Direct and indirect methods of estimating lucerne (Medicago sativa) yield

Makuni, Josiah (2019-12)

Thesis (MScAgric)--Stellenbosch University, 2019.

Thesis

ENGLISH ABSTRACT: Lucerne (Medicago sativa) is an important drought tolerant fodder crop which plays an important role in providing feed for livestock in South Africa. Currently, the standard method for determining fodder on offer is the cut-and-dry method, which is time consuming, costly and labour intensive. There is therefore a need to find alternative non-destructive methods that can be used to accurately estimate lucerne yield in a time-efficient manner. The aim of this study was to calibrate a rising plate meter (RPM), ceptometer, meter ruler and canopy cover using an unmanned aerial vehicle (UAV) to estimate lucerne herbage yield. Data was collected from January 2015 till February 2018 with a break from June 2016 to June 2017. The study trial was conducted from July 2017 to February 2018 on existing lucerne trial plots under full irrigation at the Elsenburg Research Farm outside Stellenbosch. The first objective was to determine yield potential of lucerne cultivars available commercially in South Africa. Herbage yield data for 2015 was used to determine yield potential of different cultivars. Dormancy class did not affect herbage production in this study. The second objective was to calibrate indirect methods namely RPM, ceptometer and meter ruler, for estimating lucerne yield. Linear and quadratic regressions were calculated to estimate the accuracy of the RPM, ceptometer and meter ruler. Coefficients of determination derived from three yield estimations were significant (p<0.05). The RPM had the best coefficient of determination of r2 = 0.69 (p<0.05) compared to the other instruments. Operation was fairly easy and it achieved its objective of cutting down on time. It worked best on the months where lucerne production was low. The ceptometer (r2 = 0.55) was highly weather dependent as it worked best on clear sunny days and was affected on days with clouds and morning dew. The meter ruler was quick and easy to use to collect data. However, it could not produce a high coefficient of determination (r2 = 0.50). The third objective was to develop ways to use digital data collected with a UAV for estimating lucerne yield. Linear and quadratic regressions were also calculated to estimate accuracy of the UAV canopy cover. The UAV canopy cover estimations produced the lowest coefficient of determination of r2 = 0.45 compared to the other instruments. The drought experienced in the Western Cape Province during 2017 and part of 2018 cut the data collection period down to seven months from the expected twelve months. For the current study, it was concluded the RPM could be the best yield estimation instrument for estimating yield albeit there is room for it to be calibrated to get higher yield estimation accuracy. It is recommended the study is repeated over a longer period to properly calibrate all yield estimation instruments over all seasons of the year.

AFRIKAANS OPSOMMING: Lusern (Medicago sativa) is ’n belangrike droogte-tolerante voergewas wat ’n belangrike rol in veeproduksiestelsels in Suid-Afrika speel. Huidiglik is die standaardmetode om ruvoerbeskikbaarheid te bepaal, die sny-en-droog-metode, wat tydrowend, duur en arbeidsintensief is. Daar is ‘n behoefte om alternatiewe, nie-destruktiewe metodes te vind wat akkurraat en op ‘n tyd-effektiewe manier, lusernopbrengs kan skat. Die doel van die studie was om die skyfmeter (RPM), septometer, meterstok en blaredakbedekking gemeet met ‘n onbemande lugvoertuig (UAV) te kalibreer om lusernopbrengs te bepaal. Data was van Januarie 2015 tot Februarie 2018 versamel, met ‘n breek van Junie 2016 tot Junie 2017. Die studie was uitgevoer op bestaande lusernpersele onder besproeiing by die Elsenburg Navorsingsplaas buite Stellenbosch. Die eerste doelwit was om die opbrengs van lusernkultivars wat kommersiëel beskikbaar in Suid-Afrika is, te bepaal. Opbrengsdata van 2015 was gebruik om opbrengspotenisaal van verskillende kultivars te bepaal. Dormansieklasse het nie ’n invloed op produksie in hierdie studie gehad nie. Die tweede doelwit was om die indirekte metodes, naamlik die RPM, septometer en meterstok te gebruik om opbrengs te bepaal. Liniêre en kwadratiese regressies was bereken om die akkuraatheid van die drie metodes te bepaal. Koëffisiente van bepalings was afgelei van drie opbrengsskattings, was betekensivol (p<0.05). Die RPM het die hoogste koëffisient gehad van r2 = 0.69 (p<0.05), vergeleke met die ander instrumente. Hantering van die RPM was redelik eenvoudig en tyd-effektief. Die effektiwiteit was egter die beste in maande wanneer lusernproduksie laag was. Die septometer (r2 = 0.55) het afgehang van die weersomstandighede en het die beste op sonnige dae gewerk, en was die meeste beinvloed op oortrokke dae en deur oggenddou. Die meterstok was maklik en eenvoudig om te gebruik, maar kon nie ‘n hoë koëffisient (r2 = 0.50) produseer nie. Die derde doelwit was om maniere om digitale data wat deur ’n UAV versamel was, te ontwikkel om lusernopbrengs te bepaal. Liniêre en kwadratiese regressies was ook gebruik om lusernopbrengs en die blaredak te korrelaar. Die UAV-skattings het die laagste koëffisient van r2 = 0.45 tot gevolg gehad. Die droogte wat in die Wes-Kaap gedurende 2017 en 2018 ondervind was, het veroorsaak dat die dataversamelingstyd van 12 na sewe maande verkort was. Die gevolgtrekking was dat die RPM die beste opbrengskattingsinstrument was, alhoewel daar nog plek vir verbetering is om nog beter akkuraatheid te verseker. Dit word aanbeveel dat die studie herhaal word oor ‘n langer tyd om die inligting verder te verfyn.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/107325
This item appears in the following collections: