ 0.99, and 0.98 ≤ d ≤ 1.00. Soil water content displayed poor performance on calibration, with performance values of 0.54 ≤ r ≤ 0.82, 3.6 mm ≤ RMSE ≤ 24.4 mm, 1.30% ≤ CV (RMSE) ≤ 9.00%, −4.18 ≤ EF ≤ 0.00, and 0.66 ≤ d ≤ 0.81. The validation results demonstrated that the model performed well on canopy cover with 0.96 ≤ r ≤ 1.00, 3.1% ≤ RMSE ≤ 7.7%, 8.2% ≤ CV (RMSE) ≤ 20.8%, EF ≥ 0.91, and d ≥ 0.9. The model validation correctly predicted biomass with r ≥ 0.98, 0.3 t/ha ≤ RMSE ≤ 0.7 t/ha, 8.9% ≤ CV (RMSE) ≤ 21.8%, EF ≥ 0.94, and d ≥ 0.98. The model validation poorly performed in forecasting soil water content, 0.20 ≤ r ≤ 0.80, 10.2 t/ha ≤ RMSE ≤ 24.0 t/ha, 3.5% ≤ CV (RMSE) ≤ 9.0%, −22.76 ≤ EF ≤ 0.63, and 0.40 ≤ d ≤ 0.87. The AquaCrop model is easy to use, requires less input data, and has high simulation accuracy, making it a useful tool for predicting crop yields and water productivity under staged deficit irrigation in areas with limited data.

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Section: Statically Validation Performance Of Aquacropmentioning

confidence: 67%

Section: Statically Validation Performance Of Aquacropmentioning

confidence: 76%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Performance Evaluation of AquaCrop Model of Tomato under Stage Wise Deficit Drip Irrigation at Southern Ethiopia

Yersaw,

Ebstu,

Areru

et al. 2024

Advances in Agriculture

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“…Namely, Katerji et al, (2013) obtained higher deviation of yield and biomass (from 4.2 % .up to 16.7% in non water stress condition and mild stressed). Battiliani et al, (2014) also stated that AquaCrop model adequately simulated processing tomato yield grown in valley of the river Po as well as Takács et al, (2021) in Hungary. Darko et al, (2016) Rather high value of NRMSE 16.7% and 21.8 % are the consequences of underestimation during initial period.…”

Section: Resultsmentioning

confidence: 99%

Simulation of Water Consumption, Growth and Yield of Tomatoes Using the Aquacrop Model

Lipovac,

Stricevic,

Ćosić

et al. 2022

JAFES

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Water for irrigation will undoubtedly be reduced as a result of climate change, disrupted rainfall patterns, and water scarcity, putting crop production in jeopardy. As a result, in order to maintain high agricultural production and meet food demand, new technology must be developed, and the feasibility of cultivating essential vegetable crops without irrigation must be investigated. The goal of this research is to estimate tomato water consumption, growth, and yield using the Aquacrop model. The experiment was put up on carbonate chernozem soil near Stara Pazova (40 kilometers north of Belgrade). There were two treatments: soil treated with organic fertilizer Fertigkompost (OF) and soil treated with no organic fertilizer (K). Both treatments were fed by rain. The obtained results show that the AquaCrop model accurately predicts tomato yields with variations of 7.1 percent and 11.8 percent, respectively, when compared to observed yields on OF and K treatments. For the OF and K treatments, statistical indices of correlation coefficients (r) of 0.97 and 0.95, respectively, root mean square error (RMSE) of 10.1 percent, 9.0 percent, and Willmott index of agreement (d) of 0.98, 0.97, confirm excellent assessment of tomato growth. Water consumption is likewise fairly predicted by the model, with r= 0.72 and 0.63, RMSE = 38.1 and 32.5 mm, and d= 0.83 and 0.76 for the OF and K treatments, respectively. With high confidence, the model may be used to estimate tomato production in a variety of growth circumstances.

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“…The adverse effect of such factors on yield can be managed by adopting appropriate irrigation techniques, the use of bio-fertilizers, and the use of drought-resistant varieties. The application of different irrigation model systems provides the possibility to determine irrigation timing and irrigation water dose for crops [1][2][3][4], though this process requires knowledge of the response of the varieties to water-deficit stress. Under water shortage, plants respond by decreasing water loss as a result of stomata closing, which reduces transpiration as well as the inflow and delivery of atmospheric CO 2 to the cells [5] but increases stomata resistance, therefore influencing the efficacy of water consumption [6].…”

Section: Introductionmentioning

confidence: 99%

Impact of Plant Growth-Promoting Rhizobacteria Inoculation on the Physiological Response and Productivity Traits of Field-Grown Tomatoes in Hungary

et al. 2022

Self Cite

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Drought-tolerant plant growth-promoting rhizobacteria (PGPR) may promote plant development under limited water supply conditions, when plant’s water demand is not completely satisfied under rain-fed conditions or when irrigation water availability is limited. The aim of this study was to examine the effects of two inoculation treatments (B2: Alcaligenes sp. 3573, Bacillus sp. BAR16, and Bacillus sp. PAR11 strains and B3: Pseudomonas sp. MUS04, Rhodococcus sp. BAR03, and Variovorax sp. BAR04 strains) and compare those to a control (B0) without artificial inoculation on chlorophyll fluorescence, leaf chlorophyll content (SPAD value), canopy temperature, and the yield of the processing tomato cultivar H-1015 F1 grown under field conditions. The young seedlings of the hybrid tomato variety H-1015 F1 were immersed in 1% of B2 or B3 products (BAY-BIO, Szeged Hungary) for 5 min. Inoculated and untreated seedlings were grown under three irrigation treatments [regular irrigation (RI), deficit irrigation (DI), and no irrigation (I0)], to reveal the effect of PGPR under different levels of water stress. In the dry year (2018), higher canopy temperature and chlorophyll fluorescence (Fv/Fm) were measured during flowering in plants treated with bacteria than in untreated plants. In the stage of flowering and fruit setting, the B3 treatment led to a significant decrease in the Fv/Fm value, canopy temperature remained high, and the SPAD value was statistically the same in all treatments. Under limited water supply, in most cases, PGPR led to a significantly greater total yield but more unripe green berries compared to untreated plants. Under moderate water shortage (dry year + deficit irrigation), the B3 treatment resulted in 26% more ripe, marketable fruit and 49% less unripe fruit compared to the B2 treatment. On the other hand, in the wet year (2020), the bacterial treatments generally did not affect physiological properties, though the B2 treatment produced a higher marketable yield while the amount of green and diseased fruits did not differ statistically, compared to the B3 treatment under deficit irrigation. Based on our study, we recommend the application of the B3 PGPR product as it positively affected key physiological processes, leading to a higher marketable yield particularly under water shortage.

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Performance Evaluation of AquaCrop Model in Processing Tomato Biomass, Fruit Yield and Water Stress Indicator Modelling

Cited by 8 publications

References 39 publications

Performance Evaluation of AquaCrop Model of Tomato under Stage Wise Deficit Drip Irrigation at Southern Ethiopia

Performance Evaluation of AquaCrop Model of Tomato under Stage Wise Deficit Drip Irrigation at Southern Ethiopia

Simulation of Water Consumption, Growth and Yield of Tomatoes Using the Aquacrop Model

Impact of Plant Growth-Promoting Rhizobacteria Inoculation on the Physiological Response and Productivity Traits of Field-Grown Tomatoes in Hungary

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