Dr. Lize Joubert-van der Merwe, Veldtology (Pty) Ltd.
email: lize@veldtology.co.za, mobile: 082 650 9814
Publication: AmberCircle March Newsletter
Date: 30 March 2023

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A holistic approach is necessary for effective farm management; where effectiveness is defined as the ability to achieve a set of objectives with limited resources (time, money and people), and without having an unreasonable adverse effect on non-target areas. This means that available resources must be spent on actions to achieve certain outcomes. However, it is common to find that historical achievement of outcomes (particularly those impacting profit margins) determines how much resources are available now. The knock-on effect is that resource availability limits the actions that can be implemented now to achieve outcomes in future.

It follows that prioritization should influence the choice of actions to implement, and also the order in which to execute them, so that the greatest possible outcome can be achieved. Moreover, adaptation should run in parallel (and in iterative cycles) as part of the continual improvement process, with decision-making at every step of the Plan-Do-Check-Act cycle strategically informed by good data interpreted within the correct context

A framework for understanding management systems

There is much going on in management, and it is easy to get lost in the detail and lose focus of the bigger picture. To navigate these dynamics, I apply concepts from the field of study that interrogates how systems work (Systems Theory and Systems Thinking). Here, a system is a collection of things that independently and interactively influence other things within a certain context. All systems exist alongside other systems, and all systems are dynamic (i.e., they change over time due to internal and external drivers). Some of these changes are beneficial to the achievement of outcomes, while others are not.

An effective system is running well within its current context. But an effective system should also be resilient to adverse conditions arising from a change in that context (e.g., market conditions). Both effectiveness and resilience are system properties, i.e., they emerge as out of the mist when a large number of small things are done correctly.

To become effective and resilient requires an in-depth understanding of the system, including the drivers of change. A workable strategy is to start with the drivers you know best (how people use things to achieve an objective), and then to think about how things influence other things along the way to achieving that objective. Examples follow in the section (below). These approaches help with the identification of current dynamics in the management system, and also help shape our understanding of what might happen in future. Knowing what to suspect in future is key to proactive management, which is usually cheaper than getting caught up in cycles of reactive activities.

Identifying the different elements of a system

As part of this two-tiered approach to understanding current dynamics and foresee future scenarios, I like to identify causes and effects, interactions, and buffers in a system. For example, fertilizer is a cause of vigorous plant growth, but interacts with irrigation water – too much water causes leaching of nutrients from soils, while too little water can cause chemical burns. Soil clay percentage can buffer the soil from the leaching of nutrients (by altering the Cation Exchange Capacity of soils). Similarly, organic material in soils buffer soils from drying out too quickly (by altering the water holding capacity).

To identify trade-offs and knock-on effects requires managers to think two steps ahead. For example, air among soil particles provide the oxygen needed by plant roots to respirate and grow, but the original action of irrigation replaces this air with water. Effective management identifies the knock-on effect of the action; here, oxygen supply to roots impacted by irrigation. Then, it manages that effect too; here, by allowing routine drying out of the soil profile between irrigation events. Another example involves surface application of wood chips in tree rows. This causes an initial drying-out of the soil profile, because water first has to penetrate the mulch blanket before it reaches the tree roots. Effective irrigation compensates for this initial drying out of the soil profile (by consulting readings from soil moisture probes or similar devices and making appropriate adjustments to irrigation scheduling), and then reverts back to the status-quo when the time is right. The application of mulch can also cause top soil layers to enter a nitrogen-negative period, which is when all nitrogen is locked up inside the bodies of microorganisms and insects that decompose organic matter. Adjusting the application of nitrogen during this period can help the decomposition process, and prevent harm to the nutritional status of the plant.

Context adds yet another layer of complexity to the system, as it considers the recipient environment into which inputs are delivered. The context of farms has several dimensions, notably, a specific geographic locality, with specific environmental conditions that are managed in a certain way during a defined time period. These dimensions feed into precision farming, which Veldtology defines as doing the right thing (action) in the right place (spatial accuracy) at the right time (as informed by data generated through routine monitoring).

Over time, farming practices modify the natural environmental conditions to better suit crop production, which means that geographic locality (or production region) is not synonymous with on-farm environmental conditions. There are differences among farms in the same region, partly as a result of historical management practices, and these will affect the outcomes too. Let us use the long-term investments that goes into soil conservation as an example. Farm A with long-term routine alleviation of soil compaction to improve water infiltration, and maintenance of cover crops to prevent erosion and contours to divert surface runoff to low-risk areas should find less damage and bounce back faster after a flood than a neighbouring Farm B that did not implement these practices (or only started implementing them recently). Farm B is also likely to engage in a larger number of reactive management activities to fix damages caused by the flood. However, there is a possibility that Farm A will overspend if they plan to futureproof themselves against every contingency.

Finally, there is the need to define the system boundary, because you have to know where to start and where to stop looking for answers. Without a boundary, it is entirely possible to include the whole agricultural value chain (from production to end-user) for the global trade of a crop, in addition to the socio-economic, political and environmental drivers of change that influence this chain. While alignment of on-farm management with global trends is necessary, it is not necessary to know the operational details of value chains to inform the improvement of farming operations at ground level.

Moreover, the system boundary needs to fit the sphere of control, which is smaller than an entity’s sphere of influence. Let us consider, for example, two entities (producer and factory owner) in an agricultural value chain. These entities have different but complementary objectives. It is the objective of the producer to consistently and cost-effectively produce good quality crops, while it is the objective of the factory owner to consistently and energy-efficiently conserve the quality of crops during processing. It is in the interest of both entities that both roles are performed well. However, the factory owner will control processing activities, which is not to be confused with the influence exerted over farming operations (e.g., on-farm hygiene practices that influence shelf life). Similarly, the producer will control farming operations, which is not the same as, for example, influencing waiting times of trucks at the processing facility. The system boundary should be realistic about the control of an entity, but not blind to outside influences.

How to define the system boundary depends on the specific question that is being asked. For improvement of on-farm management effectiveness, farm boundaries work well as system boundaries, because they are specific, visible and land ownership (or tenure) is entrenched in societal thinking. This will differ for other roleplayers in the value chain.

Case study: A young macadamia farm in the Western Cape

Concepts from this article are best illustrated with a practical example. This example should not be used as specific management advice. Each farm is unique, and each producer should gain their own expert advice before making important decisions that could influence material outcomes.

This case study is from the Western Cape, and concepts are illustrated with data obtained from public platforms funded by the Western Cape Department of Agriculture (WCDoA). I acknowledge that the knowledge infrastructure of the Western Cape differs from other production regions. Notably, the WCDoA invested in the development of CapeFarmMapper (https://gis.elsenburg.com/apps/cfm/#) and paid for the services provided by the Fruitlook platform (https://fruitlook.co.za/). CapeFarmMapper provides a static and high-level overview of variables (including soils and long-term climatic trends) to inform management direction at farm-level. This is complemented by Fruitlook that provides up-to-date and fine-scale satellite-derived data on biomass production, growth vigor, evapotranspiration (ET) and leaf nitrogen content of crops at block-level. Because Fruitlook data are updated weekly, it is possible to reflect on farming practices at the end of each week to see what worked well and what shortcomings hampered progress.

The case study presented here involves a young macadamia farm, with trees 1-2 years old, to demonstrate how an adjustment in irrigation led to an increase in nitrogen uptake (through fertigation) and growth of trees on sandy soils.

We focus only on the farm in the case study (= system boundary), and consider its context and system dynamics. Trees were planted on well-drained ridges of predominantly sandstone-derived soils. This sand has a poor water holding capacity, poor nutrient status, low carbon content and low CEC; thus, no real buffer to manage. Soil moisture probes inform irrigation scheduling. Furthermore, a fertigation system was installed and first implemented on 1 December 2022, after which soluble fertilizer was applied through the micro irrigation system once every ~14 days.

In terms of climate, the farm has a very strong wet-and-dry seasonal cycle (Figure 1), and biomass production follow ET closely throughout the year (Figure 2). This indicates a high likelihood that lack of heat limits growth in winter and lack of precipitation limits growth in summer. Effective management of limiting factors requires the ability to detect when dry summers (with water limitations alleviated by irrigation) transition to winters (with heat limitations). This transition point is usually towards the end of March, and brings with it the risk of over-irrigation.

Over-irrigation is counterproductive for several reasons:

1) It wastes water and electricity (pumping costs).

2) Water has a higher specific heat capacity than air, which means that irrigation gives water, but takes heat away from the soil profile. Because heat is limiting growth in winter, the conservation of heat in the soils of this farm should become a priority to management when water stops being a limiting factor. This means less irrigation.

3) Fertigation on too wet soil can cause leaching of water-soluble nutrients, and so impede nutrient uptake by roots of young macadamia trees.

 

	Figure 1 The farm exhibits very strong seasonal differences between wet winters and dry summers to which irrigation practices need to adapt. The sudden switch from dry-to-wet needs to be navigated with care to prevent over-irrigation and ensure effective fertigation. Data source: CapeFarmMapper
	Figure 2 There is a strong relationship between biomass production (in blue) and evapotranspiration (in green), which could point to cool temperatures limiting vegetative growth. The sharp drop in biomass production on 1 Nov 2022 was caused by mowing of interrows, because satellites cannot distinguish between macadamia trees and cover crops. Data source: Fruitlook

 

After the fertigation system was implemented on 1 Dec 2022, there was a clear effect on growth rate of plants (NDVI) (Figure 3). But fertigation did not have the same positive effect on nitrogen content of leaves. This did not match our expectations of future scenarios, and so warranted further investigation. Because nitrogen is a water-soluble chemical, an interaction with soil moisture content was suspected and a decision was made to experiment with irrigation scheduling in an attempt to improve nitrogen uptake.

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Figure 3 The implementation of a fertigation system on 1 Dec 2022 had a clear effect on vegetative growth rate (in blue), but less so on the nitrogen content of leaves. Because nitrogen is soluble in water, there was a suspicion that interaction with soil moisture content could impede nitrogen uptake. Data source: Fruitlook

Starting on 18 Feb 2023, irrigation was adjusted so that the soil profile could become drier between irrigation events. Practically, this meant no irrigation for a total of 1-3 cool days per week depending on weather forecasts. This change in irrigation was carefully navigated with the help of soil moisture probe readings and retrospective weekly analysis of relevant Fruitlook data (including ET).

Furthermore, fertigation was scheduled to take place when the soil profile was not saturated with irrigation or rain water, which meant shifting fertigation when there was an approaching cold front. It was fortuitous that the satellites that measure biomass, growth rate (NDVI) and nitrogen content of leaves passed over this farm within a few days after each fertigation event, and on days without cloud cover, which enabled great data capturing.

 

Figure 4 Since irrigation scheduling was adjusted (18 Feb 2023), nitrogen content of leaves (in brown) increased and converged with biomass production (in blue) for the first time since the fertigation system was installed. Data source: Fruitlook

These tweaks in irrigation and fertigation resulted in an increase in the nitrogen content of leaves (Figure 4). The fluctuations in nitrogen content from mid-Feb to end-of March coincide with fertigation ‘pulses’. The improvement in nitrogen content of leaves was accomplished without making any changes to the fertigation solution, i.e., no extra input costs. The only change was to the moisture content of the recipient environment.

Moreover, nitrogen content of leaves converged with weekly biomass production for the first time (on 21 Feb 2023) since the fertigation system was installed (on 1 Dec 2022). Fluctuations in biomass production normally follow fluctuations in ET on this farm. The convergence of nitrogen content with ET and biomass production seems to imply that nitrogen is now contributing more actively to plant growth, within the limits set by available heat units.

Achieving better outcomes at lower costs and by generating less waste. Now, there is a nice win…

Dr. Lize Joubert-van der Merwe
Veldtology (Pty) Ltd.
email: lize@veldtology.co.za, mobile: 082 650 9814
Publication: AmberCircle March Newsletter
Date: 30 March 2023

 

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