Evaluating soil and terrain variables in a production environment: implications for agricultural land assessment

Date
2022-12
Journal Title
Journal ISSN
Volume Title
Publisher
Stellenbosch : Stellenbosch University
Abstract
ENGLISH ABSTRACT: Agricultural land in South Africa is under increasing pressure to produce more food from an ever-shrinking land base, as more land is being converted to non-productive uses. Additional to these pressures, is the concept of land reform and strategic land acquisition, aimed at agrarian transform within the rural landscape. It is estimated that less than 15% of South Africa is suitable for dryland cultivation. Consequently, the sustainable utilisation of these scarce resources and preservation of agricultural land is of paramount importance, to ultimately ensure some measure of national food security in the years to come. Agricultural land evaluation is a critical tool that can achieve this goal. Unfortunately, in recent decades the development of revised or novel land evaluation methodologies has stalled for South African farm-level assessments, the scale at which land release decisions are made. Further, the relationship between productivity and individual land assessment attributes has not been adequately quantified or incorporated into contemporary local assessment procedures. It is envisaged that this study would influence and help guide in-field methodologies, as well as draft legislation and best-practice strategies, with a view of both standardising and improving agricultural land assessment techniques. By emphasising the importance of agricultural land and the accurate assessment thereof, this research also aims to increase our understanding of production-based approaches at an operational scale, though the novel combination of traditional approaches and use of newer technologies. It is anticipated that this improved understanding will be employed to not only protect more agricultural land, which may have been undervalued by historical methods, but also as an intuitive assessment tool to highlight the yield gap between potential and actual production levels. A review of pertinent literature identified the need for local verification studies to evaluate the performance of land assessment methodologies currently used in industry. To address this, five methods were verified using land assessment polygons in a commercial production environment, in the Province of KwaZulu-Natal, South Africa. The resultant classifications, derived from 225 soil observations, were compared to actual land use and precision yields achieved by dryland maize and soybean, across five growing seasons (2016 - 2020). By comparing land use with broad arability, four of the five land assessment methods were found to adequately classify arable land. Additionally, land evaluation polygons, linked to dryland precision maize and soybean yields can provide a general overview of method performance. However, it was concluded that yield performance and variation, across land evaluation methods and classes, is only explicit on or near a soil observation point where measurements are taken. Accordingly, seasonal variograms for maize and soybean were developed, to establish a representative yield buffer around individual soil observation points. This, along with yield normalisation strategies were employed, to improve verification procedures across multiple growing seasons. To determine crop productivity drivers, significant land assessment attributes inter alia slope, effective rooting depth, soil texture, soil group and soil wetness limitations were analysed against maize and soybean yields. It was found that the two crops respond differently to individual land assessment attributes and these differences should be taken cognisance of in new, crop-specific land evaluation methodologies and weighted accordingly. In an attempt to improve productivity-based land classification 78 attributes; derived from land assessment methodologies, digital terrain analysis, the pedological survey and soil colour spectrophotometry were collated. From these attributes, three new approaches, one based on biophysical scoring criteria and two based on machine learning, were developed across two commercial farming operations, in northern KwaZulu-Natal. These new methodologies were then tested on three separate commercial operations, located in different regions of the province. The biophysical scoring classification generally outperformed machine learning models and was particularly accurate when classifying observations associated with either extremely poor or extremely advantageous soil and terrain attributes. The transferability of the models to other regions, with different resources produced mixed results, highlighting the need for wider calibration in some instances. The study also found that the new productivity-based approaches can have useful applications in commercial farm management, where crop specific classification can identify underperforming areas and yields gaps, which can be ringfenced for appropriate interventions. The newly developed biophysical scoring classification was used to demonstrate the utility of these approaches in broader agricultural land release applications. The study found the new approaches better reflect production potential and should be used to supplement existing methodologies in land release assessments. Ultimately, the application of these production- based approaches can assist the land assessor to better classify the production potential of the land, as well as the decision-making authority to justify preserving more land for agricultural purposes.
AFRIKAANSE OPSOMMING: Landbougrond in Suid-Afrika is onder toenemende druk om meer voedsel van 'n steeds krimpende grondbasis te produseer, aangesien meer grond na nie-produktiewe gebruike omgeskakel word. Bykomend tot hierdie druk is die konsep van grondhervorming en strategiese grondverkryging, gemik op agrariese transformasie binne die landelike landskap. Daar word beraam dat minder as 15% van Suid-Afrika geskik is vir droëlandverbouing. Gevolglik is die volhoubare benutting van hierdie skaars hulpbronne en bewaring van landbougrond van kardinale belang, om uiteindelik 'n mate van nasionale voedselsekerheid in die komende jare te verseker. Landbougrond evaluering is 'n kritieke instrument wat hierdie doelwit kan bereik. Ongelukkig het die ontwikkeling van hersiene of nuwe grondevaluering metodologieë in die afgelope dekades vir Suid-Afrikaanse plaasvlak-assesserings, die skaal waarop besluite oor grondvrystelling geneem word, tot stilstand gekom. Verder is die verwantskap tussen produktiwiteit en individuele grondbeoordeling eienskappe nie voldoende gekwantifiseer nie, en ook nie ingesluit in kontemporêre plaaslike assessering prosedures nie. Daar word in die vooruitsig gestel dat hierdie studie in-veld metodologieë, sowel as konsep- wetgewing en beste-praktyk strategieë sal beïnvloed en help rig, met die oog op beide standaardisering en verbetering van landbougrond assessering tegnieke. Deur die belangrikheid van landbougrond en die akkurate beoordeling daarvan te beklemtoon, poog hierdie navorsing ook om ons begrip van produksie gebaseerde benaderings op 'n operasionele skaal te verhoog, al is die nuwe kombinasie van tradisionele benaderings en die gebruik van nuwer tegnologieë word is missing. Daar word verwag dat hierdie verbeterde begrip aangewend sal word om nie net meer landbougrond, wat moontlik deur historiese metodes onderwaardeer is, te beskerm nie, maar ook as 'n intuïtiewe assessering instrument om die opbrengsgaping tussen potensiële en werklike produksievlakke uit te lig. 'n Oorsig van toepaslike literatuur het die behoefte aan plaaslike verifikasie studies geïdentifiseer om die prestasie van grondbeoordeling metodologieë wat tans in die industrie gebruik word (removed comma) te evalueer. Om dit aan te spreek, is vyf metodes geverifieer deur gebruik te maak van grondevaluering poligone in 'n kommersiële produksie omgewing, in die provinsie KwaZulu-Natal, Suid-Afrika. Die gevolglike klassifikasies, afgelei van 225 grond waarnemings, is vergelyk met werklike grond-gebruik en presisie-opbrengste wat deur droëland-mielies en sojabone behaal is, oor vyf groeiseisoene (2016 - 2020). Deur grondgebruik met breë bewerkbaarheid te vergelyk, is vier van die vyf grondbeoordeling metodes gevind om bewerkbare grond voldoende te klassifiseer. Boonop kan grondevaluering poligone, gekoppel aan droëland-presisiemielies en sojaboon opbrengste, 'n algemene oorsig van metode prestasie verskaf. Daar is egter tot die gevolgtrekking gekom dat opbrengsprestasie en variasie, oor grondevaluering metodes en -klasse heen, slegs eksplisiet is op of naby 'n grondwaarnemingspunt waar metings geneem word. Gevolglik is seisoenale variogramme vir mielies en sojabone ontwikkel om 'n verteenwoordigende opbrengsbuffer rondom individuele grondwaarnemingspunte te vestig. Dit, tesame met opbrengs normalisering strategieë, is aangewend om verifikasie prosedures oor verskeie groei seisoene te verbeter. Om oesproduktiwiteit drywers te bepaal, is beduidende grondbeoordeling eienskappe, onder andere helling, effektiewe worteldiepte, grondtekstuur, grondgroep- en grondnat beperkings, ontleed teen mielie- en sojaboon opbrengste. Daar is gevind dat die twee gewasse verskillend reageer op individuele grondbeoordeling eienskappe en hierdie verskille moet in nuwe, gewas-spesifieke grondevaluering metodologieë in ag geneem word en dienooreenkomstig geweeg word. In 'n poging om produktiwiteit-gebaseerde grondklassifikasie te verbeter 78 eienskappe; afgelei van grondevaluering metodologieë, digitale terrein analise, die pedologiese opname en grondkleur spektrofotometrie is saamgestel. Uit hierdie eienskappe is drie nuwe benaderings, een gebaseer op biofisiese telling kriteria en twee gebaseer op masjienleer, ontwikkel oor twee kommersiële boerdery bedrywighede, in die noorde van KwaZulu-Natal. Hierdie nuwe metodologieë is toe getoets op drie afsonderlike kommersiële bedrywighede, geleë in verskillende streke van die provinsie. Die biofisiese punte-klassifikasie het oor die algemeen beter as masjienleer-modelle presteer en was besonder akkuraat wanneer waarnemings geassosieer met óf uiters swak óf uiters voordelige grond- en terrein kenmerke geklassifiseer is. Die oordraagbaarheid van die modelle na ander streke, met verskillende hulpbronne, het gemengde resultate opgelewer, wat die behoefte aan wyer kalibrasie in sommige gevalle beklemtoon. Die studie het ook bevind dat die nuwe produktiwiteit gebaseerde benaderings nuttige toepassings in kommersiële plaasbestuur kan hê, waar gewas-spesifieke klassifikasie onderpresterende gebiede en opbrengsgapings kan identifiseer, wat afgesper kan word vir toepaslike ingrypings. Die nuut ontwikkelde biofisiese punte-klassifikasie is gebruik om die nut van hierdie benaderings in breër landbougrond-vrystelling toepassings te demonstreer. Die studie het bevind die nuwe benaderings weerspieël produksie potensiaal beter en moet gebruik word om bestaande metodologieë in grondvrystelling evaluerings aan te vul. Uiteindelik kan die toepassing van hierdie produksie gebaseerde benaderings die grond beoordelaar help om die produksie potensiaal van die grond beter te klassifiseer, asook die besluitneming gesag om die behoud van meer grond vir landbou doeleindes te regverdig.
Description
Thesis (PhDAgric)--Stellenbosch University, 2022.
Keywords
Soils, Land evaluation, Soils -- Environmental aspects, Agricultural landscape management -- South Africa, Terrain evaluation, Agricultural land -- Evaluation, UCTD
Citation