# Cacao stand rehabilitation practices affect long-term cocoa production in agroforestry systems in Cameroon

Jean Guy Ndje Mbile, Stephane Saj, Seguy Enock, William A Mala, Jean-Michel Harmand

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Jean Guy Ndje Mbile, Stephane Saj, Seguy Enock, William A Mala, Jean-Michel Harmand. Cacao stand rehabilitation practices affect long-term cocoa production in agroforestry systems in Cameroon. Agroforestry Systems, 2025, 99, pp.199. 10.1007/s10457-025-01285-7. hal-05262380

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# Cacao stand rehabilitation practices affect long-term cocoa production in agroforestry systems in Cameroon

Jean Guy Ndje Mbile · Stephane Saj · Seguy Enock · William A. Mala · Jean-Michel Harmand

Received: 24 September 2024 / Accepted: 28 July 2025
© The Author(s) 2025

**Abstract** Previous studies suggest that the density and diversity of associated trees stabilises cocoa agroforestry systems (cAFS) production in the long term. However, the impact of cocoa rejuvenation practices on this stabilisation process remains unclear. This study investigated how farmers' practices, particularly cocoa stand management, influence long-term cocoa yields, considering the production area's history and current management. Cocoa plantations aged from 7 to over 60 years were selected in two areas: an old cocoa production area (Bakoa) and a cocoa pioneer front in the forested land (Talba) in Cameroon's Centre region. Measurements included cocoa and associated tree diameters, shade tree cover and accessible cocoa yield. We also identified architectural types of cocoa trees representing various development stages. Results showed no effect of plantation age

on associated tree parameters at either site. In Talba, cocoa tree density and accessible yield decreased with plantation age. This decline was associated with an increase in senescent cocoa trees and few regenerated multi-stem trees over time. This indicates poor rejuvenation of existing plantations in Talba, where forest reserves are available to create new ones. Conversely, in Bakoa, an area with no available forest reserves, rejuvenation of existing plantations, evidenced by the increasing density of multi-stem cocoa trees and new seedlings over time, was associated with stable yields in the long term. Providing farmers with training and incentives to rejuvenate old cocoa stands should be part of an overall strategy to increase production, improve farmers' incomes, protect forests

J. N. Mbile
Institute of Agricultural Research for Development
(IRAD), Yaounde, Cameroon

J. N. Mbile (✉) · J.-M. Harmand
Eco&Sols, CIRAD, INRAE, Institut Agro, IRD, Univ
Montpellier, Montpellier, France
e-mail: jgndje@yahoo.fr

J. N. Mbile · W. A. Mala
University of Yaoundé 1, Yaoundé, Cameroon

S. Saj
ABSys, CIHEAM, CIRAD, INRAE, Institut Agro, Univ
Montpellier, Montpellier, France

S. Saj
French Agricultural Research Centre for International
Development (CIRAD), UMR ABSys, 34398 Montpellier,
France

S. Saj
Department of International Cooperation, Research
Institute of Organic Agriculture (FiBL), Lausanne,
Switzerland

S. Enock · J.-M. Harmand (✉)
CIRAD, UMR Eco&Sols, Yaoundé, Cameroon
e-mail: jean-michel.harmand@cirad.fr

J.-M. Harmand
CIFOR-ICRAF, Yaoundé, Cameroon
and comply with the commercial rules of consumer countries.

**Keywords** Cocoa tree architecture · Sustainable cocoa production · Cocoa agroforestry management · Cocoa pioneer front

**Introduction**

In Central Cameroon, cocoa is mostly produced in agroforestry systems (cAFS) with transmission of plantations through generations of farmers (Jagoret et al. 2018a). Compared to monoculture, this type of production favors (i) sustainability through the ecosystem services (ES) provided (Oke and Olatilu 2011; Saj et al. 2017a; Nijmeijer et al. 2019a,) and (ii) farmers' livelihood resilience through the diversification of household food and incomes (Gockowski et al. 2010; Jagoret et al. 2014; Temgoua et al. 2018). Central Cameroon is characterized by a forest-savannah transition zone where cAFS are installed after either partial forest clearing or savannah. In plantations derived from forest, producers generally select remnant associated trees according to long-term needs (Manga Essouma et al. 2020). In addition, Central Cameroon exhibits cAFS over 100 years old that are still managed and productive, and this is possibly due to the implementation of rehabilitation practices able to maintain acceptable productivity levels as considered by the farmers (Saj et al. 2017a; Jagoret et al. 2017). Such rehabilitation practices imply at least two different modalities: (i) replacing old/unproductive and dead cocoa trees by direct sowing or planting new seedlings and (ii) coppicing senescent cocoa trees. Associated trees are removed when they are harvested for timber, deemed useless, or provide too much shade. New trees can be planted/transplanted/ left to grow in places where shade is lacking (Jagoret et al. 2018b). Even when the associated tree canopy is diverse and dense, cocoa remains the main crop in cAFS and farmers clearly manage these systems in order to influence cocoa production (Jagoret et al. 2017). However, there are meaningful geographic differences in the composition, structure and management practices of cAFS (Jagoret et al. 2011), which translate into different levels of ES provision and trade-offs, whether the latter are intentionally chosen by farmers or not (Andreotti et al. 2018).

In a context where Cameroon promotes doubling cocoa production by 2030 while preserving forests (Republic of Cameroon—National Development Strategy 2020; Carodenuto et al. 2017; Ingram et al. 2018; Reboul 2024), farmers' practices that drive productivity are likely to vary according to the production area and history (Michel et al. 2019). This study aimed to investigate how farmers' practices, particularly cocoa stand management, influence long-term productivity, considering the production area's history and current context. More specifically, the study aimed to analyze how the associated tree stand structure and cocoa stand management impact cocoa production over time.

To that end, we studied cocoa farms of different ages in two contrasted production areas in the forest-savannah transition zone of Central Cameroon. On the one hand, we studied cAFS from Bakoa, an old cocoa production area characterized by a patchwork of forests and savannahs. On the other hand, we studied cAFS in Talba, a few decades-old cocoa pioneer front in a forested land. We used a chronosequence pathway to check for cAFS temporal evolution and focused solely on cocoa plots with a forest previous land use. A set of attributes of the cocoa system structure influenced by farmers' management was used to assess their effects on cocoa production over time. For associated trees, a particular attention was paid to their density, basal area and canopy cover. For cocoa trees, we monitored their density and architectural type contribution to total yield on the long run.

**Material and methods**

Study sites and sampling design of cocoa plots

Bakoa village is located in the Bokito district (04°30 N–11°10 E). The landscape consists of hills, with gentle slopes, at altitudes ranging from 400 to 500 m, and is characterized by a patchwork of forests, cocoa agroforests, herbaceous savannahs and croplands (Jagoret et al. 2012; Nijmeijer et al. 2019b). Soil is Orthic Ferralsol (Sauvadet et al. 2020). In Bakoa, cAFS have been created either after forest or after savannah. Cocoa plantations have mainly been established by planting seedlings from old cocoa varieties and hybrids grown on the farms. Talba village is
located in the Mbangassina district (04°34 N–11°28 E). It is a pioneer front of a few decades old where cocoa plantations have been created after partial or almost total deforestation. Soils are ferralitic and clayed-sandy. Cocoa plantations have been established mainly by planting seedlings from on-farm bred cocoa hybrids, derived from the first “improved” varieties dissemination program of the 1970s.

The two villages, 35 km apart as the crow flies, share the same rainfall pattern: 1300–1400 mm per year, with a main long dry season lasting from mid-November to March (Pedelahore 2014). The topsoil in the studied cocoa plantations had similar clay content in both sites, but C content, pH, inorganic P and sum of exchangeable bases were higher in Talba compared to Bakoa (Table 1).

In total, 46 cocoa agroforestry plantations—14 in Bakoa and 32 in Talba, were selected from the research sites network established by the Institute of Agricultural Research for Development (IRAD) and by the French Agricultural Research Centre for International Development (CIRAD) in these villages. The cocoa plots were selected on the basis of (i) the previous land use: forest, and (ii) the cacao cultivation duration: distributed along a gradient ranging from 7 to over 100 years. We also defined four cAFS age categories: [7–20], [20–40], [40–60] and ≥ 60 years old. In these farms, cocoa had been planted with regular spacing, although we did not have information on the initial density of cocoa trees. In the young systems, this regular distribution of cocoa trees was very visible. In the older plots, it was also clear when focusing on the older cocoa trees.

## Data collection

### Tree diversity, density, and size

In each cAFS, all cacao trees were inventoried in a 800 m² subplot while associated trees were inventoried in a 2400 m² plot including the 800 m² subplot. Height and diameter at breast height (1.3 m; DBH) were measured using appropriate tools and techniques. Trees were inventoried as described in Saj et al. (2017b) and Nijmeijer et al. (2019b). The data of floristic inventory enabled us to compute five ecosystem attributes at the plot scale related to associated trees, i.e. species richness and diversity, canopy cover, basal area and aboveground biomass.

The Shannon–Wiener index was calculated as follows:

$$ \text{Shannon-Wiener } H' = - \sum ((N_i/N) * \text{Log}(N_i/N)) $$

where $N_i$ corresponds to the number of individuals of a species and $N$ to the total number of individuals inventoried.

In order to estimate the canopy cover of associated trees, the diameter of the crown of each associated tree was estimated according to the manual for the national forest inventory (FAO 2004) and determined through the measurement of the radius of the crown (CR) in eight (08) different directions according to the cardinal points (from North to North-West). The shade cover (SC) was calculated as follows, Eq. (1):

<caption>**Table 1** Soils properties in cocoa agroforestry systems in Bakoa (14 plots) and Talba (29 plots)</caption>

Values in bold are significantly different between sites at *P* < 0.05 (Source Nijmeijer et al. 2019a, b; Fonkeng et al. 2024)

<table><thead><tr><th rowspan="2">Soil parameter</th><th colspan="2">Site</th><th rowspan="2">P value</th></tr><tr><th>Bakoa</th><th>Talba</th></tr></thead><tbody><tr><td>pH<sub>water</sub></td><td><strong>6.5 ± 0.56</strong></td><td><strong>7.4 ± 0.41</strong></td><td><strong>&lt; 0.0001</strong></td></tr><tr><td>Clay</td><td>21.38 ± 6.81</td><td>20.16 ± 5.38</td><td>0.523</td></tr><tr><td>Organic C (%)</td><td>1.95 ± 0.47</td><td>2.1 ± 0.47</td><td>0.059</td></tr><tr><td>Total N (%)</td><td><strong>0.15 ± 0.04</strong></td><td><strong>0.2 ± 0.04</strong></td><td><strong>0.000</strong></td></tr><tr><td>C:N</td><td><strong>13.5 ± 2.09</strong></td><td><strong>10.8 ± 0.52</strong></td><td><strong>&lt; 0.0001</strong></td></tr><tr><td>Inorganic P (ppm)</td><td><strong>7.2 ± 7.1</strong></td><td><strong>14.53 ± 5.64</strong></td><td><strong>&lt; 0.0001</strong></td></tr><tr><td>Total bases (cmol kg<sup>-1</sup>)</td><td><strong>8.9 ± 4.8</strong></td><td><strong>13.9 ± 3.2</strong></td><td><strong>0.001</strong></td></tr><tr><td>Exchangeable K (cmol kg<sup>-1</sup>)</td><td>0.23 ± 0.1</td><td>0.32 ± 0.2</td><td>0.084</td></tr><tr><td>Exchangeable Ca (cmol kg<sup>-1</sup>)</td><td><strong>6.87 ± 4.34</strong></td><td><strong>12.07 ± 3</strong></td><td><strong>0.001</strong></td></tr><tr><td>Exchangeable Mg (cmol kg<sup>-1</sup>)</td><td>1.75 ± 0</td><td>1.52 ± 0.46</td><td>0.377</td></tr></tbody></table>
$$SC = \pi * \left( \sum (CR)/8 + DBH/100/2 \right)^2 \quad (1)$$

where SC is expressed in m², CR in m and DBH in cm.

We estimated the aboveground biomass (AGB) of all associated trees using the allometric equation established by Chave et al. (2014), Eq. (2):

$$AGB = 0,112(\mu * DBH^2 * H)^{0,916} \quad (2)$$

where AGB of the tree is expressed in kg, DBH (diameter at breast height) in cm, H (height of the tree) in m and μ (density of the wood) in g cm⁻³. AGB

values were multiplied by 0.47 to obtain carbon storage in aboveground biomass.

## Identification of architectural types of cocoa trees

To take account of the characteristics of cocoa trees, the different architectural types of cocoa trees were identified, as previously described by Jagoret et al. (2018a) in Central Cameroon (Fig. 1). These architectural types are indicative of both the different stages of cocoa tree development and the management practices used by farmers. Indeed, architectural types partially indicate the practices used by the farmers to renew old, senescent or dead cocoa trees. The types 1–3 show the different shapes of cocoa trees

<figure><img src="image_2.png" /><figcaption>**Fig. 1** Cocoa tree architectural types found in cocoa agroforestry systems in Central Cameroon (Source: Jagoret et al. 2018a). Type 1 represents a single-stem cocoa tree with the crown formed at the first node. Type 2 represents a single-stem cocoa tree with the crown formed at the second node. Type 3</figcaption></figure>

represents a two-stem cocoa tree. Type 4 represents a single or multi-stem cocoa tree resulting from the coppicing of a senescent cocoa tree and type 5 represents a senescent cocoa tree with dead branches
growing from the seedling stage. Type 1 represents a single-stem cocoa tree with the crown formed at the first node. In Central Cameroon, type 1 is generally associated with young, unpruned cocoa trees. Type 2 represents a single-stem cacao tree with the crown formed at the second node, which is the most common pruning practice in central Cameroon. Type 3 represents a two-stem cacao tree that has grown this way from the seedling stage. Type 4 represents a single or multi-stem cocoa tree resulting from the copicing of a senescent cocoa tree. Type 5 represents a senescent cocoa tree with dead branches (Fig. 1).

## Assessment of accessible cocoa yield

To evaluate the impact of cocoa stand structure and age on cocoa production at the plot level we measured the accessible cocoa yield and not the actual yield. This approach allowed us to exclude the impact of pests and diseases on the annual production, and avoid a significant bias in our evaluation. The management of pests and diseases varies from farmer to farmer (e.g., application of pesticides, pruning of cocoa tree branches), and therefore has a different impact on cocoa production, regardless of the main cocoa stand structure. Immature cocoa pods over 10 cm in length were counted five times, every 6 weeks during the fruiting period (between June and December in 2015 at Bakoa and in 2019 at Talba). The counted pods were marked with paint and different colours were used for each count in order to avoid counting the same pods more than once. Such a count indicates the maximum number of pods per plot that can physiologically reach maturity within a production cycle. This pod counting did not consider the potential impact of pests and diseases on pod maturation and yield. We defined it as the “accessible” production of pods from which we then derived the “accessible” yield in cocoa beans (Saj et al. 2017a, b).

The accessible yield was calculated as follow Eq. (3):

$$ \text{Yield (kg ha}^{-1}\text{)} = \text{Total number of pods per plot} * \text{W beans} * \text{TC} \quad (3) $$

where “W beans” is the mean weight of fresh beans per pod (0.115 kg), TC is the weight ratio of fresh

beans to marketable dry beans (0.35) (Jagoret et al. 2011).

The average cocoa tree productivity (kg per cocoa tree) was calculated by dividing the cocoa yield at the plot level (kg ha⁻¹) by the density of cocoa trees in the plot (number of cocoa trees per ha). The productivity of each cocoa tree architectural type was obtained by dividing the total production of the corresponding architectural type by its density in the plot.

## Data analyses

First, the contributions of cocoa tree architectural types to cocoa yield were investigated using principal component analysis (PCA), with site and plot age added as additional variables to position them in the resulting projection. A full-factorial analysis of covariance (ANCOVA) was used to check for the effect of plot ageing (quantitative factor) and site (qualitative factor) on cocoa tree attributes (density, yield at the plot level, contribution of cocoa tree architectural type to yield, cocoa tree productivity) and associated trees features (canopy cover, density, basal area, above ground biomass, Shannon index). Following the ANCOVA, the Tukey test was run to distinguish between the two sites. And, the attributes statistically affected by cAFS ageing (cocoa tree density, cocoa yield at plot level, contribution of cocoa tree type to yield and cocoa tree productivity) were specifically plotted for linear regressions. Finally, a Kruskal-Wallis test was done to check the effect of age categories in each site. When found significant for an attribute, it was followed by the Conover-Iman test to distinguish between age categories. Statistical analyses were performed using XLSTAT (v. 2023 3.1; Addinsoft 2023) and statistical significance was set at *P* < 0.05.

## Results

### Attributes of associated trees in cocoa farms

The stands of trees associated with cacao were less dense, less massive and less diverse in Talba than in Bakoa, with significantly lower average values for
<table><caption>**Table 2** Attributes of associated trees (mean and standard deviation) in Bakoa and Talba according to different age categories of plots</caption><thead><tr><th rowspan="2">Site</th><th rowspan="2">Attribute of associated trees</th><th colspan="4">Age category of cocoa plots</th><th rowspan="2">Mean</th></tr><tr><th>[7–20] years</th><th>[20–40] years</th><th>[40–60] years</th><th>≥ 60 years</th></tr></thead><tbody><tr><td rowspan="5">Bakoa</td><td>Canopy Cover (%)</td><td>59.5±33.8</td><td>51.6±37</td><td>65.75±12.41</td><td>55.6±29.9</td><td>58.14±28.3 B</td></tr><tr><td>Density (nb ha<sup>-1</sup>)</td><td>56±31</td><td>60±24</td><td>68±15</td><td>75±34</td><td>65±28 B</td></tr><tr><td>Basal area (m<sup>2</sup> ha<sup>-1</sup>)</td><td>19.1±11.8</td><td>15.9±12.3</td><td>19.2±3.6</td><td>22.5±19.8</td><td>19.10±11.9 B</td></tr><tr><td>AGC stocks (ton ha<sup>-1</sup>)</td><td>58.3±38</td><td>51.9±38.1</td><td>77.1±10.2</td><td>69.3±55.3</td><td>64.1±35.4 B</td></tr><tr><td>Shannon index</td><td>2.01±0.59</td><td>2.08±0.21</td><td>2±0.18</td><td>2.05±0.36</td><td>2.03±0.33 B</td></tr><tr><td rowspan="5">Talba</td><td>Canopy Cover (%)</td><td>40.2±26.1</td><td>40.6±29.9</td><td>30.6±16.9</td><td>43.10±15.9</td><td>38.6±22.2 A</td></tr><tr><td>Density (nb ha<sup>-1</sup>)</td><td>52±33</td><td>37±22</td><td>45±61</td><td>31±5</td><td>41±30 A</td></tr><tr><td>Basal area (m<sup>2</sup> ha<sup>-1</sup>)</td><td>9.6±3.9</td><td>9.7±7.2</td><td>7.8±3.6</td><td>8±4.7</td><td>8.8±4.9 A</td></tr><tr><td>AGC stocks (ton ha<sup>-1</sup>)</td><td>38.3±21.5</td><td>46.9±35.9</td><td>29.3±18.5</td><td>35.2±24.2</td><td>37.4±25 A</td></tr><tr><td>Shannon index</td><td>1.8±0.7</td><td>1.3±0.7</td><td>1.2±0.4</td><td>1.8±0.2</td><td>1.55±0.5 A</td></tr></tbody></table>

Within a column, values followed by the same capital letter are not significantly different between sites at *P* < 0.05

<table><caption>**Table 3** Results from the ANCOVA run on attributes of the associated trees stand and attributes of cocoa trees stand according to age of the plantations and site</caption><thead><tr><th></th><th>F complete model</th><th>F-AFS age</th><th>F-site</th><th>F AFS age * site</th></tr></thead><tbody><tr><td colspan="5"><strong>Associated trees attributes</strong></td></tr><tr><td>Canopy cover (%)</td><td>2.254**</td><td>0.133</td><td>2.449**</td><td>0.018</td></tr><tr><td>Density (nb ha<sup>-1</sup>)</td><td>1.670**</td><td>0.235</td><td>0.030**</td><td>1.197</td></tr><tr><td>Basal area (m<sup>2</sup> ha<sup>-1</sup>)</td><td>6.125***</td><td>0.105</td><td>4.718***</td><td>0.067</td></tr><tr><td>Abg. biomass (ton ha<sup>-1</sup>)</td><td>2.773**</td><td>0.014</td><td>1.556**</td><td>0.171</td></tr><tr><td>Shannon index</td><td>2.558**</td><td>0.555</td><td>1.144**</td><td>0.272</td></tr><tr><td colspan="5"><strong>Cocoa tree density (nb ha<sup>-1</sup>)</strong></td></tr><tr><td>Total</td><td>3.594*</td><td>5.439*</td><td>0.603</td><td>3.371°</td></tr><tr><td>Type 1</td><td>15.429***</td><td>0.340</td><td>15.816***</td><td>0.128</td></tr><tr><td>Type 2</td><td>11.926***</td><td>22.769***</td><td>7.124*</td><td>6.077*</td></tr><tr><td>Type 3</td><td>2.314°</td><td>3.981°</td><td>0.002</td><td>1.104</td></tr><tr><td>Type 4</td><td>13.043***</td><td>9.971**</td><td>0.607</td><td>4.569*</td></tr><tr><td>Type 5</td><td>14.110***</td><td>24.978</td><td>4.772*</td><td>12.555***</td></tr><tr><td colspan="5"><strong>Cocoa yields (kg ha<sup>-1</sup>)</strong></td></tr><tr><td>Total</td><td>10.207***</td><td>9.602**</td><td>10.080**</td><td>1.828</td></tr><tr><td>Type 1</td><td>3.427*</td><td>4.093*</td><td>7.442**</td><td>3.351°</td></tr><tr><td>Type 2</td><td>14.839***</td><td>19.127***</td><td>13.463***</td><td>4.127*</td></tr><tr><td>Type 3</td><td>2.103</td><td>5.629*</td><td>0.140</td><td>0.181</td></tr><tr><td>Type 4</td><td>10.002***</td><td>14.342***</td><td>0.000</td><td>4.105°</td></tr><tr><td>Type 5</td><td>10.008***</td><td>12.914***</td><td>0.135</td><td>7.203*</td></tr><tr><td colspan="5"><strong>Tree type contribution to total yield (%)</strong></td></tr><tr><td>Type 1</td><td>4.421**</td><td>2.060</td><td>10.508**</td><td>3.455°</td></tr><tr><td>Type 2</td><td>19.579***</td><td>43.788***</td><td>4.399*</td><td>0.915</td></tr><tr><td>Type 3</td><td>1.065</td><td>1.022</td><td>0.790</td><td>0.000</td></tr><tr><td>Type 4</td><td>30.556***</td><td>44.585***</td><td>0.004</td><td>12.704***</td></tr><tr><td>Type 5</td><td>19.708***</td><td>31.617***</td><td>1.649</td><td>15.310***</td></tr></tbody></table>

<footnote>°P < 0.08, *P < 0.05, **P < 0.01, ***P < 0.001</footnote>
tree density (41 vs 61 trees ha⁻¹), basal area (8.8 vs 19.1 m² ha⁻¹), aboveground carbon stock (37 vs 64 tons ha⁻¹), canopy cover (38% vs 58%) and Shannon index (1.55 vs 2.03) respectively (Table 2). However, we found no significant effect of cocoa plantation age on all these attributes of associated trees in both sites (Table 3).

## Density and size of cocoa trees

The cocoa tree densities varied with the age of cocoa plantations depending on the site and cocoa tree type (Table 3; Fig. 2). Indeed, the density of total cocoa trees significantly decreased with the age of the plantations in Talba (from 1287 ind ha⁻¹ in young plantations to 848 ind ha⁻¹ in very old plantations) but no significant change was found in Bakoa (Table 4; Fig. 2a). Regarding cocoa tree architectural types, the density of single-stem trees (type 2) significantly decreased with the age of the plantations, more strongly in Talba than in Bakoa (Table 4; Fig. 2b). On the other hand, the density of multi-stem cocoa trees (type 4) significantly increased with the age of cocoa plantation only in Bakoa (Table 4; Fig. 2d). Finally, the density of senescent cocoa trees (type 5) significantly and steadily increased with the age of cocoa plantations only in Talba. In Bakoa, the density of senescent cocoa trees was highest in the [40–60] years old plantations, then decreased in older plantations (≥60 years old) to reach a similar level as in young plantations ([7–20] years old) (Table 4; Fig. 2e).

The average densities of multi-stem (type 4) and young single-stem (type 1) cocoa trees were high in Bakoa (170 and 186 ind ha⁻¹, respectively) in comparison to Talba (24 and 56 ind ha⁻¹, respectively) (Table 4).

## Accessible yield at plot level

Our analyses showed different values and dynamics of accessible yield depending on both the production site and the age of cAFS. Total cocoa yield significantly decreased with cAFS ageing only in Talba (Table 4; Fig. 3a). However, the average total yield in Talba (1259 kg ha⁻¹) was higher than in Bakoa (719 kg ha⁻¹) (Table 4). Regarding cocoa tree architectural types, the yield of single-stem cocoa trees (type 2) at the plot level steadily decreased in both

sites, while the yield of regenerated cocoa trees (type 4) increased with cAFS ageing only in Bakoa.

## Contribution of architectural types of cocoa trees to total yield

The first two axes of the PCA explained 67% of the total variance of the system studied (Fig. 4). The first axis accounted for 40% of the total variance, and single-stem (type 2) and multi-stem (type 4) cocoa trees were the main contributors to this axis. The second axis accounted for only 27% of the total variance, and senescent (type 5), young (type 1) and to a lesser extent double-stem (type 3) cocoa trees were the main contributors of this axis. The projection of age categories of plots discriminated between old cocoa plantations ([40–60] and ≥60 years old) related to multi-stem (type 4) and senescent (type 5) cocoa trees and young / mature cocoa plantations ([7–20] and [20–40] years old) more related to shapes of cocoa tree grown directly from the seedling stage (types 1, 2 and 3). The projection of sites discriminated between Bakoa and Talba with multi-stem (types 3 and 4) and young type 1 cocoa trees related to Bakoa and single-stem (type 2) and senescent (type 5) cocoa trees more related to Talba.

The contribution of single-stem (type 2) cocoa trees to the total yield significantly decreased with the cAFS age in both sites (Fig. 5a). The contribution of senescent cocoa trees to the total yield significantly increased with the cAFS age only in Talba as a result of an increasing density of senescent cocoa trees with the cAFS age in this site (Table 4; Fig. 5c). Indeed, the senescent cocoa trees in very old plantations had the greatest contribution to the total yield in Talba (36%) whereas it remained low in Bakoa (6%) (Table 4). On the other hand, the contribution of regenerated type 4 cocoa trees to the total yield increased more strongly in Bakoa than in Talba (Table 4; Fig. 5b). As a result, in very old cocoa plantations, multi-stem cocoa trees (type 4) contributed to 54% of the total yield in Bakoa compared to only 23% in Talba (Table 4).

## Mean cocoa tree productivity

Concerning productivity, our results showed that cocoa trees were more productive in Talba (1.35 kg beans tree⁻¹) than Bakoa (0.73 kg beans tree⁻¹).
<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

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Bakoa

Talba

<figure><img src="image_8.png" /></figure>
►Fig. 2 Variations of the total density of cocoa trees and densities of cocoa architectural types 2, 4 and 5 of in Bakoa and Talba according to the age of plantations. Linear regressions show the significant trends in both study sites (no regression means no statistical significance). Black is for Talba. Grey is for Bakoa. R²: coefficient of determination

Cocoa tree productivity was low (from 0.70 to 0.99 kg beans tree⁻¹) in Bakoa but did not change significantly with the age of the cAFS. On the other hand, individual cocoa productivity in Talba was high (from 1.13 to 1.62 kg beans tree⁻¹) up to 60 years of age, and declined sharply in very old plantations (0.78 kg beans tree⁻¹) at a similar level as in Bakoa (0.71 kg beans tree⁻¹). Senescent cocoa trees (type 5) were more productive in Talba than in Bakoa with a significant difference in the [40–60] years old plots (Table 4). In both sites, the productivity of multi-stem cocoa trees was rather similar to the other architectural types in plantations less than 60 years old. Only in very old plantations (≥ 60 years old) did the multi-stem cocoa trees show the highest productivity (Table 4).

## Discussion

Influence of soil type and AFS structure on cocoa yield

In this study, accessible cocoa yield estimated with pod counts done every 6 weeks during the fruiting period, did not consider the potential impact of pests and diseases on pod maturation. Therefore, those values likely overestimated actual cocoa yield by 25% according to Ploetz (2016). Several factors can explain the productivity of old cAFS such as the basal area of cocoa trees (Saj et al. 2017b), renewal practices (Jagoret et al. 2018a), intercropping with associated trees (Vanhove et al. 2016) and maintaining soil fertility (Nijmeijer et al. 2019a; Sauvadet et al. 2020).

In our study, cocoa tree productivity and cocoa yield at plot level in plantations of less than 60 years old, were generally higher in one site (Talba) than in the other one (Bakoa). These differences could be explained, first by higher soil fertility (higher soil pH, inorganic P and total bases, and lower C:N ratio) (Table 1) indicating a higher cocoa production potential in Talba than in Bakoa. Besides, we could not

detect any effect of associate tree parameters on cocoa yield in Talba. But, in Bakoa, associated trees density was negatively correlated to the yield (data not shown). The lower density of associate trees (41 vs 61 trees ha⁻¹), and lower canopy cover (38% vs 58%) in Talba than in Bakoa, respectively, could also have impacted positively the production. Nevertheless, we could not detect any effect of cocoa plantation age on these associated trees attributes in both sites, whereas plantation age influenced cocoa yield at least in Talba suggesting a main influence of the cocoa stand structure on yield. However, our study did not consider the specific interactions between each cocoa tree and its environment (neighbouring cocoa trees and shade trees), which could have provided further insight into the factors affecting yield (Saj et al. 2023).

Cocoa tree management in both sites

We observed a decline in cocoa tree stand density with increasing age in Talba plantations. This phenomenon has already been observed by Saj et al. (2017b) and Jagoret et al. (2018b) who have conducted studies in other cocoa-producing areas of Cameroon. In Talba, this decline, has been associated with a higher proportion of senescent cocoa trees in older plantations, coupled with a low occurrence of multi-stem cocoa trees resulting from coppicing and young cocoa trees (Ngono et al. 2015). The very low renewal of senescent cocoa trees, combined with the lack of replacement of dead cocoa trees, was evident in plantations over 40 years old in Talba. The absence of rehabilitation of mature and old cocoa plantations can be attributed to the fact that farmers in Talba had the opportunity to establish new cocoa plantations in nearby secondary forests. Consequently, farmers would have been more inclined to expand their production area than to intensify existing plots. This strategy was previously observed in cocoa pioneer fronts where land was still available for the expansion of cocoa production (Ruf 2004; Kouadio Kouassi and Koffi Fêtê 2017).

Conversely, no discernible variation in cocoa tree density was observed with cAFS ageing in Bakoa. The increasing density of multi-stem cocoa trees resulting from coppicing, coupled with the emergence of young cocoa trees in both mature and old cocoa plantations, indicated a dynamic of renewal of mature and old plantations in Bakoa.
<table><caption>**Table 4** Attributes of the cocoa tree stands in Bakoa and Talba according to the age of plantations</caption><thead><tr><th rowspan="2">Site</th><th rowspan="2">Attribute</th><th rowspan="2">Architectural type of cocoa trees</th><th colspan="4">Age category of cocoa plots</th><th rowspan="2">Mean</th></tr><tr><th>[7-20] years</th><th>[20-40] years</th><th>[40-60] years</th><th>≥ 60 Years</th></tr></thead><tbody><tr><td rowspan="6">Bakoa</td><td rowspan="5">Cocoa tree density (nb ha<sup>-1</sup>)</td><td>type 1</td><td>159 B</td><td>179 B</td><td>194 B</td><td>150</td><td>170 B</td></tr><tr><td>type 2</td><td>406 A</td><td>654</td><td>616</td><td>158</td><td>524</td></tr><tr><td>type 3</td><td>153</td><td>175</td><td>166</td><td>129</td><td>163</td></tr><tr><td>type 4</td><td>72</td><td>125</td><td>338 B</td><td>242</td><td>186 B</td></tr><tr><td>type 5</td><td>50 a</td><td>21 a</td><td>268 b</td><td>75 ab</td><td>92</td></tr><tr><td>Total</td><td>840 A</td><td>1154</td><td>1582 B</td><td>754</td><td>1136</td></tr><tr><td rowspan="5">Cocoa tree productivity (kg tree<sup>-1</sup>)</td><td>type 1</td><td>0.71</td><td>0.21</td><td>0.01</td><td>0.11</td><td>0.23</td></tr><tr><td>type 2</td><td>1.15 b</td><td>0.78 ab A</td><td>0.32 a A</td><td>0.60 ab</td><td>0.79</td></tr><tr><td>type 3</td><td>1.19</td><td>1.17</td><td>0.55 A</td><td>0.80</td><td>0.86 A</td></tr><tr><td>type 4</td><td>0.96</td><td>1.11</td><td>0.55</td><td>1.16</td><td>0.82</td></tr><tr><td>type 5</td><td>0.14</td><td>0.45</td><td>0.47 A</td><td>0.49</td><td>0.26 A</td></tr><tr><td rowspan="5">Cocoa yield (kg ha<sup>-1</sup>)</td><td>Total</td><td>0.99 b</td><td>0.78 ab A</td><td>0.38 a A</td><td>0.71 ab</td><td>0.727 A</td></tr><tr><td>type 1</td><td>113</td><td>38 B</td><td>2</td><td>17</td><td>48 B</td></tr><tr><td>type 2</td><td>466 bc A</td><td>510 c</td><td>196 ab</td><td>95 a</td><td>383 A</td></tr><tr><td>type 3</td><td>183</td><td>206</td><td>91 A</td><td>104</td><td>154</td></tr><tr><td>type 4</td><td>69</td><td>139</td><td>187 B</td><td>280</td><td>152 B</td></tr><tr><td rowspan="5">Cocoa tree type contribution to total yield (%)</td><td>type 5</td><td>7a</td><td>10a</td><td>125 b A</td><td>37 ab</td><td>28 A</td></tr><tr><td>Total</td><td>838</td><td>903</td><td>601 A</td><td>533</td><td>719 A</td></tr><tr><td>type 1</td><td>11%</td><td>5%</td><td>1%</td><td>4%</td><td></td></tr><tr><td>type 2</td><td>55% b</td><td>63% b</td><td>36% ab</td><td>17% a</td><td></td></tr><tr><td>type 3</td><td>22%</td><td>18%</td><td>14%</td><td>19%</td><td></td></tr><tr><td rowspan="5">Cocoa tree type contribution to total yield (%)</td><td>type 4</td><td>11% a</td><td>13% a</td><td>30% ab</td><td>54% b</td><td></td></tr><tr><td>type 5</td><td>1% a</td><td>1% a</td><td>19% b</td><td>6% ab</td><td></td></tr><tr><td>Total</td><td>100</td><td>100</td><td>100</td><td>100</td><td></td></tr></tbody></table>
<table><caption>**Table 4** (continued)</caption><thead><tr><th rowspan="2">Site</th><th rowspan="2">Attribute</th><th rowspan="2">Architectural type of cocoa trees</th><th colspan="4">Age category of cocoa plots</th><th rowspan="2">Mean</th></tr><tr><th>[7–20] years</th><th>[20–40] years</th><th>[40–60] years</th><th>≥ 60 Years</th></tr></thead><tbody><tr><td rowspan="6">Talba</td><td rowspan="6">Cocoa tree density (nb ha<sup>-1</sup>)</td><td>type 1</td><td>21 A</td><td>14 A</td><td>17 A</td><td>63</td><td>24 A</td></tr><tr><td>type 2</td><td>1010 c B</td><td>663 bc</td><td>373 ab B</td><td>206 a</td><td>638</td></tr><tr><td>type 3</td><td>189 b</td><td>73 a</td><td>81 ab</td><td>113 ab</td><td>120</td></tr><tr><td>type 4</td><td>48</td><td>41</td><td>31 A</td><td>125</td><td>56 A</td></tr><tr><td>type 5</td><td>19 a</td><td>100 b</td><td>206 bc</td><td>341 c</td><td>134</td></tr><tr><td>Total</td><td>1287 b B</td><td>891 ab</td><td>708 a A</td><td>848 ab</td><td>973</td></tr><tr><td rowspan="6">Cocoa tree productivity (kg tree<sup>-1</sup>)</td><td rowspan="6"></td><td>type 1</td><td>0.87</td><td>0.68</td><td>0.82</td><td>0.27</td><td>0,48</td></tr><tr><td>type 2</td><td>1.14</td><td>1.53 B</td><td>1.56 B</td><td>0.78</td><td>1,32</td></tr><tr><td>type 3</td><td>1.18 ab</td><td>1.53 ab</td><td>1.84 b B</td><td>0.80 a</td><td>1.44 B</td></tr><tr><td>type 4</td><td>1.19</td><td>1.50</td><td>1.19</td><td>1.35</td><td>1.17</td></tr><tr><td>type 5</td><td>0.72 a</td><td>1.61 ab</td><td>1.78 b B</td><td>0.66 ab</td><td>1.01 B</td></tr><tr><td>Total</td><td>1.13 ab</td><td>1.52 b B</td><td>1.62 b B</td><td>0.78 a</td><td>1.346 B</td></tr><tr><td rowspan="6">Cocoa yield (kg ha<sup>-1</sup>)</td><td rowspan="6"></td><td>type 1</td><td>18</td><td>10 A</td><td>14</td><td>17</td><td>13 A</td></tr><tr><td>type 2</td><td>1154 b B</td><td>1014 b</td><td>581 ab</td><td>161 a</td><td>824 B</td></tr><tr><td>type 3</td><td>222</td><td>112</td><td>149</td><td>90</td><td>156</td></tr><tr><td>type 4</td><td>57</td><td>61</td><td>37 A</td><td>169</td><td>72 A</td></tr><tr><td>type 5</td><td>13 a</td><td>162 b</td><td>369 c B</td><td>225 bc</td><td>174 B</td></tr><tr><td>Total</td><td>1464 b</td><td>1359 ab</td><td>1150 ab B</td><td>663 a</td><td>1259 B</td></tr><tr><td rowspan="6">Cocoa tree type contribution to total yield (%)</td><td rowspan="6"></td><td>type 1</td><td>1%</td><td>1%</td><td>1%</td><td>3%</td><td></td></tr><tr><td>type 2</td><td>77% c</td><td>69% bc</td><td>50% ab</td><td>24% a</td><td></td></tr><tr><td>type 3</td><td>17%</td><td>10%</td><td>13%</td><td>14%</td><td></td></tr><tr><td>type 4</td><td>4% a</td><td>6% a</td><td>4% ab</td><td>23% b</td><td></td></tr><tr><td>type 5</td><td>1% a</td><td>14% bc</td><td>32% c</td><td>36% c</td><td></td></tr><tr><td>Total</td><td>100</td><td>100</td><td>100</td><td>100</td><td></td></tr></tbody></table>

Within a row, values followed by the same small letter are not significantly different at *P* < 0.05. Within a column, values followed by the same capital letter in bold are not significantly different between sites at *P* < 0.05

This dynamic may have been facilitated by the need to produce on the same land as there was no longer any forest reserve to be cleared for cocoa cultivation in Bakoa (Camara et al. 2012). Furthermore, in this region historically dedicated to cocoa production, the practices of rehabilitating old cocoa trees and plantations, developed by farmers over time and passed down from generation to generation, are common—which may not be the case in Talba yet.

Such practices have the potential to be transferred to newer production areas.

### Impact of cocoa tree management on yield

The product of cocoa tree density and cocoa tree productivity determines cocoa yield at plot level. In Talba, the steady decline in accessible cocoa yield, from 1400 kg ha⁻¹ in young plantations to
<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

Bakoa

<figure><img src="image_15.png" /></figure>

Talba

<figure><img src="image_16.png" /></figure>
►Fig. 3 Variations of the total yield of cocoa trees and yields of cocoa architectural types 2, 4 and 5 in Bakoa and Talba according to the age of plantations. Linear regressions show the significant trends in both study sites (no regression means no statistical significance). Black is for Talba. Grey is for Bakoa. R²: coefficient of determination

663 kg ha⁻¹ in very old plantations, can be associated first to a decline in cocoa tree density up to 60 years of age and then to a decline in cocoa productivity in very old plantations (Table 4). Apparently, the lack of replacement of dead cocoa trees led to a decrease in cocoa tree density and yield as plantations aged. In addition, the decline in productivity of all mature cocoa trees (architectural types 2, 3 and 5) occurred in plantations over 60 years old in Talba. However, the continued high productivity of multi-stem cacao trees (architectural type 4) in Talba's old plantations argues for more rejuvenation of old cacao trees through coppicing (Table 4).

In Bakoa, no significant variation has been observed in accessible cocoa yield as plantations aged. The increased density and contribution to plot yield of multi-stem cocoa trees (type 4) compensated the decline in the contribution to plot yield of

single-stem cocoa trees (type 2) in mature and old cocoa plantations in Bakoa (Table 4).

Despite these site-specific dynamics with decline in accessible cocoa yield in Talba and stability in Bakoa as plantations aged, accessible yield was generally higher in Talba than in Bakoa, except for the plantations older than 60 years, which showed similar values in both sites.

In Bakoa, cocoa tree density tended to increase up to the age of 60 years old, indicating a permanent rejuvenation of the plantations. Rejuvenation was accompanied by the pruning of senescent cocoa trees, as evidenced by the increase in the number of multi-stem (type 4) cocoa trees. These combined practices were therefore responsible for sustaining cocoa production.

Conclusion

The study underlined different cAFS management strategies in two different cocoa production sites. Compared to Bakoa, Talba is a site with more suitable soil conditions for cocoa growth. The strategy

Fig. 4 Principal component analysis of contribution (%) to total yield of architectural types of cocoa trees. Grey squares (age category of plots) and triangles (site) represent the centroids of plots according to these factors. Site (Bakoa and Talba) and age category of plots were added as supplementary variables and did not participate to the ACP

<figure><img src="image_17.png" /></figure>
<figure><img src="image_18.png" /><figcaption>**Fig. 5** Variations of the contribution to total yield of cocoa architectural types 2, 4 and 5 in Bakoa and Talba according to the age of plantations. Linear regressions show the significant</figcaption></figure>

trends in both study sites (no regression means no statistical significance). Black is for Talba. Grey is for Bakoa. R²: coefficient of determination

undertaken in Bakoa showed a renewal process of the cacao stand allowing for a relatively stable yield over the long run. The strategy undertaken in Talba underlined lower associated tree densities and C storage but higher average cocoa yields than in Bakoa. However, in Talba, cAFS went through a steep decrease in the cocoa tree densities and lack of rejuvenation, which led to a steadily decrease of the yields after 40 years old.

Our results highlight the fact that in Talba—a former pioneer front where forest is still available—the rejuvenation processes of cocoa plantations are poor and will probably lead to further forest degradation in the years to come if nothing is done. They also point out that, in a context where land is no longer available, continuous rejuvenation of cocoa agroforestry systems enable cocoa cultivation and support its production over the very long run, while sustaining other ecosystem services.

However, in this region, there is a need to introduce practices that would help sustain higher yields (e.g. nurseries with improved germplasm) and/or better incomes (e.g. certification of ecosystem service provision, market development for co-products). If Cameroon wants to increase its production, while ensuring a better income for farmers and

guaranteeing cocoa that complies with the new ecological rules of consuming countries, offering training and incentives to farmers to implement rejuvenation of cocoa farms should be considered as part of this strategy.

**Acknowledgements** This study was carried out in partnership with the Institute of Agricultural Research for Development (IRAD, Cameroon) and the French Agricultural Research Centre for International Development (CIRAD, France) within the framework of the Research Platform in Partnership “DP Agroforesterie Cameroun”. We thank Agoume Alfred, Jean Paul Bidias and Théophile Yana for their help with field data collection. This work was mainly supported by the BNP Paribas Foundation through the SoCa project (no. 306735/00), as part of its Climate Initiative program. This work received additional support funded by the European Union under GA N°101083653, project CANALLS. Views and opinions expressed are howerer those of the authors only and do not necessarily reflect those of the European Union. The European Union can not be held responsible of them.

**Author contribution** Jean Guy Ndje Mbile: Conceptualization, Data curation, Data analysis, Investigation, Methodology, Writing—original draft, Writing—review & editing. Stéphane Saj: Investigation, Data analysis, Writing—review & editing. Seguy Enock: Investigation, Data curation. Jean-Michel Harmand: Conceptualization, Investigation, Data analysis, Writing—review & editing, Supervision Armand William Mala: Writing—review & editing, Supervision.
**Funding** Open access funding provided by CIRAD.

**Data availability** No datasets were generated or analysed during the current study.

**Declarations**

**Conflict of interest** The authors declare no competing interests.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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