Long-term maize trial plots at the Hatfield Experimental Farm, U of Pretoria

Long-term yield trials are great resources for agricultural researches in multiple disciplines, but such dataset have not been readily available in Sub-Saharan Africa. The Hatfield Experimental Farm in Pretoria, South Africa, is an exceptional case that has been providing maize yield and fertilizer trial dataset with 32 treatments since 1939. In collaboration with University of Pretoria, HarvestChoice facilitated the re-discovery of raw yield dataset from the trial to study the measured long-term yield variability.

Long-term crop trials provide valuable research data to help understand complex interactions between field management practices and environment conditions. Such datasets are often used as a basis for developing analytical biophysical models that are used to assess the sustainability of crop production, strategies for improving the status of food security, and enhanced resilience to the climate variability/change impacts. Two historic example sites are still managed by Rothamsted Research in Harpenden, UK, and University of Illinois in Morrow Plots, Illinois, USA for generations (see NASA Global Change Master Directory for the list of long-term trials globally), and many of their outcomes are being used even in outside of their original purposes of the experiments. For example, the Rothamstead's long term experiments were set up to study soil fertility and soil properties change and became the dataset to study and model soil organic matter dynamics. However, they are now also addressing other issues including "... the incidence of pests, diseases, and weeds; soil pollution; ecology of farmland; carbon sequestration; factors influencing the sustainability of arable agriculture."

Experiments

In Sub-Saharan Africa, however, only a handful long-term trial sites have been established, and most of their datasets are left in grey literatures and not readily available to a broader research community. Among those, the Hatfield Experimental Farm Long-Term Maize Trial in Pretoria, South Africa, is an exceptional case. Being one of the oldest long-term experiments in the world, 32 treatments of the combination of water, fertilizer (N/P/K) and green manure applications, have been continuously applied on 128 experimental plots of maize (summer; planting in October/November) in rotation with legume crop (field pea during winter season) since 1939.

In 1996, Nel et al. published an article describing the experiment and findings based on decadal (5 periods: 1940-1949, 1950-1959, 1960-1969, 1970-1979, and 1980-1990) mean yield impacts by combinational effects of treatments and discussed the importance of balanced management of N, P, and K, and the critical roles of leguminous rotation crop and manure application. No follow-up publication has been made in public since 1996, but the trial is still being carried out by University of Pretoria. Hatfield is now preparing for its 71st harvest in 2011.

Beyond the focus of Nel's discussion on the nutrient management on decadal time-scale, we retrieved the underlying annual yield data to illustrate the temporal pattern of yield and its variability for the extended period of 1939-2005¹. To simplify the analysis and reflect typical² management choices of farmers in SSA, we focused on following four treatments under no-water condition³:

  • Control
  • N, P, and K fertilizer
  • Manure
  • N, P, and K fertilizer + Manure

The amount of fertilizer and manure and the used cultivar varies from period to period; but they can be generally considered as moving toward a high-input system. Unlike Nel's study, no statistical adjustment was made on the raw yield data yet, primarily to illustrate the extent of potential yield variability as-is.

Rainfall

Rainfall data for the growing season covering the same time period was retrieved from the University of East Anglia CRU-TS v3.0 database at monthly-basis. The sum of rainfall for the first three-month of growing season, assumed to be from October to December, was computed and analyzed in relation to the yield, based on the hypothesis that this period roughly coincides with the period between planting and flowering, and the water stress of this period is critical to yield.

 

Annual early-season (Oct-Dec) rainfall amount (mm)

When the amount of the early-season rainfall was plotted annually (Figure 1), overall there were 13 (19%) and 9 (13%) years with rainfall amount larger and smaller than the 1 standard deviation of rainfall over time, respectively. It was also shown that some increasing frequency of extreme events over the years. There were three incidents of rainfall amount larger than 2 standard deviation (i.e., wet years), and these all occurred after 1990. Between 1980 and 2005, there were 64% of years with rainfall less than long-term average. Overall there were about 60% of chance that the given year's rainfall is less than the long-term average.

Cumulative Distribution of Rainfall

This was also shown at the cumulative probability chart of rainfall shown by three time periods (1939-1960, 1961-1980, and 1981-2005) (Figure 2). Especially, the probability line for the last time period, 1981-2005, indicated that more chances of receiving high amount of rainfall than previous periods. However the impact of rainfall variability was not clearly correlated with the variability of yield, possibly due to the initial water management practiced for all treatment plots.

Yield

In general, overall historical changes of yield show increasing trend over time (except for the control), but with noticeably high degrees of variability (Figure 3). Across treatments (excluding the control), it was shown that given year's yield was >50% more or less (red dotted lines) than the previous year in about 23% of cases (Figure 4). That is, in about 1 in 5 years, given year's yield - no matter how it was managed - can be unpredictably vary, either double of halve, from the previous year. Some extent of the variability may be due to the changing treatment conditions over time (e.g., different varieties) or undocumented biotic (e.g., pest infestation) or abiotic (e.g., acute drought) damages, yet the exact cause of such high variability is not yet identified in this quick study, but it will be the main subject of matters in the follow up study. The thickness of lines in Figure 4 correspond with the average yield level of each treatment each year, and they are showing the increasing trends over time with thickening lines, compared to the early years.

Annual yield & rainfall

 

 

To take into account the changing technology over time, the whole period was segmented into six (1939-1950, 1951-1960, 1961-1970, 1971-1980, 1981-1990, and 1991-2005), and the cumulative probability of yield during each period was plotted (Figure 5). Over time, the probability of getting higher yield level noticeably increased (i.e., moving toward right hand side), yet the variability persisted (i.e., wide spread of each line) even for the high input case of NPK fertilizer plus manure application (red line).

Cumulative probability of yield by decade

Remark

This post revealed the highly variable yield trends over time from the long-term maize trial in Hatfield Experiment Farm in Pretoria, South Africa. Since the trial started in 1939, the average yield levels across treatment significantly increased, partly due to the changing varieties and amount of nutrient inputs, yet so does their variabilities. About one in five years, average yield has been doubled or halved from the previous year. Not exact causes of the yield variability was identified yet, but will be further studied in the near future as a follow-up study.

It is worth reiterating that the long-term agronomic trials can give unprecedented insightful study materials for various study fields involving sustainability, ecology, food security, climate change, as well as conventional agriculture. Although the management of such trials demand nontrivial resources and dedications, we believe the value of well-maintained and carefully documented long-term trials easily outweigh the necessary cost and will provide valuable guidance for generations to come.

Download

We plan to make the annual maize yield dataset used in this post available in Excel format. Please fill out the data request form; download instructions will be sent to your email.

Reference

Nel et al. 1996. Trends in maize grain yields in a long-term fertilizer trial. Field Crops Research 47 (1996) 53-64.

Acknowledgement

HarvestChoice deeply thanks University of Pretoria for the great efforts being made to lead the unprecedented long-term trial in Sub-Saharan Africa, and we sincerely wish this effort will continue for generations to come. We especially thank Johan de Beer, Johan van der Watt and Burger Cille for their data collecting efforts over the decades, and our colleagues/collaborators in Pretoria who helped to track down and compile the datasets, including Frikkie Liebenberg, John Annandale, and Martin Steyn.

Footnote

  1. The annual yield dataset expands until 2008, but this study limited its focus until 2005 to coincide with the rainfall data.
  2. We assumed it is not common to only apply potassium fertilizers.
  3. Prior to planting in each season, sufficient water was applied to attain field capacity in all treatment plots. However, irrigation is not commonly practiced in the area. As a reference, Gauteng province (where Pretoria district belongs to) was reported to have irrigation in maize field was practiced in about 8% of area (Statistics South Africa, 2002).

Citation

HarvestChoice, 2010. "Measured Maize Yield Variability in South Africa (1938-2005)." International Food Policy Research Institute, Washington, DC., and University of Minnesota, St. Paul, MN. Available online at http://harvestchoice.org/node/1433.

Dec 16, 2010