000086155 001__ 86155 000086155 005__ 20200117221645.0 000086155 0247_ $$2doi$$a10.2134/agronj2017.12.0680 000086155 0248_ $$2sideral$$a113294 000086155 037__ $$aART-2018-113294 000086155 041__ $$aeng 000086155 100__ $$0(orcid)0000-0002-0167-0343$$aMalik, Wafa 000086155 245__ $$aAdapting the CROPGRO model to simulate alfalfa growth and yield 000086155 260__ $$c2018 000086155 5060_ $$aAccess copy available to the general public$$fUnrestricted 000086155 5203_ $$aDespite alfalfa’s global importance, there is a dearth of crop simulation models available for predicting alfalfa growth and yield with its associated composition. The objectives of this research were to adapt the CSM-CROPGRO Perennial Forage Model for simulating alfalfa growth and yield and to describe model adaptation for this species. Data from six experimental plots grown under sprinkler irrigation in the Ebro valley (Northeast Spain) were used for model adaptation. Starting with parameters for Bracharia brizantha, the model adaptation was based on values and relationships reported from the literature for cardinal temperatures and dry matter partitioning. A Bayesian optimizer was used to optimize temperature effects on photosynthesis and daylength effects on partitioning and an inverse modeling technique was employed for nitrogen fixation rate and nodule growth. The calibration of alfalfa tissue composition was initiated from soybean composition analogy but was improved with values from alfalfa literature. There was considerable iteration in optimizing parameters for the processes outlined above where comparisons were made to measured data. After adaptation, the Root Mean Square Error and d-statistic of harvested herbage averaged across 58 harvests (yield range: 990-4617 kg ha-1) were 760 kg ha-1 and 0.75, respectively. In addition, good agreement was observed for Leaf Area Index (LAI) (LAI range: 0.1-6.7) with d-statistic of 0.71. Simulated belowground mass was within the range of literature values. The results of this study showed that CROPGRO-PFM-Alfalfa can be used to simulate alfalfa growth and development. Further testing with more extensive datasets is needed to improve model robustness. 000086155 536__ $$9info:eu-repo/grantAgreement/ES/MICINN/AGL2013-48728-C2-2-R 000086155 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/ 000086155 590__ $$a1.805$$b2018 000086155 591__ $$aAGRONOMY$$b28 / 89 = 0.315$$c2018$$dQ2$$eT1 000086155 592__ $$a1.049$$b2018 000086155 593__ $$aAgronomy and Crop Science$$c2018$$dQ1 000086155 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000086155 700__ $$aBoote, Kenneth J. 000086155 700__ $$aHoogemboom, Gerrit 000086155 700__ $$aCavero, José 000086155 700__ $$aDechmi, Farida 000086155 773__ $$g110, 5 (2018), 1777-1790$$pAgron. j.$$tAgronomy journal$$x0002-1962 000086155 8564_ $$s353157$$uhttps://zaguan.unizar.es/record/86155/files/texto_completo.pdf$$yVersión publicada 000086155 8564_ $$s123705$$uhttps://zaguan.unizar.es/record/86155/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000086155 909CO $$ooai:zaguan.unizar.es:86155$$particulos$$pdriver 000086155 951__ $$a2020-01-17-22:06:26 000086155 980__ $$aARTICLE