guest ::
| Home > Publications database > Monitoring and Modelling Analysis of Maize (Zea mays L.) Yield Gap in Smallholder Farming in Ghana > print |
| Home > Publications database > Monitoring and Modelling Analysis of Maize (Zea mays L.) Yield Gap in Smallholder Farming in Ghana > print |
| 001 | 884768 | ||
| 005 | 20210130005934.0 | ||
| 024 | 7 | _ | |a 10.3390/agriculture10090420 |2 doi |
| 024 | 7 | _ | |a 2128/26137 |2 Handle |
| 024 | 7 | _ | |a altmetric:91024255 |2 altmetric |
| 024 | 7 | _ | |a WOS:000578205100001 |2 WOS |
| 037 | _ | _ | |a FZJ-2020-03244 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 570 |
| 100 | 1 | _ | |a Owusu Danquah, Eric |0 P:(DE-HGF)0 |b 0 |
| 245 | _ | _ | |a Monitoring and Modelling Analysis of Maize (Zea mays L.) Yield Gap in Smallholder Farming in Ghana |
| 260 | _ | _ | |a Basel |c 2020 |b MDPI AG |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1605275523_16532 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Modelling and multiple linear regression were used to explore the reason for low maize yield in the Atebubu-Amantin and West Mamprusi Districts of Ghana, West Africa. The study evaluated maize yields on twenty farms against measures of soil fertility, agronomic attributes and soil water availability. Correlations between yield, soil fertility, rain, crop density, and weed biomass, were low, and no single factor could explain the low yields. A 50-year virtual experiment was then set up using the Agricultural Production Systems Simulator (APSIM) to explore the interactions between climate, crop management (sowing date and nitrogen fertilization) and rooting depth on grain yield and nitrate (NO3-N) dynamics. The analysis showed that a lack of optimal sowing dates that synchronize radiation, rainfall events and nitrogen (N) management with critical growth stages explained the low farm yields. |
| 536 | _ | _ | |a 582 - Plant Science (POF3-582) |0 G:(DE-HGF)POF3-582 |c POF3-582 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef |
| 700 | 1 | _ | |a Beletse, Yacob |0 P:(DE-HGF)0 |b 1 |e Corresponding author |
| 700 | 1 | _ | |a Stirzaker, Richard |0 0000-0001-6956-4179 |b 2 |
| 700 | 1 | _ | |a Smith, Christopher |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Yeboah, Stephen |0 P:(DE-HGF)0 |b 4 |
| 700 | 1 | _ | |a Oteng-Darko, Patricia |0 P:(DE-HGF)0 |b 5 |
| 700 | 1 | _ | |a Frimpong, Felix |0 P:(DE-Juel1)173985 |b 6 |
| 700 | 1 | _ | |a Ennin, Stella Ama |0 P:(DE-HGF)0 |b 7 |
| 773 | _ | _ | |a 10.3390/agriculture10090420 |g Vol. 10, no. 9, p. 420 - |0 PERI:(DE-600)2651678-0 |n 9 |p 420 - |t Agriculture |v 10 |y 2020 |x 2077-0472 |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/884768/files/agriculture-10-00420-v2.pdf |
| 856 | 4 | _ | |y OpenAccess |x pdfa |u https://juser.fz-juelich.de/record/884768/files/agriculture-10-00420-v2.pdf?subformat=pdfa |
| 909 | C | O | |o oai:juser.fz-juelich.de:884768 |p openaire |p open_access |p VDB |p driver |p dnbdelivery |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 6 |6 P:(DE-Juel1)173985 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Key Technologies for the Bioeconomy |1 G:(DE-HGF)POF3-580 |0 G:(DE-HGF)POF3-582 |2 G:(DE-HGF)POF3-500 |v Plant Science |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |
| 914 | 1 | _ | |y 2020 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2019-12-21 |
| 915 | _ | _ | |a Creative Commons Attribution CC BY 4.0 |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1060 |2 StatID |b Current Contents - Agriculture, Biology and Environmental Sciences |d 2019-12-21 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0501 |2 StatID |b DOAJ Seal |d 2019-12-21 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0500 |2 StatID |b DOAJ |d 2019-12-21 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |d 2019-12-21 |
| 915 | _ | _ | |a Fees |0 StatID:(DE-HGF)0700 |2 StatID |d 2019-12-21 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2019-12-21 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b DOAJ : Blind peer review |d 2019-12-21 |
| 915 | _ | _ | |a Article Processing Charges |0 StatID:(DE-HGF)0561 |2 StatID |f 2019-12-21 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0310 |2 StatID |b NCBI Molecular Biology Database |d 2019-12-21 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2019-12-21 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2019-12-21 |
| 920 | 1 | _ | |0 I:(DE-Juel1)IBG-2-20101118 |k IBG-2 |l Pflanzenwissenschaften |x 0 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)IBG-2-20101118 |
| 980 | 1 | _ | |a FullTexts |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|