Yıl: 2023 Cilt: 47 Sayı: 6 Sayfa Aralığı: 1078 - 1098 Metin Dili: İngilizce DOI: 10.55730/1300-011X.3149 İndeks Tarihi: 14-03-2024

Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan

Öz:
Crop growth models can be valuable tools for researchers, academia, extension educators, and policy makers/planners for the evaluation of sustainable and long-term husbandry practices. Determining the optimum sowing window, which can be determined using crop growth models, is imperative under changing climate conditions. Thus, the main objectives herein were to 1) assess the performance of the cropping system model-crop environment resource synthesis-maize model for hybrids and sowing dates in the spring and autumn, and 2) determine the optimum sowing window in 15 districts of Punjab, Pakistan. In the spring experiment, 3 hybrids (P-33M15, M-DK6525, and S-NK8441) were planted in the main plots and then on 5 different sowing dates (January 15th, February 5th, February 25th, March 15th, and April 5th), they were planted in the subplots. In the autumn experiment, 3 hybrids (P-30R50, M-DK6714, and S-NK6621) were planted in the main plots and then on 5 different sowing dates (June 15th, July 5th, July 25th, August 15th, and September 5th), they were planted in the subplots. Model calibration and evaluation results were better in the spring and autumn. Performance of the model was good for the grain yield in the autumn (mean percentage difference (MPD): 7.47% to 8.90%) compared to the spring (MPD: 9.42% to 11.72%). Model evaluation was good for the early sowing dates (January 15th and February 5th) (error range: 6.26% to 9.65%) compared to the delayed dates (February 25th to April 5th) (error range: 9.34 to 14.91%). In the autumn, the model showed better performance for the delayed sowing dates (February 25th and August 15th) (error range: 5.22% to 9.43%) compared to the early dates (June 15th and July 5th) (error range: 8.56% to 11.27%). The model simulated good growth, development, grain yield, and yield components in the spring and autumn and of both 2016 and 2017. For the model application simulation of data over the long-term (1980 to 2017), the optimum sowing window in the spring was January 15th to March 5th and for the autumn it was July 23rd to August 27th for the 15 districts in Punjab, Pakistan. Simulation of the sowing dates for the whole year indicated that the spring was better compared to the autumn for obtaining the maximum grain yield. The results of the model were in line with the recommendations of the agricultural extension department for the sowing window for spring and autumn maize. It is therefore suggested that farmers should complete the sowing of spring and autumn maize within the sowing window to attain a higher yield of maize in arid and semiarid areas of Punjab, Pakistan.
Anahtar Kelime: Cropping system model Zea mays L. DSSAT hybrid maize spring autumn grain yield

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
  • Abbas G, Ahmad S, Ahmad A, Nasim W, Fatima Z et al. (2017). Quantification the impacts of climate change and crop management on phenology of maize-based cropping system in Punjab, Pakistan. Agricultural and Forest Meteorology 247: 42- 55. https://doi.org/10.1016/j.agrformet.2017.07.012
  • Abbas G, Ahmad S, Hussain M, Fatima Z, Hussain S et al. (2020a). Sowing date and hybrid choice matters production of maize– maize system. International Journal of Plant Production 14 (4): 583-595. https://doi.org/10.1007/s42106-020-00104-6
  • Abbas G, Fatima Z, Riaz F, Iqbal P, Hussain S et al. (2019). Study of sowing dates and hybrids effect in maize-based cropping system under arid conditions of Southern Punjab, Pakistan. Pakistan Journal of Life and Social Sciences 17 (1): 24-31.
  • Abbas G, Ahmed M, Fatima Z, Hussain S, Kheir AMS et al (2023). Modeling the potential impact of climate change on maize-maize cropping system in semi-arid environment and designing of adaptation options. Agricultural and Forest Meteorology 341: 109674.
  • Abbas G, Fatima Z, Tariq M, Ahmed M, Rahman MH et al. (2020b). Applications of crop modeling in cotton production. In: Cotton Production and Uses (pp. 429-445) Singapore: Springer. https:// doi.org/10.1007/978-981-15-1472-2_21
  • Abdala LJ, Gambin BL, Borras L (2018). Sowing date and maize grain quality for dry milling. European Journal of Agronomy 92: 1-8. https://doi.org/10.1016/j.eja.2017.09.013
  • Adnan AA, Diels J, Jibrin JM, Kamara AY, Craufurd P et al. (2019) Options for calibrating CERES-maize genotype specific parameters under data-scarce environments. PloS One 14 (2): e0200118. https://doi.org/10.1371/journal.pone.0200118
  • Adnan AA, Jibrin JM, Abdulrahman BL, Shaibu AS, Garba II (2017). CERES-maize model for determining the optimum planting dates of early maturing maize varieties in northern Nigeria. Frontiers in Plant Sciences 8: 1118. https://doi.org/10.3389/ fpls.2017.01118
  • Afzal MN, Tariq M, Ahmed M, Abbas G, Mehmood Z (2020). Managing planting time for cotton production. In: Ahmad S, Hasannazuman M (editors) Cotton Production and Uses (pp. 31-44) Singapore: Springer. https://doi.org/10.1007/978-981-15- 1472-2_3
  • Ali W, Ali M, Ahmad Z, Igbal J, Anwar S (2018). Influence of sowing dates on varying maize ( Zea mays L.) varieties grown under agro-climatic condition of Peshawar, Pakistan. European Journal of Experimental Biology 8 (6): 36. https://doi.org/10.21767/2248- 9215.100077
  • Amouzou KA, Naab JB, Lamers JP, Becker M (2018). CERES-maize and CERES-sorghum for modeling growth, nitrogen and phosphorus uptake, and soil moisture dynamics in the dry savanna of West Africa. Field Crops Research 217: 134-149. https://doi. org/10.1016/j.fcr.2017.12.017
  • Araya A, Hoogenboom G, Luedeling E, Hadgu KM, Kisekka I et al. (2017). Assessment of maize growth and yield using crop models under present and future climate in southwestern Ethiopia. Agricultural and Forest Meteorology 214: 252-265. https://doi. org/10.1016/j.agrformet.2015.08.259
  • Bao Y, Hoogenboom G, McClendon R, Vellidis G (2017). A comparison of the performance of the CSM-CERES-maize and EPIC models using maize variety trial data. Agricultural Systems 150: 109-119. https://doi.org/10.1016/j.agsy.2016.10.006
  • Basso B, Liu L, Ritchie JT (2016). A comprehensive review of the CERES-wheat, -maize and-rice models’ performances. Advances in Agronomy 136: 27-132. https://doi.org/10.1016/ bs.agron.2015.11.004
  • Bonelli LE, Monzon JP, Cerrudo A, Rizzalli RH, Andrade FH (2016). Maize grain yield components and source-sink relationship as affected by the delay in sowing date. Field Crops Research 198: 215-225. https://doi.org/10.1016/j.fcr.2016.09.003
  • Caubel J, de Cortazar-Atauri IG, Vivant AC, Launay M, de Noblet- Ducoudre N (2018). Assessing future meteorological stresses for grain maize in France. Agricultural Systems 159: 237-247. https://doi.org/10.1016/j.agsy.2017.02.010
  • Corbeels M, Chirat G, Messad S, Thierfelder C (2016). Performance and sensitivity of the DSSAT crop growth model in simulating maize yield under conservation agriculture. European Journal of Agronomy 76: 41-53. https://doi.org/10.1016/j.eja.2016.02.001
  • Dobor L, Barcza Z, Hlasny T, Árendas T, Spitko T et al. (2016). Crop planting date matters: estimation methods and effect on future yields. Agricultural and Forest Meteorology 223: 103-115. https://doi.org/10.1016/j.agrformet.2016.03.023
  • Dokoohaki H, Gheysari M, Mousavi SF, Zand-Parsa S, Miguez FE et al. (2016). Coupling and testing a new soil water module in DSSAT CERES-Maize model for maize production under semi-arid condition. Agricultural Water Management 163: 90-99. https:// doi.org/10.1016/j.agwat.2015.09.002
  • Dzotsi K, Agboh-Noameshie A, Struif Bontkes TE, Singh U, Dejean P et al. (2003). Using DSSAT to derive optimum combinations of cultivar and sowing date for maize in southern Togo. In: Bontkes T, Wopereis M (editors). Decision Support Tools for Smallholder Agriculture in Sub-Saharan Africa; A Practical Guide. IFDC Muscle Shoals, USA, and CTA, Wageningen, pp.100-112.
  • Fatima Z, Ahmed M, Hussain M, Abbas G, Ul-Allah S et al. (2020). The fingerprints of climate warming on cereal crops phenology and adaptation options. Scientific Reports 10 (1): 1-21. https:// doi.org/10.1038/s41598-020-74740-3
  • Fujisao K, Khanthavong P, Oudthachit S, Matsumoto N, Homma K et al. (2018). A study on the productivity under the continuous maize cultivation in Sainyabuli Province, Laos I. Yield trend under continuous maize cultivation. Field Crops Research 217: 167-171. https://doi.org/10.1016/j.fcr.2017.12.016
  • GOP (Government of Pakistan) (2020). Economic survey of Pakistan 2019-2020, finance division, economic advisory wing, Islamabad, Pakistan, pp. 22.
  • Hammad HM, Abbas F, Ahmad A, Farhad W, Anothai J et al. (2018). Predicting water and nitrogen requirements for maize under semi-arid conditions using the CSM-CERES-maize model. European Journal of Agronomy 100: 56-66. https://doi. org/10.1016/j.eja.2017.10.008
  • Hammad HM, Ahmad A, Farhad W, Abbas F, Qasim K et al. (2013). Nitrogen stimulates phenological traits, growth and growing degree days of maize. Pakistan Journal of Agricultural Sciences 50 (3): 337-344.
  • Hoogenboom G., Porter CH, Shelia V, Boote KJ, Singh U et al. (2021). Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.7.5 (https://DSSAT.net) DSSAT Foundation, Gainesville, Florida, USA.
  • Huang C, Liu Q, Li H, Li X, Zhang C et al. (2018). Optimised sowing date enhances crop resilience towards size-asymmetric competition and reduces the yield difference between intercropped and sole maize. Field Crops Research 217: 125- 133. https://doi.org/10.1016/j.fcr.2017.12.010
  • Hunt R (2012). Basic growth analysis: plant growth analysis for beginners. Springer Science and Business Media. https://doi. org/10.1007/978-94-010-9117-6
  • Jin H, Li A, Wang J, Bo Y (2016). Improvement of spatially and temporally continuous crop leaf area index by integration of CERES-maize model and MODIS data. European Journal of Agronomy 78: 1-12. https://doi.org/10.1016/j.eja.2016.04.007
  • Jing Q, Shang J, Huffman T, Qian B, Pattey E et al. (2017). Using the CSM-CERES-maize model to assess the gap between actual and potential yields of grain maize. Journal of Agricultural Sciences 155 (2): 239-260. https://doi.org/10.1017/ S0021859616000290
  • Jones JW, Hoogenboom G, Porter CH, Boote KJ, Batchelor WD et al. (2003). The DSSAT cropping system model. European Journal of Agronomy 18 (3-4): 235-265. https://doi. org/10.1016/S1161-0301(02)00107-7
  • Júnior RDSN, Sentelhas PC (2019). Soybean-maize succession in Brazil: Impacts of sowing dates on climate variability, yields and economic profitability. European Journal of Agronomy 103: 140-151. https://doi.org/10.1016/j.eja.2018.12.008
  • Khalid MHB, Cui L, Abbas G, Raza MA, Anwar A et al. (2023) Effect of row spacing under maize-soybean relay intercropping system on yield, competition, and economic returns. Turkish Journal of Agriculture and Forestry 47: 390-401. https://doi. org/10.55730/1300-011X.3095
  • Li ZT, Yang JY, Drury CF, Hoogenboom G (2015). Evaluation of the DSSAT-CSM for simulating yield and soil organic C and N of a long-term maize and wheat rotation experiment in the Loess Plateau of northwestern China. Agricultural Systems 135: 90-104. https://doi.org/10.1016/j.agsy.2014.12.006
  • Long NV, Assefa Y, Schwalbert R, Ciampitti IA (2017). Maize yield and planting date relationship: A synthesis-analysis for US high-yielding contest-winner and field research data. Frontiers in Plant Sciences 8, https://doi.org/10.3389/ fpls.2017.02106
  • Lu HD, Xue JQ, Guo DW (2017). Efficacy of planting date adjustment as a cultivation strategy to cope with drought stress and increase rainfed maize yield and water-use efficiency. Agricultural Water Management 179: 227-235. https://doi.org/10.1016/j.agwat.2016.09.001
  • MacCarthy DS, Adiku SG, Freduah BS, Gbefo F (2017). Using CERES-maize and ENSO as decision support tools to evaluate climate-sensitive farm management practices for maize production in the northern regions of Ghana. Frontiers in Plant Sciences 8: 31. https://doi.org/10.3389/fpls.2017.00031
  • Malik W, Isla R, Dechmi F (2019). DSSAT-CERES-maize modelling to improve irrigation and nitrogen management practices under Mediterranean conditions. Agricultural Water Management 213: 298-308. https://doi.org/10.1016/j.agwat.2018.10.022
  • Mason S, Galusha T, Kmail Z (2017) Planting date influence on yield of drought-tolerant maize with different maturity classifications. Agronomy Journal 110 (1): 293-299. https://doi. org/10.2134/agronj2017.06.0326
  • Mubarak MK, Hussain K, Abbas G, Altaf MT, Baloch FS et al. (2022) Productivity of sorghum (Sorghum bicolar L.) at diverse irrigation regimes and sowing dates in semi-arid and arid environment. Turkish Journal of Agriculture and Forestry 46 (1): 1-18. https://doi.org/10.3906/tar-2106-18
  • Mubeen M, Ahmad A, Wajid A, Khaliq T, Bakhsh A (2013). Evaluating CSM-CERES-maize model for irrigation scheduling in semi- arid conditions of Punjab, Pakistan. International Journal of Agriculture and Biology 15 (1): 1-10.
  • Mubeen M, Ahmad A, Wajid A, Khaliq T, Hammad HM et al. (2016). Application of CSM-CERES-maize model in optimizing irrigated conditions. Outlook in Agriculture 45 (3): 173-184. https://doi.org/10.1177/0030727016664464
  • Naz S, Ahmad S, Abbas G, Fatima Z, Hussain S et al. (2022) Modeling the impact of climate warming on potato phenology. European Journal of Agronomy 132: 126404. https://doi.org/10.1016/j. eja.2021.126404
  • Parker PS, Shonkwiler JS, Aurbacher J (2017). Cause and consequence in maize planting dates in Germany. Journal of Agronomy and Crop Science 203 (3): 227-240. https://doi.org/10.1111/ jac.12182
  • Peng B, Guan K, Chen M, Lawrence DM, Pokhrel Y et al. (2018). Improving maize growth processes in the community land model: Implementation and evaluation. Agricultural and Forest Meteorology 250: 64-89. https://doi.org/10.1016/j. agrformet.2017.11.012
  • Perondi D, Fraisse CW, Staub CG, Cerbaro VA, Barreto DD et al. (2019). Crop season planning tool: adjusting sowing decisions to reduce the risk of extreme weather events. Computer and Electronics in Agriculture 156: 62-70.https://doi.org/10.1016/j. compag.2018.11.013
  • Qamar R, Atique-ur-Rehman, Javeed HMR , Rehman A , Safdar ME et al. (2021) Tillage systems affecting rice-wheat cropping system. Sains Malaysiana 50 (6): 1543-1562. https:// doi.org/10.17576/jsm-2021-5006-04
  • Raza MA, Cui L, Khan I, Din AM, Chen G et al. (2021a) Compact maize canopy improves radiation use efficiency and grain yield of maize/soybean relay intercropping system. Environmental Science and Pollution Research 28 (30): 41135-41148. https:// doi.org/10.1007/s11356-021-13541-1
  • Raza MA, Gul H, Wang J, Yasin HS, Qin R et al. (2021b) Land productivity and water use efficiency of maize soybean strip intercropping systems in semiarid areas. Journal of Cleaner Production 308: 127282. https://doi.org/10.1016/j. jclepro.2021.127282
  • Raza MA, Yasir HS, Gul H, Qin R, Din AM et al. (2022) Maize/soybean strip intercropping produces higher crop yields and saves water under semi-arid conditions. Frontiers in Plant Science 13: 1006720. https://doi.org/10.3389/fpls.2022.1006720
  • Saddique Q, Cai H, Ishaque W, Chen H, Chau HW et al. (2019). Optimizing the sowing date and irrigation strategy to improve maize yield by using CERES (crop estimation through resource and environment synthesis)-maize model. Agronomy 9 (2): 109. https://doi.org/10.3390/agronomy9020109
  • Sarwar N, Atique-ur-Rehman, Farooq O, Wasaya A, Hussain M et al. (2021) Integrated nitrogen management improves productivity and economic returns of wheat-maize cropping system. Journal of King Saud University-Science 33: 101475. https:// doi.org/10.1016/j.jksus.2021.101475
  • Saxton KE, Rawls WJ (2006) Soil water characteristic estimates by texture and organic matter for hydrologic solutions. Soil Science Society of America Journal 70: 1569-1578. https://doi. org/10.2136/sssaj2005.0117
  • Seidel SJ, Palosuo T, Thorburn P, Wallach D (2018). Towards improved calibration of crop models–Where are we now and where should we go? European Journal of Agronomy 94: 25-35. https://doi.org/10.1016/j.eja.2018.01.006
  • Seyoum S, Rachaputi R, Chauhan Y, Prasanna B, Fekybelu S (2018). Application of the APSIM model to exploit G × E × M interactions for maize improvement in Ethiopia. Field Crops Research 217: 113-124. https://doi.org/10.1016/j. fcr.2017.12.012
  • Shelia V, Simunek J, Boote KJ, Hoogenboom G (2018). Coupling DSSAT and HYDRUS-1D for simulations of soil water dynamics in the soil-plant-atmosphere system. Journal of Hydrology and Hydromechanics 66 (2): 232-245. https://doi. org/10.1515/johh-2017-0055
  • Singh G, Lone BA, Dar ZA, Singh P, Fayaz A et al. (2017). Simulating date of sowing in maize ( Zea mays L.) under irrigated conditions using CERES-maize model. International Journal of Pure and Applied Biosciences 5 (4): 980-993. http://doi. org/10.18782/2320-7051.4016
  • Solar CMT, Hoogenboom G, Sentelhas PC, Duarte AP (2007). Impact of water stress on maize grown off-season in a subtropical environment. Journal of Agronomy and Crop Science 193: 247-261. https://doi.org/10.1111/j.1439-037X.2007.00265.x
  • Srivastava RK, Panda RK, Chakraborty A, Halder D (2017). Enhancing grain yield, biomass and nitrogen use efficiency of maize by varying sowing dates and nitrogen rate under rainfed and irrigated conditions. Field Crops Research 221: 339-349. https://doi.org/10.1016/j.fcr.2017.06.019
  • Tsimba R, Edmeades GO, Millner JP, Kemp PD (2013). The effect of planting date on maize grain yields and yield components. Field Crops Research 150: 135-144. https://doi.org/10.1016/j. fcr.2013.05.028
  • Wang N, Wang E, Wang J, Zhang J, Zheng B et al. (2018). Modelling maize phenology, biomass growth and yield under contrasting temperature conditions. Agricultural and Forest Meteorology 250: 319-329. https://doi.org/10.1016/j.agrformet.2018.01.005
  • Wolf J, Ouattara K, Supit I (2015). Sowing rules for estimating rainfed yield potential of sorghum and maize in Burkina Faso. Agricultural and Forest Meteorology 214: 208-218. https://doi. org/10.1016/j.agrformet.2015.08.262
  • Yakoub A, Lloveras J, Biau A, Lindquist JL, Lizaso JI (2017). Testing and improving the maize models in DSSAT: development, growth, yield, and N uptake. Field Crops Research 212: 95-106. https://doi.org/10.1016/j.fcr.2017.07.002
  • Yang JM, Yang JY, Liu S, Hoogenboom G (2014). An evaluation of the statistical methods for testing the performance of crop models with observed data. Agricultural Systems 127: 81-89. https://doi.org/10.1016/j.agsy.2014.01.008
  • Zhao J, Yang X (2018). Distribution of high-yield and high-yield- stability zones for maize yield potential in the main growing regions in China. Agricultural and Forest Meteorology 248: 511-517. https://doi.org/10.1016/j.agrformet.2017.10.016
  • Zheng Z, Cai H, Yu L, Hoogenboom G (2017). Application of the CSM-CERES-wheat model for yield prediction and planting date evaluation at Guanzhong Plain in northwest China. Agronomy Journal 109 (1): 204-217. https://doi.org/10.2134/ agronj2016.05.0289
APA Abbas G, A, Sarwar N, Fatima Z, Hussain S, AHMED M, Raza D, KAN M, Doğan H, Khan M, Ahmad S (2023). Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan. , 1078 - 1098. 10.55730/1300-011X.3149
Chicago Abbas Ghulam, Atique,Sarwar Naeem,Fatima Zartash,Hussain Sajjad,AHMED MUKHTAR,Raza Dr. Muhammad Ali,KAN MUSTAFA,Doğan Hülya,Khan Muhammad Azam,Ahmad Shakeel Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan. (2023): 1078 - 1098. 10.55730/1300-011X.3149
MLA Abbas Ghulam, Atique,Sarwar Naeem,Fatima Zartash,Hussain Sajjad,AHMED MUKHTAR,Raza Dr. Muhammad Ali,KAN MUSTAFA,Doğan Hülya,Khan Muhammad Azam,Ahmad Shakeel Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan. , 2023, ss.1078 - 1098. 10.55730/1300-011X.3149
AMA Abbas G, A,Sarwar N,Fatima Z,Hussain S,AHMED M,Raza D,KAN M,Doğan H,Khan M,Ahmad S Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan. . 2023; 1078 - 1098. 10.55730/1300-011X.3149
Vancouver Abbas G, A,Sarwar N,Fatima Z,Hussain S,AHMED M,Raza D,KAN M,Doğan H,Khan M,Ahmad S Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan. . 2023; 1078 - 1098. 10.55730/1300-011X.3149
IEEE Abbas G, A,Sarwar N,Fatima Z,Hussain S,AHMED M,Raza D,KAN M,Doğan H,Khan M,Ahmad S "Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan." , ss.1078 - 1098, 2023. 10.55730/1300-011X.3149
ISNAD Abbas, Ghulam vd. "Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan". (2023), 1078-1098. https://doi.org/10.55730/1300-011X.3149
APA Abbas G, A, Sarwar N, Fatima Z, Hussain S, AHMED M, Raza D, KAN M, Doğan H, Khan M, Ahmad S (2023). Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan. Turkish Journal of Agriculture and Forestry, 47(6), 1078 - 1098. 10.55730/1300-011X.3149
Chicago Abbas Ghulam, Atique,Sarwar Naeem,Fatima Zartash,Hussain Sajjad,AHMED MUKHTAR,Raza Dr. Muhammad Ali,KAN MUSTAFA,Doğan Hülya,Khan Muhammad Azam,Ahmad Shakeel Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan. Turkish Journal of Agriculture and Forestry 47, no.6 (2023): 1078 - 1098. 10.55730/1300-011X.3149
MLA Abbas Ghulam, Atique,Sarwar Naeem,Fatima Zartash,Hussain Sajjad,AHMED MUKHTAR,Raza Dr. Muhammad Ali,KAN MUSTAFA,Doğan Hülya,Khan Muhammad Azam,Ahmad Shakeel Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan. Turkish Journal of Agriculture and Forestry, vol.47, no.6, 2023, ss.1078 - 1098. 10.55730/1300-011X.3149
AMA Abbas G, A,Sarwar N,Fatima Z,Hussain S,AHMED M,Raza D,KAN M,Doğan H,Khan M,Ahmad S Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan. Turkish Journal of Agriculture and Forestry. 2023; 47(6): 1078 - 1098. 10.55730/1300-011X.3149
Vancouver Abbas G, A,Sarwar N,Fatima Z,Hussain S,AHMED M,Raza D,KAN M,Doğan H,Khan M,Ahmad S Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan. Turkish Journal of Agriculture and Forestry. 2023; 47(6): 1078 - 1098. 10.55730/1300-011X.3149
IEEE Abbas G, A,Sarwar N,Fatima Z,Hussain S,AHMED M,Raza D,KAN M,Doğan H,Khan M,Ahmad S "Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan." Turkish Journal of Agriculture and Forestry, 47, ss.1078 - 1098, 2023. 10.55730/1300-011X.3149
ISNAD Abbas, Ghulam vd. "Deciding sowing-window for maize-based cropping system in arid and semiarid environments in Punjab, Pakistan". Turkish Journal of Agriculture and Forestry 47/6 (2023), 1078-1098. https://doi.org/10.55730/1300-011X.3149