Growth responses of green mustard (Brassica juncea) and water spinach (Ipomoea aquatica) in terms of water productivity and yield based on Cropwat 8.0 with limited data availability in a semi-arid developing nation
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Abstract
The crop water requirement (CWR) is one of the most important aspects to consider when studying food production under the types of water scarcity constraints that are widely encountered in semi-arid regions. Better CWR predictions lead to better irrigation applications when studies are hampered by inadequate data and expertise. The aim of this work is therefore to predict the irrigation requirements, variate the irrigation application, to determine and model the crop growth and production responses, and subsequently assess the crop water productivity. In this research, we input climate, crop and soil data and certain strong assumptions to FAO-Cropwat Version 8.0 to predict the CWR. Green mustard (Brassica juncea) and water spinach (Ipomoea aquatica) were cultivated in polybags with limited handling, and irrigated with variations in the predicted CWR. The crop height, number of leaves, and fresh weight were measured and used as input to a crop-water response model using the response surface methodology. The water productivity (WP) was then used to quantify the crop-water relationship. The results showed that these two small vegetables showed similar effects from irrigated water on the crop height, with a slightly different effect on the number of leaves, and different effects on the fresh weight. The models fitted the reduced quadratic model, and were considered to be valid. The most significant components of our model were the potential evapotranspiration (ETo), available water (AVW), and the interaction between ETo and AVW, which showed saddle responses with maximum and minimum effects. The WP for green mustard was higher than for water spinach. The highest WP for both crops was achieved when they were irrigated with a reduction of 50% from the predicted CWR. In these research conditions, we recommend taking advantage of FAO- Cropwat version 8.0 for a reduction in irrigation water application. We also suggest further experiments with crops cultivated in fields.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
Akinbile CO, Ogundipe A, Davids RO. Crop water requirements, biomass and grain yields estimation for upland rice using CROPWAT, AQUACROP and CERES simulation models. Agric Eng Int: CIGR J. 2020;22(2):1-20.
García-Tejero IF, Durán-Zuazo VH. Plant water use efficiency for a sustainable agricultural development. Agronomy. 2022;12(8):1-6.
Elnashar A, Abbas M, Sobhy H, Shahba M. Crop water requirements and suitability assessment in arid environments: a new approach. Agronomy 2021;11(2):1-18.
Koehuan JE, Suharto B, Djoyowasito G, Susanawati LD. Water total factor productivity growth of rice and corn crops using data envelopment analysis – Malmquist index (West Timor, Indonesia). Agric Eng Int: CIGR J. 2020;22(4):20-30.
Gong X, Zhang H, Rena C, Sun D, Yang J. Optimization allocation of irrigation water resources based on crop water requirement under considering effective precipitation and uncertainty. Agric Water Manag. 2020;239:106264.
Xie YL, Xia DX, Ji L, Huang GH. An inexact stochastic-fuzzy optimization model for agricultural water allocation and land resources utilization management under considering effective rainfall. Ecol Indic. 2018;92:301-11.
Pereira LS, Paredes P, Hunsaker DJ, López-Urrea R, Mohammadi Shad Z. Standard single and basal crop coefficients for field crops :Updates and advances to the FAO 56 crop water requirements method. Agric Water Manag. 2021;243:106466.
Bao Y, Duan L, Liu T, Tong X, Wang G, Lei H, et al. Simulation of evapotranspiration and its components for the mobile dune using an improved dual-source model in semi-arid regions. J Hydrol. 2021;592:125796.
Blaney HF, Criddle WD. Determining water requirements for settling water disputes. Nat Resour J. 1964;29:29-41.
Vozhehova RA, Lavrynenko YO, Kokovikhin SV, Lykhovyd PV, Biliaieva IM, Drobitko AV, et al. Assessment of the CROPWAT 8.0 software reliability for evapotranspiration and crop water requirements calculations. J Water Land Dev. 2018;39(X-XII):147-52.
Doorenbos J, Pruitt WO. Crop water requirements (FAO Irrigation and Drainage Paper No. 24). 4th ed. Rome, Italy: Food and Agriculture Organization; 1992.
Allen RG, Pereira LS, Raes D, Smith M. Crop evapotranspiration (guidelines for computing crop water requirements) - FAO Irrigation and Drainage Paper No. 56. Rome, Italy: Food and Agriculture Organization; 1998.
Sharma B, Molden D, Cook S. Water use efficiency in agriculture: measurement, current situation and trends. In: Drechsel P, Heffer P, Magen H, Mikkelsen R, Wichelns D, editors. Managing water and fertilizer for sustainable agricultural intensification. Paris, France: International Fertilizer Industry Association (IFA), International Water Management Institute (IWMI), International Plant Nutrition Institute (IPNI), and International Potash Institute (IPI); 2015. p. 39-64.
Koehuan JE. The estimation and optimization of socio-economy-environment response on West Timor’s staple food consumptive water use. Eng Appl Sci Res. 2023;50(1):63-73.
Desta FY, Abera K, Eshetu M, Koech R, Alemu MM. Irrigation water planning for crops in the central highlands of Ethiopia, aided by FAO Cropwat Model. Afr J Agric Res. 2017;12(28):2329-35.
Gabr MES. Management of irrigation requirements using FAO-CROPWAT 8.0 model: a case study of Egypt. Model Earth Syst Environ. 2022;8:3127-42.
Aydin Y. Quantification of water requirement of some major crops under semi-arid climate in Turkey. PeerJ. 2022;10:e13696.
Ewaid SH, Abed SA, Al-Ansari N. Crop water requirements and irrigation schedules for some major crops in Southern Iraq. Water. 2019;11(4):756.
Haq MA, Khan MYA. Crop water requirements with changing climate in an arid region of Saudi Arabia. Sustainability. 2022;14(20):13554.
Banerjee S, Chatterjee S, Sarkar S, Jena S. Projecting future crop evapotranspiration and irrigation requirement of potato in Lower Gangetic Plains of India using the CROPWAT 8.0 model. Potato Res. 2016;59(4):313-27.
Herbha N, Vora H, Kunapara AN. Simulation of crop water requirement and irrigation scheduling for maize crop using FAO-CROPWAT 8.0 in Panchmahal region of Middle Gujarat. Trends Biosci. 2017;10(46):9387-91.
Bahrun AH, Nurfaida, Ridwan I, Zul AF, Widiayani N, Kusumah R. Management of planting system based on water balance patterns on corn plants using Cropwat 8.0 model. IOP Conf Ser: Earth Environ Sci. 2019;343:1-6.
Beshir S. Review on estimation of crop water requirement, irrigation frequency and water use efficiency of cabbage production. J Geosci Environ Prot. 2017;5:59-69.
Moseki O, Murray-Hudson M, Kashe K. Crop water and irrigation requirements of Jatropha curcas L. in semi-arid conditions of Botswana: applying the CROPWAT model. Agric Water Manag. 2019;225:105754.
Gashari T, Twaibu S, Kucel SB, Magumba D. Tomato yield and quality response to water application technique and management. Eur J Eng Technol Res. 2021;6(7):153-9.
Masafu CK, Trigg MA, Carter R, Howden NJK. Water availability and agricultural demand: an assessment framework using global datasets in a data scarce catchment, Rokel-Seli River, Sierra Leone. J Hydrol Reg Stud. 2016;8:222-34.
Eze E, Girma A, Zenebe A, Kourouma JM, Zenebe G. Exploring the possibilities of remote yield estimation using crop water requirements for area yield index insurance in a data-scarce dryland. J Arid Environ. 2020;183:104261.
Sharma DN, Tare V. Assessment of irrigation requirement and scheduling under canal command area of Upper Ganga Canal using CropWat model. Model Earth Syst Environ. 2022;8(2):1863-73.
Zakari MD, Maina MM, Audu I, Abubakar MS, Shanono NJ, Mohammed D. Sensitivity analysis of crop water requirement simulation Model (Cropwat 8.0) at Kano River Irrigation Project (KRIP), Kano-Nigeria. Proceedings of Second International Interdisciplinary Conference on Global Initiatives for Integrated Development (IICGIID); 2015 Sep 2-5; Chukwuemeka Odumegwu University, Igbariam Campus, Nigeria. p. 502-10.
Saeed FH, Al-Khafaji MS, Al-Faraj FAM. Sensitivity of irrigation water requirement to climate change in arid and semi-arid regions towards sustainable management of water resources. Sustainability. 2021;13(24):13608.
Doorenbos J, Kassam AH. Yield response to water (FAO Irrigation and Drainage Paper No. 33). Rome, Italy: Food and Agriculture Organization; 1979.
Pasquale Steduto P, Hsiao TC, Fereres E, Raes D. Crop yield response to water (FAO Irrigation and Drainage Paper No. 66). Rome, Italy: Food and Agriculture Organization; 2012.
Myers RH, Montgomery DC, Anderson-Cook CM. Response surface methodology: process and product optimization using designed experiments. 3rd ed. New Jersey: John Wiley & Sons; 2009.
Soltani M, Soltani J. Determination of optimal combination of applied water and nitrogen for potato yield using response surface methodology (RSM). Biosci Biotechnol Res Commun. 2016;9(1):46-54.
Sugiharta I, Sari DI, Febriyani V, Man YL, Rinaldi A, Suri FI. The application of response surface method in producing water spinach (Ipomoea reptans Poir) through hydroponics technique with iron-electrode electrolyzed water. J Phys: Conf Ser. 2021;1796:012032.
Giordano M, Turral H, Scheierling SM, Tréguer DO, McCornick PG. Beyond “More crop per drop”: evolving thinking on agricultural water productivity. Colombo, Sri Lanka: International Water Management Institute (IWMI); Washington, DC, USA: The World Bank; 2017. IWMI Research Report 169.
Molden D. Accounting for water use and productivity. Colombo, Sri Lanka: International Irrigation Management Institute; 1997. SWIM Paper 1.
Koehuan JE, Suharto B, Djoyowasito G, Susanawati LD. Corn water productivity growth of West Timor, Indonesia. International Conference on Biology and Applied Science (ICOBAS); 2019 Mar 20-21; Malang, Indonesia. AIP Conf Proc. 2019;2120:1-9.
BPS (Statistics of Kupang Municipality). Kupang Municipality in Figures 2022. Kupang-NTT: BPS (Statistics of Kupang Municipality); 2022. (In Indonesian)
Wikipedia. Kupang – Wikipedia [Internet]. 2023 [cited 2023 Apr 25]. Available from: https://en.wikipedia.org/wiki/Kupang.
Smith M. CROPWAT: A computer program for irrigation planning and management. (FAO Irrigation and Drainage Paper No. 46). 3rd ed. Rome, Italy: Food and Agriculture Organization; 1996.
Vudhivanich V. Crop water requirements and irrigation scheduling with CROPWAT 8.0 application. Climate Smart Irrigation Training [Presentation]; 2018 May 21-25; Kasetsart University, Thailand.
Asgarzadeh H, Mosaddeghi MR, Mahboubi AA, Nosrati A, Dexter AR. Soil water availability for plants as quantified by conventional available water, least limiting water range and integral water capacity. Plant Soil. 2010;335:229-44.
Brendel O. The relationship between plant growth and water consumption: a history from the classical four elements to modern stable isotopes. Annals of Forest Science 2021;78:1-16.
Ines AVM, Droogers P, Makin IW, Gupta AD. Crop growth and soil water balance modeling to explore water management options. Colombo, Sri Lanka: International Water Management Institute; 2001. IWMI Working Paper 22.
Anda P, Ginting S, Sabaruddin L, Hamimu L, Tufaila M. The effect of different water levels and varieties on the growth and yield of onion (Allium cepa L.) using a watering pot in hot dry season at Tomia District Wakatobi Indonesia. Adv Environ Biol. 2017;11(10):65-71.
Parkash V, Singh S, Deb SK, Ritchie GL, Wallace RW. Effect of deficit irrigation on physiology, plant growth, and fruit yield of cucumber cultivars. Plant Stress. 2021;1(1):100004.
Fourcaud T, Zhang X, Stokes A, Lambers H, Körner C. Plant growth modelling and applications: the increasing importance of plant architecture in growth models. Ann Bot. 2008;101(8):1053-63.
Foster T, Brozović N. Simulating crop-water production functions using crop growth models to support water policy assessments. Ecol Econ. 2018;152:9-21.
Rai A, Mohanty B, Bhargava R. Supercritical extraction of sunflower oil: a central composite design for extraction variables. Food Chem. 2016;192:647-59.
Liu Q, Niu J, Sivakumar B, Ding R, Li S. Accessing future crop yield and crop water productivity over the Heihe River basin in northwest China under a changing climate. Geosci Lett. 2021;8:1-16.