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Comprehensive yield gap analysis and optimizing agronomy practices of soybean in Iran

Published online by Cambridge University Press:  05 April 2021

A. Nehbandani Open the ORCID record for A. Nehbandani [Opens in a new window] ,
A. Soltani ,
A. Hajjarpoor ,
A. Dadrasi  and
F. Nourbakhsh
A. Nehbandani*
Affiliation:
Department of Plant Protection, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan49138-15739, Iran
A. Soltani
Affiliation:
Department of Plant Protection, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan49138-15739, Iran
A. Hajjarpoor
Affiliation:
IRD–UMR DIADE–Univ. de Montpellier, 911 Av Agropolis–BP 64501-34394, MontpellierCedex 5, France
A. Dadrasi
Affiliation:
Department of Agronomy, Agriculture College, Vali-e-Asr University of Rafsanjan, Kerman77188-97111, Iran
F. Nourbakhsh
Affiliation:
SWEP Analytical Laboratories, Melbourne, Victoria3173, Australia
*
Author for correspondence: A. Nehbandani, E-mail: a.nehbandani@yahoo.com
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Abstract

Soybean is one of the key oil crops in global food security. The objective of the current study was to determine the magnitude of soybean yield and yield gaps (Yg) in the main producing regions in Iran, the main causes and possible solutions to reduce these gaps and improve yields. This study uses an integrated approach of crop simulation and on-farm information. The SSM-iCrop2 model was used to calculate the potential yield (Yp). Furthermore, management information of soybean farms (the number of monitored farms was 224) was collected and analysed with two methods, including stepwise regression (a production model was created and based on it, the yield-limiting factors were determined) and boundary line analysis (show the optimum level of crop management and simultaneously the percentage of farms that were out of the optimal range of a specific management procedure). The results showed a Yp of 4681 kg/ha while actual yield (Ya) was around 2257 kg/ha. The main factors causing Yg of soybean in Iran were irrigation, nitrogen fertilizer, phosphorus fertilizer and sowing date. Altering soybean sowing date to late June or early July, irrigating at least five times during the growing season, applying at least 50 kg/ha nitrogen and 45 kg/ha phosphorus base application are foremost management practices that could shrink the soybean yield gap in Iran. The results presented in this study can bring relevant transferable information to other soybean production areas sharing the same latitudes and climate, and the approach can be used for other crops worldwide.

Keywords

Boundary line analysiscrop simulationfood securitystepwise regression
Type
Crops and Soils Research Paper
Information
The Journal of Agricultural Science , Volume 158 , Issue 8-9 , November 2020 , pp. 739 - 747
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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References

Aghayari, F, Faraji, A and Kordkatooli, A (2015) Determination of yield and yield components response of soybean (Glycin max L.) to swing date, temperature and sunshine hours. Journal of Agroecology 4, 547–562.Google Scholar
Bieranvand, NP, Rastin, NS, Afarideh, H and Sagheb, N (2003) An evaluation of the N-fixation capacity of some Bradyrhizobium japonicum strains for soybean cultivars. Iranian Journal of Agricultural Sciences 34, 97–104.Google Scholar
Bindraban, PS, Stoorvogel, JJ, Jansen, DM, Vlaming, J and Groot, JJR (2000) Land quality indicators for sustainable land management: proposed method for yield gap and soil nutrient balance. Agriculture, Ecosystems & Environment 81, 103–112.CrossRefGoogle Scholar
Boyer, CN, Stefanini, M, Larson, JA, Smith, SA, Mengistu, A and Bellaloui, N (2015) Profitability and risk analysis of soybean planting date by maturity group. Agronomy Journal 107, 2253–2262.CrossRefGoogle Scholar
Casanova, D, Goudriaan, J, Bouma, J and Epema, GF (1999) Yield gap analysis in relation to soil properties in direct-seeded flooded rice. Geoderma 91, 191–216.CrossRefGoogle Scholar
Davis, KF, Rulli, MC, Garrassino, F, Chiarelli, D, Seveso, A and D'Odorico, P (2017) Water limits to closing yield gaps. Advances in Water Resources 99, 67–75.CrossRefGoogle Scholar
De Bie, C (2000) Comparative performance analysis of agro-ecosystems (Doctoral dissertation), Wageningen University & Research.Google Scholar
Draper, NR and Smith, H (1998) Applied Regression Analysis. Canada: John Wiley & Sons.CrossRefGoogle Scholar
Edreira, JIR, Mourtzinis, S, Conley, SP, Roth, AC, Ciampitti, IA, Licht, MA, Kandel, H, Kyveryga, PM, Lindsey, LE, Mueller, DS, Naeve, SL, Nafziger, E, Specht, JE, Stanley, J, Staton, MJ and Grassini, P (2017) Assessing causes of yield gaps in agricultural areas with diversity in climate and soils. Agricultural and Forest Meteorology 247, 170–180.CrossRefGoogle Scholar
Egli, DB (1993) Cultivar maturity and potential yield of soybean. Field Crops Research 32, 147–158.CrossRefGoogle Scholar
Egli, DB and Cornelius, PL (2009) A regional analysis of the response of soybean yield to planting date. Agronomy Journal 101, 330–335.CrossRefGoogle Scholar
FAO (2017) Assists Iran to boost oils seed production and reach self-sufficiency. Available at http://www.fao.org/neareast/news/view/en/c/896554/Google Scholar
Fischer, RA (2015) Definitions and determination of crop yield, yield gaps, and of rates of change. Field Crops Research 182, 9–18.CrossRefGoogle Scholar
French, RJ and Schultz, JE (1984) Water use efficiency of wheat in a Mediterranean-type environment. I. The relation between yield, water use and climate. Australian Journal of Agricultural Research 35, 743–764.CrossRefGoogle Scholar
George, T (2014) Why crop yields in developing countries have not kept pace with advances in agronomy. Global Food Security 3, 49–58.CrossRefGoogle Scholar
Gobbett, DL, Hochman, Z, Horan, H, Navarro Garcia, J, Grassini, P and Cassman, KG (2017) Yield gap analysis of rainfed wheat demonstrates local to global relevance. Journal of Agricultural Science 155, 282–299.CrossRefGoogle Scholar
Grassini, P, Bussel, LGJ, Van Wart, J, Van Wolf, J, Claessens, L, Yang, H, Boogaard, H, Groot, H, Van De Ittersum, MK and Cassman, KG (2015 a) Field crops research how good is good enough? Data requirements for reliable crop yield simulations and yield-gap analysis. Field Crops Research 177, 49–63.CrossRefGoogle Scholar
Grassini, P, Torrion, JA, Yang, HS, Rees, J, Andersen, D, Cassman, KG and Specht, JE (2015 b) Soybean yield gaps and water productivity in the western US Corn Belt. Field Crops Research 179, 150–163.CrossRefGoogle Scholar
Hajjarpoor, A, Soltani, A, Zeinali, E, Kashiri, H, Aynehband, A and Vadez, V (2018) Using boundary line analysis to assess the on-farm crop yield gap of wheat. Field Crops Research 225, 64–73.CrossRefGoogle Scholar
Hartman, GL, West, ED and Herman, TK (2011) Crops that feed the World 2. Soybean – worldwide production, use, and constraints caused by pathogens and pests. Food Security 3, 5–17.CrossRefGoogle Scholar
Heatherly, LG and Elmore, RW (2004) Managing inputs for peak production. Soybeans: Improvement, Production, and Uses 16, 451–536.Google Scholar
Hochman, Z, Gobbett, D, Horan, H and Garcia, JN (2016) Data rich yield gap analysis of wheat in Australia. Field Crops Research 197, 97–106.CrossRefGoogle Scholar
Hoogenboom, G, Jones, JW, Wilkens, PW, Porter, CH, Batchelor, WD, Hunt, LA, Boote, KJ, Singh, U, Uryasev, O, Bowen, WT, Gijsman, A, Dutoit, A, White, J and Tsuji, G (2004) Decision Support System for Agrotechnology Transfer Version 4.0. (CD-ROM). Honolulu, HI: University of Hawaii.Google Scholar
Kitchen, NR, Drummond, ST, Lund, ED, Sudduth, KA and Buchleiter, GW (2003) Soil electrical conductivity and topography related to yield for three contrasting soil–crop systems. Agronomy Journal 95, 483–495.CrossRefGoogle Scholar
Koo, J and Dimes, J (2013) HC27 Generic Soil Profile Database. Harvard Dataverse ver. 4. Washington, DC: International Food Policy Research Institute.Google Scholar
Lobell, DB (2013) The use of satellite data for crop yield gap analysis. Field Crops Research.CrossRefGoogle Scholar
Makowski, D, Doré, T and Monod, H (2007) A new method to analyse relationships between yield components with boundary lines. Agronomy for Sustainable Development 27, 119–128.CrossRefGoogle Scholar
Merlos, FA, Monzon, JP, Mercau, JL, Taboada, M, Andrade, FH, Hall, AJ, Jobbagy, E, Cassman, KG and Grassini, P (2015) Potential for crop production increase in Argentina through closure of existing yield gaps. Field Crops Research 184, 145–154.CrossRefGoogle Scholar
Milne, AE, Ferguson, RB and Lark, RM (2006) Estimating a boundary line model for a biological response by maximum likelihood. Annals of Applied Biology 149, 223–234.CrossRefGoogle Scholar
Moosavi, SS, Akbar, SMJMA, Khaneghah, AM and Moghanlou, BS (2011) Study of effect of planting date on vegetative traits, reproductive traits and grain yield of soybean cultivars in cold region of Ardabil (Iran). African Journal of Agricultural Research 6, 4879–4883.Google Scholar
Mussgnug, F, Becker, M, Son, TT, Buresh, RJ and Vlek, PLG (2006) Yield gaps and nutrient balances in intensive, rice-based cropping systems on degraded soils in the Red River Delta of Vietnam. Field Crops Research 98, 127–140.CrossRefGoogle Scholar
Nehbandani, A (2018) Yield Gap Analysis of Soybean in Iran (Doctoral dissertation), Gorgan University of Agricultural Sciences and Natural Resources.Google Scholar
Nehbandani, A, Soltani, A, Naghab, RT, Dadrasi, A and Alimagham, SM (2020 a) Assessing HC27 soil database for modeling plant production. International Journal of Plant Production 14, 679–687.CrossRefGoogle Scholar
Nehbandani, A, Soltani, A, Nourbakhsh, F and Dadrasi, A (2020b) Estimating crop model parameters for simulating soybean production in Iran conditions. OCL 27, 58.CrossRefGoogle Scholar
Patrignani, A, Lollato, RP, Ochsner, TE, Godsey, CB and Edwards, JT (2014) Yield gap and production gap of rainfed winter wheat in the southern Great Plains. Agronomy Journal 106, 1329–1339.CrossRefGoogle Scholar
Prost, L, Makowski, D and Jeuffroy, M-H (2008) Comparison of stepwise selection and Bayesian model averaging for yield gap analysis. Ecological Modelling 219, 66–76.CrossRefGoogle Scholar
Robinson, AP, Conley, SP, Volenec, JJ and Santini, JB (2009) Analysis of high yielding, early-planted soybean in Indiana. Agronomy Journal 101, 131–139.CrossRefGoogle Scholar
Salmeron, M, Gbur, EE, Bourland, FM, Buehring, NW, Earnest, L, Fritschi, FB, Golden, BR, Hathcoat, D, Lofton, J, Miller, TD, Neely, C, Shannon, G, Udeigwe, TK, Verbree, DA, Vories, ED, Wiebold, WJ and Purcell, LC (2014) Soybean maturity group choices for early and late plantings in the Midsouth. Agronomy Journal 106, 1893–1901.CrossRefGoogle Scholar
Schulze, J, Temple, G, Temple, SJ, Beschow, H and Vance, CP (2006) Nitrogen fixation by white lupin under phosphorus deficiency. Annals of Botany 98, 731–740.CrossRefGoogle ScholarPubMed
Senapati, N and Semenov, MA (2019) Assessing yield gap in high productive countries by designing wheat ideotypes. Scientific Reports 9, 1–12.CrossRefGoogle ScholarPubMed
Sentelhas, PC, Battisti, R, Câmara, GMS, Farias, JRB, Hampf, AC and Nendel, C (2015) The soybean yield gap in Brazil – magnitude, causes and possible solutions for sustainable production. The Journal of Agricultural Science 153, 1394–1411.CrossRefGoogle Scholar
Serraj, R and Sinclair, TR (1996) Processes contributing to N2-fixation intensitivity to drought in the soybean cultivar Jackson. Crop Science 36, 961–968.CrossRefGoogle Scholar
Shatar, TM and McBratney, AB (2004) Boundary-line analysis of field-scale yield response to soil properties. The Journal of Agricultural Science 142, 553.CrossRefGoogle Scholar
Solomon, T, Pant, LM and Angaw, T (2012) Effects of inoculation by Bradyrhizobium japonicum strains on nodulation, nitrogen fixation, and yield of soybean (Glycine max L. Merill) varieties on nitisols of Bako, Western Ethiopia. International Scholarly Research Notices 2012, 1–8.Google Scholar
Soltani, A and Sinclair, TR (2012) Modeling Physiology of Crop Development, Growth and Yield. USA: CABi.CrossRefGoogle Scholar
Soltani, A, Hajjarpour, A and Vadez, V (2016) Analysis of chickpea yield gap and water-limited potential yield in Iran. Field Crops Research 185, 21–30.CrossRefGoogle Scholar
Soltani, A, Alimagham, SM, Nehbandani, A, Torabi, B, Zeinali, E, Dadrasi, A, Zand, E, Ghassemi, S, Pourshirazi, S, Alasti, O, Hosseini, R, Zahed, M, Arabameri, R, Mohammadzadeh, Z, Rahban, S, Kamari, H, Fayazi, H, Mohammadi, S, Keramat, K, Vadez, V, van Ittersum, M and Sinclair, TR (2020) SSM-iCrop2: a simple model for diverse crop species over large areas. Agricultural Systems 182, 102855.CrossRefGoogle Scholar
Sulieman, S, Ha, C, Van Schulze, J and Tran, L-SP (2013) Growth and nodulation of symbiotic Medicago truncatula at different levels of phosphorus availability. Journal of Experimental Botany 64, 2701–2712.CrossRefGoogle ScholarPubMed
Tittonell, P, Shepherd, KD, Vanlauwe, B and Giller, KE (2008) Unravelling the effects of soil and crop management on maize productivity in smallholder agricultural systems of western Kenya – an application of classification and regression tree analysis. Agriculture, Ecosystems & Environment 123, 137–150.CrossRefGoogle Scholar
van Bussel, LGJ, Grassini, P, Van Wart, J, Wolf, J, Claessens, L, Yang, H, Boogaard, H, de Groot, H, Saito, K, Cassman, KG and van Ittersum, MK (2015) From field to atlas: upscaling of location-specific yield gap estimates. Field Crops Research 177, 98–108.CrossRefGoogle Scholar
Vance, CP, Uhde-Stone, C and Allan, DL (2003) Phosphorus acquisition and use: critical adaptations by plants for securing a nonrenewable resource. New Phytologist 157, 423–447.CrossRefGoogle ScholarPubMed
Van Ittersum, MK, Cassman, KG, Grassini, P, Wolf, J, Tittonell, P and Hochman, Z (2013) Yield gap analysis with local to global relevance-a review. Field Crops Research 143, 4–17.CrossRefGoogle Scholar
Van Wart, J, van Bussel, LGJ, Wolf, J, Licker, R, Grassini, P, Nelson, A, Boogaard, H, Gerber, J, Mueller, ND, Claessens, L, van Ittersum, MK and Cassman, KG (2013) Use of agro-climatic zones to upscale simulated crop yield potential. Field Crops Research 143, 44–55.CrossRefGoogle Scholar
Verdoodt, A, Van Ranst, E and Van Averbeke, W (2003) Modelling crop production potentials for yield gap analysis under semiarid conditions in Guquka, South Africa. Soil Use and Management 19, 372–380.CrossRefGoogle Scholar
Villamil, MB, Davis, VM and Nafziger, ED (2012) Estimating factor contributions to soybean yield from farm field data. Agronomy Journal 104, 881–887.CrossRefGoogle Scholar
Zhang, Z, Liao, H and Lucas, WJ (2014) Molecular mechanisms underlying phosphate sensing, signaling, and adaptation in plants. Journal of Integrative Plant Biology 56, 192–220.CrossRefGoogle ScholarPubMed