Evaluating the Effect of Intercropping Maize (Zea mays L.) with Different Lablab (Lablab purpureus L.) Cultivars on Yield, Soil Water Content and Soil Nitrogen in Dry Environments of Limpopo Province using APSIM Model

Abstract

Smallholder maize production systems are characterized by continuous maize monoculture production, which often leads to soil degradation, nutrient depletion and increased risk of pests and diseases. The cropping system is characterized by low yields that continue to decline due to soil degradation and increased temperatures coupled with poor rains. The integration of drought tolerant crops, such as lablab, into predominantly maize monoculture systems presents a better alternative to maize monoculture. Lablab is native to Africa but remains overlooked in many countries including South Africa, due to lack of information and access to seeds. Crop models, such as APSIM, are useful decision-making tools for investigating crop adaptability to various climates, management, and cropping systems. The objective of this study was therefore to assess the performance of maize and lablab under sole and intercropping systems and to evaluate the capability of APSIM to simulate crop yields in dry environments of Limpopo province, South Africa. Field experiments were conducted at the University of Limpopo Experimental Farm (Syferkuil) (2018/2019) and at University of Venda Experimental Farm (Univen) (2018/2019 and 2019/2020). Treatments consisted of maize cultivar (DKC-2147) and three lablab cultivars (DL-1002, Rongai (brown) and Q-6880B) planted as sole crops and intercrops. The treatments were laid out in a randomized complete block design with three replicates. Maize and lablab dry biomass (roots and shoots) and grain yield were assessed. Biomass was evaluated at respective flowering and harvest maturity dates for lablab and maize. Harvest index (HI) and land equivalent ratio (LER) were determined from shoot biomass and grain yield collected at harvest maturity. Soil mineral nitrogen (SMN) and soil water content (SWC) were determined at different maize growth stages. Biomass and grain yield of maize-lablab intercrops was evaluated using APSIM and observed data collected from the field experiments. Data obtained was subjected to analysis of variance using the general linear model procedure of Statistix software version 10.0. Means were compared using critical values of comparison at a 5% level of significance. Intercropping maize with lablab reduced maize roots biomass at Syferkuil by 10% and increased shoots biomass and grain yield by 17% and 19% at Univen in 2018/2019 and 2019/2020, respectively. Lablab cultivars had no effect on LER in both sites. DL-1002 and Rongai had roots and shoots biomass of 117-143% and 212-250%, respectively, greater than Q-6880B at flowering. Cropping system significantly affected lablab grain yield, root and shoot biomass at flowering and harvest, and HI. Intercropping reduced roots biomass, shoots biomass, grain yield and HI of lablab cultivars by over 50% compared to monocropping. Cropping system was highly influential on SMN and SWC, and the highest concentration of SMN was observed in maize monocropping at flowering and, lablab monocropping and vi maize/lablab intercrops at harvest. Generally, the levels of SMN were greatest in the topsoil depth (0-15 cm). Maize-lablab intercropping had no effect on SWC at both sites. Sole lablab increased SWC by over 13% across locations. Contrary to SMN, SWC was highest at lower soil depth (30-60 cm). APSIM model accurately simulated maize grain yield and shoot biomass. However, the model had difficulties in simulating lablab grain yield and shoot biomass, with overestimations and underestimations of 4-132% and -49.9-98.6% for biomass and grain yield, respectively, across the sites. The highest overestimations were observed for maize-lablab intercropping. The results of this study showed that intercropping maize with lablab has the potential to sustain maize yields with minimal inputs. Intercropping significantly reduced lablab yields at both locations, however, the biomass and grain yields obtained improved overall productivity of the intercropping system. Results of SMN and SWC support the potential of lablab use to improve soil N and conserve SWC. APSIM was able to simulate maize shoots biomass and grain yield but highly overestimated and underestimated lablab shoots biomass and grain yield. This suggests limited capacity of APSIM-lablab to simulate lablab biomass and grain yield under rainfed conditions in the dry areas of Limpopo province, thus the need for further research. Overall, intercropping maize with lablab showed positive results in maintaining and increasing maize yields over time at Univen, demonstrating that maize-lablab intercropping is a viable system to integrate into maize cropping systems to improve maize yields and land productivity in Limpopo province.