Introduction
The adoption of environment-friendly cropping practices is a major challenge for dessert banana growing. Indeed, the cultivation of dessert bananas for export has involved so far intensive monoculture with a high level of chemical inputs, that have detrimental effects. As mostly studied in the French West Indies (FWI), these cropping systems have caused soil and water pollution (Cabidoche et al., Reference Cabidoche, Achard, Cattan, Clermont-Dauphin, Massat and Sansoulet2009; Castillo et al., Reference Castillo, Ruepert and Solis2000; Geissen et al., Reference Geissen, Ramos, de J. Bastidas-Bastidas, Díaz-González, Bello-Mendoza, Huerta-Lwanga and Ruiz-Suárez2010; Houdart et al., Reference Houdart, Tixier, Lassoudière and Saudubray2009) and decreasing soil fertility (Delvaux and Dorel, Reference Delvaux and Dorel1990). Moreover, fertilization is a focus of reflection aimed at reducing applied quantities in banana crop, that reached 400 kg/ha−1 of nitrogen and 800 kg/ha−1 of potassium (Godefroy and Dormoy, Reference Godefroy and Dormoy1988), so as to avoid issues related to mineral fertilizer as leaching, soil acidification and pollution (Cabidoche et al., Reference Cabidoche, Cattan, Dorel and Paillat2002; Sansoulet et al., Reference Sansoulet, Cabidoche and Cattan2007) and to better adapt applied nitrogen quantities to crop requirements (Cabidoche et al., Reference Cabidoche, Cattan, Dorel and Paillat2002).
Alternatives to the use of chemical inputs are being adopted to an increasing extent, mostly in the FWI (Bellamy, Reference Bellamy2013; Blazy et al., Reference Blazy, Tixier, Thomas, Ozier-Lafontaine, Salmon and Wery2010; Tarsiguel et al., Reference Tarsiguel, Dorey, Dorel and Andrieu2023). Prophylactic deleafing is a practice to control black sigatoka disease and reduce the use of foliar fungicides (Guillermet et al., Reference Guillermet, Le Guen, Dorel, Lescot and de Lapeyre de Bellaire2018). Living mulch can be used to control weeds in banana fields instead of herbicides. Living mulch can also enhance the species diversity and provide different services to benefit the banana crop (soil cover, pest control, soil structure improvement) (Damour et al., Reference Damour, Garnier, Navas, Dorel and Risède2015; Djigal et al., Reference Djigal, Chabrier, Duyck, Achard, Quénéhervé and Tixier2012; Carval et al., Reference Carval, Resmond, Achard and Tixier2016). Living mulch can be composed of weed species mechanically controlled or sown cover crops species. Organic fertilizers (e.g. green waste, compost, chicken or cattle manure) are used to replace nitrogen-rich mineral fertilizers such as urea or ammonium sulphate. These organic fertilizers enable to improve soil health providing carbon resources to soil food web (Tabarant et al., Reference Tabarant, Villenave, Risède, Roger-Estrade and Dorel2011) and to limit mineral nitrogen leaching due to the gradual release of mineral nitrogen from organic matter mineralization (Niedziński et al., Reference Niedziński, Sierra, Łabętowicz, Noras, Cabrales and Millán2021).
Such practices can however lead to suboptimal growing conditions for banana. Prophylactic deleafing reduces the plant’s photosynthetic leaf area, which in turn can decrease the amount of photoassimilates available to the plant and affect banana bunch weight. Living mulch may compete with banana plants for soil nutrients, mostly for nitrogen (Dorel et al., Reference Dorel, Lakhia and Achard2023), and reduce the nitrogen availability for banana (Achard et al., Reference Achard, Fevrier and Estrade2018). Mineral nitrogen release with organic fertilisers in banana crop is generally lower than with mineral fertilizers (Dorel et al., Reference Dorel, Lakhia and Achard2023) and depends on factors such as temperature and soil water content that are not controlled by growers. Nitrogen is a major nutrient for banana nutrition, and its deficit may impair the crop yield. Indeed, low nitrogen availability can delay flowering (Damour et al., Reference Damour, Ozier-Lafontaine and Dorel2012; Dorel et al., Reference Dorel, Lakhia and Achard2023; Lahav, Reference Lahav and Gowen1995; Nyombi et al., Reference Nyombi, van Asten, Corbeels, Taulya, Leffelaar and Giller2010), reduce the bunch weight (Lahav, Reference Lahav and Gowen1995; Nyombi et al., Reference Nyombi, van Asten, Corbeels, Taulya, Leffelaar and Giller2010; Torres et al., Reference Torres, Sánchez, Cayón, Magnitskiy and Darghan2014) and thus decrease the banana yield.
A solution to this problem would be to crop cultivars that perform well under these suboptimal conditions induced by the agroecological practices described above.
Cavendish banana cultivars currently used have been evaluated and selected only for non-limiting cropping conditions (Cabrera Cabrera and Galán Saúco, Reference Cabrera Cabrera and Galán Saúco2005; Eckstein et al., Reference Eckstein, Fraser, Husselmann and Temple Murray1998; Fonsah et al., Reference Fonsah, Adamu, Okole and Mullinix2007; Galán Saúco et al., Reference Galán Saúco, Cabrera Cabrera, Hernàndez Delgado and Rodriguez Pastor1998; Nuno et al., Reference Nuno, Ribeiro and Alcino da Silva1998; Robinson et al., Reference Robinson, Nel and Eckstein1993). The latter studies revealed that banana cultivars of the Cavendish group exhibited differences in terms of morphology and yield in non-limiting conditions. However, cultivars that can perform well under suboptimal conditions have yet to be identified.
In this context of changes in farming practices to improve the sustainability of banana cropping system, the principal objective of the study was to find Cavendish cultivars that can perform in cropping systems where agroecological practices are implemented. The specific objectives were firstly (i) to compare the performance of 12 different Cavendish cultivars in the suboptimal conditions that could occur with the practices implemented as alternative to chemical inputs in the FWI. More precisely, we focused on conditions resulting from low organic fertilization and maintenance of weed live mulch as alternatives of high mineral fertilization and chemical weeding (reduction of the amount of soil nutrient available for the banana), and prophylactic deleafing as alternative to control of black sigatoka with fungicide (reduction of leaf area and consequently photosynthetic assimilation), and secondly, (ii) to find the most performant cultivar for each suboptimal cropping condition. An experiment was conducted in Guadeloupe (FWI) to assess the performance of 12 Cavendish cultivars with different crop management modalities that were, on one hand, cultural practices generally used in industrial banana crops (high mineral fertilization, chemical weed control and chemical control of black sigatoka associated to minimum prophylactic deleafing) and on the other hand their agroecological alternatives (low organic fertilization, weed live mulch and severe prophylactic deleafing). This aimed to induce contrasted conditions in terms of plant leaf area and soil nutrient availability, mostly nitrogen. A cultivar was considered with high performance in a suboptimal cropping condition if (i) it exhibited a higher yield than the other cultivars in this condition, and (ii) it had a low relative yield gap between the plot considered as the agricultural potential and the suboptimal condition.
Material and methods
Experimental design
The experiment was conducted at Capesterre-Belle-Eau (Guadeloupe, FWI), in the Bois-Debout banana plantation (16°01’43’’N, 61°35’48’’ W, average annual rainfall 2,600 mm, mean temperature 26°C) from June 2019 to March 2021, during two banana crop cycles. The soil is classified as Andosol (FAO, 2014). Analysis of the 0–40 cm soil layer is presented in Table 1. Banana trees were planted after three years of sugarcane crop. The soil was ploughed twice before planting with a spading machine. The planting materials were micropropagated derived plants supplied by Vitropic SA, hardened two months in greenhouse before the planting in June 2019.
Soil chemical properties of the experimental crop between 0 and 40 cm deep. CEC: cation exchange capacity
Four crop management modalities were applied on four 0,22 ha elementary plots (see Supplementary Information Figure S1): i) high mineral fertilization, chemical weed control and minimum prophylactic deleafing (N + L+), ii) high mineral fertilization, chemical weed control and severe prophylactic deleafing (N + L−), iii) low organic fertilization, weed living mulch, and minimum prophylactic deleafing (N−L+) and iv) low organic fertilization, weed living mulch and severe prophylactic deleafing (N−L−). In each elementary plot, a totally randomized design plot was planted with 12 cultivars and 15 repetitions per cultivar. One repetition consisted of one plant. An edge row around each plot was planted with the same cultivars randomly disposed. The plants were studied at the individual scale and planted in single row with 3 m × 3 m spacing, assuming that plant density was low enough to avoid competition for light between adjacent plants, even between size extremum cultivars (e.g. Dwarf Cavendish and Robusta).
The bunches were not bagged, and no fruit ablation was applied. To avoid seasonal variation due to rain differences among the cycle, the plants were irrigated all year round with a drip system. A mixture of paraffinic oil and triazole fungicide was sprayed 3 times per year with an air-blast sprayer to control black sigatoka disease on the whole experimental plot.
Crop management modalities
Each management modality was a combination of practices having an effect on banana leaf area (L modalities: L+/L−) and practices having an effect on soil nutrient availability (N modalities: N+/ N−):
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• Minimum prophylactic deleafing (L+) consisted in removing weekly the necrotic part of the leaves to limit black sigatoka disease dissemination.
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• Severe prophylactic deleafing (L−) consisted in completing the minimum prophylactic deleafing by the removal of additional healthy leaves to maintain a difference of three leaves between the minimum deleafing and the severe prophylactic deleafing. The purpose of this practice was to simulate a case of high pressure of black sigatoka without fungicide control.
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• High mineral fertilization and weed chemical control (N+) consisted of an application of 200 g per plant of complete mineral fertilizer (NPK 14-4-28) each month, that was higher than the amount applied in the FWI productions, and in a systemic herbicide sprayed 4 times per year to avoid the competition between weeds and banana. These practices aimed at providing sufficient amount of nutrient available for the banana that will not limit its production.
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• Low organic fertilization and weed living mulch (N−) consisted in an application of 200 g per plant of organic fertilizer AB’FLOR® (NPK 7–5–7) each month that was under the recommended 400 g in the context of FWI’s Andosol. This fertilizer is a mixture of vegetal compost and animal products and present mineral fertilizer equivalency values of 0.5 for nitrogen availability and 1 for potassium and magnesium availability according to results of Peraire-Brudey et al., (Reference Peraire-Brudey, Lakhia and Dorel2022).
Weeds were also mowed 15 cm above ground level each time the vegetal cover height exceeded 50 cm. According to the results of Dorel et al. (Reference Dorel, Lakhia and Achard2023), who used the same organic fertilization with different cover management, for this amount of fertilizer, the competition between weed and banana for nutrients mostly concerned nitrogen and was unsignificant for potassium and calcium.
Moreover, soil content in exchangeable potassium is 2.34 meq per 100 g of soil (Table 1) which represent a reserve of about 3,000 kg of exchangeable K /ha. This reserve was far higher than the requirements for establishing a banana plantation, which are about 1,500 kg of exchangeable K/ha. We thus considered that, even in the N− plots, bananas did not experience any limitation for potassium nutrition.
The objective of this practice was to limit nutrient availability for the banana, and mostly nitrogen, through a low release of mineral nitrogen by organic fertilizer and weed competition for nitrogen uptake.
Banana cultivars
The experiment was conducted with 12 Cavendish banana cultivars presented in Table 2 and also described by Rapetti and Dorel (Reference Rapetti and Dorel2022). These cultivars can be grouped in three types depending on their height, according to Robinson and Galán Saúco (Reference Robinson and Galán Saúco2010) and Simmonds (Reference Simmonds1954): Dwarf, Giant and Robusta type. Some morphological characteristics of the cultivars are presented in Supplementary Information (Table S1).
Description of the cultivars studied. They are all commercial cultivars from Vitropic SA
Measurements
Only measurements performed on the second crop cycle were presented because no significant effect of the crop management modalities on banana growth was observed at the first cycle (see Supplementary Information, Figure S2). It could be explained, at first, by a high black sigatoka disease pressure during the first crop cycle which makes impossible to remove additional healthy leaves after minimum prophylactic deleafing (L+) without jeopardize plant survival. Consequently, there was no difference in leaf area between L+ and L−. Then, the degradation of the residues of the previous sugarcane crop could have also offset, at the beginning of the first crop cycle, the effect of N− practices aiming to reduce nutrient availability.
All the studied variables are presented in Table 3. To verify the differences between the practices L+ and L−, the number of living leaves at bunch emergence (NLLbe) and harvest (NLLh) was counted. To quantify the differences of nitrogen availability between practices N+ and N−, soil mineral nitrogen content ([N]soil) was assessed monthly from May 2020 to October 2020. The plant nitrogen status was also assessed through chlorophyll-metre readings (SPAD-502 Minolta, Bullock and Anderson, Reference Bullock and Anderson1998) performed on the third leaf at the bunch emergence.
Presentation of the measured and calculated (*) variables
Yield at the plant scale was considered as the weight of bunches produced per year. It depended on the bunch weight and on the number of bunches produced per year, which was called here the production rate. The bunch weight depended on the fruit number per bunch and on the individual fruit weight, whose diameter was an indicator. Bunches were harvested 900 degree days after bunch emergence calculated in thermal time with a base temperature of 14°C (Ganry and Sioussaram, Reference Ganry and Sioussaram1978). A tolerance of ± 90 degree days was accepted to optimize the fruit size. The fruit number and the weight of each bunch were determined at harvest. The diameter of two fruits of the third hand was also measured. The cycle duration, expressed in year, was calculated as the interval between the first and second cycle harvests. The production rate (year−1) was calculated for each studied plant as
${1 \over {cycle\;duration}}$
. The yield, at the plant scale, was calculated as follows:
$$Yield{\rm{ }}\;(kg/yea{r^ - }^1) = bunch\;{\rm{ }}weight\;{\rm{ }}\left( {kg} \right)*production{\rm{ }}\;rate\; {\rm{ }}(yea{r^ - }^1).$$
Calculation of Relative Gaps of yield and yield components
It was assumed that cultural practices in N + L+ plot allowed the expression of the agricultural potential of Cavendish plants in the farming area of the study. The agricultural potential was defined as the performance of the crop with non-limiting cultural practices in given environmental conditions. In the other plots (N + L−, N−L+ and N−L−), Relative Yield Gap to the agricultural potential was calculated for each cultivar as follows:
$$\small{Relative \;{\rm{ }}Yield{\rm{ }} \;Gap \;{\rm{ }}in{\rm{ }} \;plot{\rm{ }} \;i = \left( {Yield \;{\rm{ }}in{\rm{ }} \;the \;{\rm{ }}plot{\rm{ }} \;N\, + \,L + - {\rm{ }}Yield \;{\rm{ }}in \;{\rm{ }}the \;{\rm{ }}plot \;{\rm{ }}i} \right)/Yield {\rm{ }} \;in \;{\rm{ }}the \;{\rm{ }}plot \;{\rm{ }}N\, + \,L + }$$
For each yield component (bunch weight, production rate, fruit number, fruit diameter), a Relative Gap to the agricultural potential was similarly calculated for each cultivar.
Statistical analysis
All statistical analyses were performed with R software (version 3.5.3) (R Core Team, 2018). For each plot and variable, the effect of the cultivar on the variables was assessed using ANOVA (α = 0.05). A Tukey post hoc test was used to compare average values per cultivar.
The difference in the number of leaves at bunch emergence (NLLbe) and at harvest (NLLh) between the plots L+ and L− was assessed using a Kruskall-Wallis test. The difference in SPAD values between N+ and N− was assessed with a Kruskall-Wallis test.
The effects of L modality (L+/L−), cultivars and their interaction, whatever nutrient availability involved by the N modality (N+/N−), were assessed with ANOVA test performed with a linear mixed model with N modality as random effect. Conversely, the effects of N modality, cultivars and their interaction, whatever the L modality, were assessed with ANOVA test performed with a linear mixed model with L modality as random effect. Linear mixed models were performed using the function ‘lmer’ (Kuznetsova et al., Reference Kuznetsova, Brockhoff and Christensen2017). For every variable, the most parsimonious model was selected with a backward stepwise procedure. The effect size of the factors selected in the final models was assessed by calculating eta squared values of each factor (Cohen, Reference Cohen1973, Reference Cohen1988). The effect was considered small when 0.01≤ eta2 <0,06, medium when 0.06≤ eta² < 0,14 and large when eta² ≥0,14.
Results
Differences of nitrogen availability and NLL in the plots
There were significant effects of the crop management modalities on NLL and mineral soil nitrogen dynamics. Indeed, at first, there was significantly more NLLbe and NLLh in L+ than in L− (Fig. 1), as shown by the Kruskall-Wallis test results.
Number of living leaves at bunch emergence (NLLbe) and at harvest (NLLh) in the second crop cycle plots with minimum prophylactic deleafing (L+) and severe prophylactic deleafing (L−). The error bars represented the standard errors, derivated from the 360 repetitions for each L modality. Kruskall-Wallis results indicated highly significant differences between L+ and L− (p-value <0.001), in terms of NLLbe and NLLh.
Then, Fig. 2 shows that [N]soil was higher in N+ plots and constantly above 70 mg/kg. In N− plots, [N]soil was remained close to 25 mg/kg. Godefroy and Dormoy (Reference Godefroy and Dormoy1983) considered that, in banana plantation, 25 mg/kg was a minimum critical threshold for banana nutrition and that above 50 mg/kg, soil mineral nitrogen was excessive and easily leached. Moreover, the chlorophyll content of the third leaf was significantly higher with N+, as shown by the SPAD results presented in Fig. 3. Thus, those results highlighted differences of nitrogen status in soil and in plant between N+ and N−, suggesting a nitrogen shortage in the latter modality.
Soil mineral nitrogen concentration in N+ and N− plots from May 2020 (beginning of the second cycle in every plot) to October 2020 (N+ harvest and beginning N− bunch emergence).
SPAD values in the plots with high mineral fertilization and weed chemical control (N+) and low organic fertilization and weed living mulch (N−) in the second crop cycle. The error bars represented the standard errors, derivated from the 360 repetitions for each L modality. Kruskall-Wallis results indicated highly significant differences between N+ and N− (p-value <0.001).
Yield and yield components in each plot
Cultivar yields in the four elementary plots are presented in Fig. 4. N + L+ plot had the highest yields, followed by N + L−, N−L+ and N−L−, with mean yields of 91 kg/year−1, 84 kg/year−1, 55 kg/year−1 and 34 kg/year−1, respectively. The ANOVA findings revealed significant differences between cultivars in the plots N + L+, N + L− and N−L+. Ame01 and Mat12 had the highest yields in N + L+ and N + L−, whereas Gua02 had a significantly higher yield in N−L+ compared to the other cultivars. In every plot, DC01 had the lowest yield.
Average yield of cultivars in the four elementary plots: N + L+: high mineral fertilization, chemical weed control and minimum prophylactic deleafing; N + L−: high mineral fertilization, chemical weed control and severe prophylactic deleafing; N−L+: low organic fertilization, weed living mulch, and minimum prophylactic deleafing; N−L−: low organic fertilization, weed living mulch and severe prophylactic deleafing. ANOVA: n.s.: non-significant; * <0.05.
It was noteworthy that the yield differences between plots were not similar between the cultivars. Indeed, Mat12, Gua01 and Ruby had the same yield in N + L+ as in N + L−. Gua02 was the only cultivar to have a higher yield in N−L+ than in N + L−.
When focusing on the yield components in the plot N + L+ where the cultivars expressed their agricultural potential in this environment (Table 4), the Tukey test findings showed few significant differences between most of the cultivars. However, some cultivars stood out, including Ame01, which had the highest yield in this plot as well as the highest bunch weight with large fruits. Conversely, DC01 exhibited the lowest yield and lowest bunch weight and the shortest fruit despite having the highest fruit number.
Average yield components (production rate, bunch weight, fruit number and diameter) of cultivars in the four plots. ANOVA: n.s.: non-significant; **: <0.01; ***: <0.001. Different letters indicate that the average values are significantly different (Tukey test, α = 0.05)
The yield components of the three other plots (N + L−, N−L+, N−L−), as presented in Table 4, revealed some marked differences between cultivars. Comparing the yield components of N + L+ with those in the other plots, N + L+ exhibited the highest values, followed by N + L−, N−L+ and finally N−L−. Despite the low values for all yield components in N−L−, all fruit diameters were above 30 mm, which is the minimal diameter required to market bananas. Firstly, it was noteworthy that for every plot, DC01 had the lowest bunch weight, the smallest fruit diameter, but the highest fruit number. Secondly, Poyo always had the lowest fruit number, yet while always having one of the highest fruit diameters. Thirdly, Gua02, which exhibited the highest yield in N−L+, had the highest production rate in this plot. Concerning the other cultivars, the Tukey tests showed few differences in terms of yield components in all plots.
Effect of crop management modalities on yield and yield components
Interferential models (linear mixed effects) showed that yield and most of yield components were affected both by the crop management modality (L or N) and the cultivar, but not by their interaction (Table 5). Only the production rate, whatever the N modality, only depends on the cultivar effect and not the L effect. Also, the cultivar had a small effect on production rate, whatever the L modality, with eta² of 0,01.
Most parsimonious linear model selected to explain the effect of cultivar (cult), crop management modality (L or N) and their interaction, whatever the N or L modality (1|N, 1|L), on the yield and its components. The size effect (eta²) of each factor along with its class of p-value was reported. P-value: *: <0.1; **: <0.01; ***: <0.001 ; n.s. : non-significant
The size effect of cultivar and of crop management modality was not the same between L and N. Indeed, in the models where L effects were tested, the cultivar eta² was higher than the L eta² for two variables (fruit number, fruit diameter) among four (no significant effect of L for production rate). On the opposite, in the models where N effects were tested, the cultivar eta² was far lower than the N eta² for all the studied variables, except for the fruit diameter.
Relative gaps of yield and yield components
The Relative Gaps of yield and yield components (production rate, bunch weight, fruit number and fruit diameter) measured in each suboptimal plots (N + L−, N−L+, N−L−) and for all cultivars are presented in Fig. 5. For each variable, the Relative Gaps values in N + L− were lower than the Relative Gaps values in N−L+ that were in turn lower than the Relative Gaps values in N−L−. The Relative Gaps of yield and yield components in N−L− were higher and are further presented below. The Relative Gaps of fruit diameter were low.
Average relative gaps for yield (line 1), production rate (PR) (line 2), bunch weight (BW) (line 3), fruit number (FN) (line 4) and fruit diameter (FD) (line 5) in N + L− (on the left), in N−L+ (in the centre) and in N−L− (on the right). The error bars represented the standard errors, derivated from the 15 repetitions for each cultivar.
There were few differences between N + L+ and N + L−, as the mean Relative Gaps values in N + L− were less than 0.25 for all variables and cultivars. Concerning the Relative Yield Gaps in N + L−, Mat01, Poyo and Gua02 had the highest ones. For the other cultivars, the values were less than 0.12. Ruby, Gua01, Mat03 and Mat12 had very low Relative Yield Gaps in N + L−, i.e. under 0.05. Concerning Relative Production rate Gap in N + L−, the values were under 0.10 for all cultivars, while negative values were obtained for five cultivars (Mat12, Mat03, Gua01, Mat11 and Ruby). Ruby was the sole cultivar with a null Relative Bunch weight Gap in N + L−, whereas Gua02 had the highest one (0.22). For all cultivars, there were few differences in fruit number, with Relative Fruit number Gaps in N + L− being less than 0.10.
There were noteworthy differences between N + L+ and N−L+, notably for the yield, with Relative Yield Gaps in N−L+ ranging from 0.19 to 0.52, while Poyo, Ame01, Mat01 and DC01 had the highest values. In contrast, Gua02 had the lowest Relative Yield Gap in N−L+ (< 0.19), followed by Ruby and Mat03. Gua02 was also the cultivar with the lowest Relative Production rate Gap in N−L+ (< 0.10). Ruby was the only cultivar with a Relative Bunch weight Gap in N−L+ of less than 0.05, followed by Gua02. For the other cultivars, the values were higher than 0.20.
Marked differences appeared between N + L+ and N−L−, with Relative Yield Gaps in N−L− higher than 0.50. For all cultivars, the Relative Gaps values in N−L− in term of production rate, bunch weight and fruit number ranged from 0.25 to 0.50. Otherwise, there were no clear differences between cultivars.
Discussion
Difference of the highest yielded cultivars according to the crop management modalities
The results showed that the highest yields were obtained by Ame01 in N + L+, Mat12 in N + L− and Gua02 in N−L+. In the N + L+ plot, Ame01 had the heaviest bunches with the largest fruits, thereby explaining its higher yield. In the N + L− plot, Mat12 had average values for all yield components. Finally, in N−L+, Gua02 had the highest production rate and the highest bunch weight, so it had the highest yield in this plot. This suggested that the flowering delay that may be induced by nutrient shortage, as described for nitrogen deficiency (Damour et al., Reference Damour, Ozier-Lafontaine and Dorel2012; Dorel et al., Reference Dorel, Lakhia and Achard2023), could be less marked with regard to Gua02 as compared to the other cultivars. These results showed that, depending on the cultivars and the plot, the yield components responsible for the high yields differed.
However, DC01 had the lowest yield in every plot, with the lightest bunches and smallest fruits despite the high fruit number. This result differed with those of Cabrera Cabrera and Galán Saúco (Reference Cabrera Cabrera and Galán Saúco2005) who found that Dwarf Cavendish cultivars performed better than Giant Cavendish banana cultivars such as Grande Naine and Williams in the Canary Islands. Dwarf banana cultivars are known to perform well in subtropical regions. DC01 might not be adapted to the tropical climatic conditions of the French West Indies and thus not express its full potential in this environment.
This study showed the high productivity of Ame01, i.e. a Robusta cultivar, in N + L+ with plot with high mineral fertilizer and minimum deleafing. Historically, Robusta cultivars were abandoned in favour of Giant cultivars because of their smaller stature and their better yields. Similar findings were obtained in some studies involving Cavendish cultivar assessment, where the authors found that Giant cultivars such as Grande Naine and Williams had a greater agronomic potential than Robusta cultivars, such as Poyo, Valery and Americani (Robinson et al., Reference Robinson, Nel and Eckstein1993; Stover, Reference Stover1982). In the light of our results, despite of its height, Ame01 should be reconsidered for some banana production, notably in area where the risk of falling is low due to the absence of cyclone and to a good telluric parasitism control.
Effects on the banana yield of suboptimal conditions induced by agroecological practices: severe deleafing, low mineral fertilization and weed live mulch
In this study, the yield and yield components significantly depend on the cultivar and the crop management modalities but not on their interaction. Moreover, the eta² values showed that the N modalities, depending on the fertilization and the weed control, had higher effect than the cultivar. That was not the case of L modalities, that depended on the black sigatoka management, which had lower effect than the cultivar for most of the studied variable. This last result suggests than N modalities had higher effect than L modalities, that was strengthened by the values of Relatives Gaps for yield and yield components. In this study, Relatives Gaps for yield and yield components were measured to compare the values in suboptimal cropping conditions and in N + L+, considered as the plot where the cultivars expressed their potential in this farming area. Relative Gaps in N + L− were found to be the smallest values (all values < 0.25), followed by Relative Gaps in N−L+ and finally in N−L−. All values for the latter were above 0.50, with some as high as 0.75. Between-plots differences of the Relative Gaps were more marked regarding the yield, bunch weight and production rate as compared to the fruit number and the fruit diameter.
Our results can be analysed based on the findings of studies focused on the effects of severe deleafing and nutrient shortages due to low fertilizer application or competitive weed on banana growth and yield. Meanwhile, severe deleafing reduced the photosynthetic leaf area and hence the biomass production and yield. Indeed, severe deleafing may decrease the amount of carbohydrates allocated to the bunch and thus the hand and fruit number, fruit diameter and bunch weight (Engwali et al., Reference Engwali, Nfor and Alain2013; Ocimati et al., Reference Ocimati, Ntamwira, Groot, Taulya, Tittonell, Dhed’a, Van Asten, Vanlauwe, Ruhigwa and Blomme2019; Robinson et al., Reference Robinson, Anderson and Eckstein1992). As presented in Turner and Gibbs (Reference Turner, Gibbs and Kema2018), in their study, Turner and Hunt (Reference Turner and Hunt1987) observed a negative effect of severe deleafing before flowering on the number of hands, that depended on the developmental stage of the plant. Indeed, the impact of severe deleafing was higher few weeks before floral induction (between 20 and 11 leaves before flowering) but was null when the defoliation was implied before or after. However, several authors found that deleafing had impacts on the bunch weight only when the plant was left with a certain number of leaves at flowering, i.e. 4 to 10 depending on the author (Daniells et al., Reference Daniells, Lisle and Bryde1994; Ocimati et al., Reference Ocimati, Ntamwira, Groot, Taulya, Tittonell, Dhed’a, Van Asten, Vanlauwe, Ruhigwa and Blomme2019; Robinson et al., Reference Robinson, Anderson and Eckstein1992). Moreover, in response to deleafing, compensatory mechanisms have been observed, with an increase in photosynthetic activity and in the length of the bunch-filling period (Daniells et al., Reference Daniells, Lisle and Bryde1994; Robinson et al., Reference Robinson, Anderson and Eckstein1992; Turner et al., Reference Turner, Fortescue and Thomas2007).
Concerning the effects of nutrient shortage caused by low fertilization or competition with weed, nitrogen is a major chlorophyll component, and its shortage or absence reduces the photosynthetic assimilation rate. The main impacts of fertilization with little or no nitrogen are a reduction in biomass production and flowering delay, that induced lighter bunches, less fruits per brunch and smaller yield (Damour et al., Reference Damour, Ozier-Lafontaine and Dorel2012; Nyombi et al., Reference Nyombi, van Asten, Corbeels, Taulya, Leffelaar and Giller2010; Torres et al., Reference Torres, Sánchez, Cayón, Magnitskiy and Darghan2014). Also, some papers found that competition with weeds or intercrop for nutrient uptake may impair banana crop yield, with less fruits per bunch and a flowering delay (Achard et al., Reference Achard, Tixier, Dorel and Estrade2018; Dorel et al., Reference Dorel, Lakhia and Achard2023), or smaller fruits, lighter bunches and smaller yields (Ocimati et al., Reference Ocimati, Ntamwira, Groot, Taulya, Tittonell, Dhed’a, Van Asten, Vanlauwe, Ruhigwa and Blomme2019). Damour et al. (Reference Damour, Ozier-Lafontaine and Dorel2012) interpreted the cycle duration increase, caused by the flowering delay, as compensatory effect for biomass accumulation. No study had compared the effect of severe deleafing with the effect of nutrient shortage on banana plants, but our results suggested that nutrient shortage, mostly nitrogen, impacted more the banana yield than severe deleafing. Moreover, as compensatory mechanisms in response to deleafing involved the increase of the photosynthetic activity and as nitrogen shortage reduced the photosynthetic capacity, the high value of Relative Gaps in N−L− suggested that the nitrogen shortage greatly affects the deleafing compensatory mechanism that is no longer as effective.
Between-Cultivar difference of stresses effects on the yield
Our results showed no statistical effect of the interaction between cultivar and crop management modalities, but between-cultivar differences in term of Relative Gaps, that can be interpreted as tendencies. For instance, yield and yield components of Ruby were not altered in N + L− relatively to N + L+ while yield and yield components of Gua02 were markedly impaired. Yield and yield components of Gua02 exhibited the lowest decrease in N−L+ compared to N + L+, followed by Ruby and Mat03, whereas DC01 exhibited the highest decrease. Finally, yield and yield components of Mat03 exhibited the lowest decrease in N−L− compared to N + L+. Stress tolerance can be assessed according to the yield stability despite the stress and is generally measured by the yield difference between stressed conditions and the potential (Clarke et al., Reference Clarke, DePauw and Townley-Smith1992; Tollenaar and Lee, Reference Tollenaar and Lee2002). Our experimental design did not include any treatment replication, but the maintenance of the yield and yield components between plots for some cultivars (Ruby, Gua01 and Mat12 between N + L+ and N + L−; Gua02 between N + L+ and N−L+) suggests that these cultivars could be respectively tolerant to the stress induced by severe deleafing and nutrient shortage due to low fertilizer associated to weed live mulch.
Conclusions
As a conclusion, this work showed that the Cavendish banana cultivars exhibited differences in term of yield and yield components in different suboptimal cropping conditions in FWI. It allowed to identify cultivars of interest to be cultivated with alternative practices to chemical inputs or suboptimal conditions due to abiotic stresses. Indeed, Ruby, Gua01 and Mat12 performed well with severe deleafing and thus are interesting for cropping system without chemical fungicide to control black sigatoka or cropping conditions with low photosynthetic activity. Otherwise, Gua02 and Ruby were the most performant with a nutrient shortage resulting from a low organic fertilization and weed living mulch to reduce chemical weeding. Moreover, our results highlighted tendencies of between-cultivars differences in terms of stress effects on the yield, which may suggest that the cultivars of the Cavendish group have differences of tolerance to abiotic stresses. This is a very innovative finding which needs to be invested to confirm the observed tendencies. Indeed, there were very few studies about the diversity with regard to the plant response to abiotic stresses between cultivars within banana groups, such as the Cavendish group and the Plantain one. Thus, there is a need to better characterize the genetic diversity of the cultivated bananas to identify cultivars adapted to various cropping practices and growing contexts.
Supplementary material
To view supplementary material for this article, please visit https://doi.org/10.1017/S0014479724000231
Data availability statement
The experimental data of the trial are deposited on a Dataverse: https://doi.org/10.18167/DVN1/J4MT4P
Acknowledgements
We first thank Guillaume Block de Fribert, the manager of the Bois-Debout banana plantation, for hosting the experiment and for enabling us to properly conduct it. Then, we thank Jérôme Saint-Marc, Rony Saint Hilaire and Dimitri Ramdaya, technicians at the CIRAD research station in Guadeloupe, for helping with field measurements and for the maintenance of the experimental field, and Laura Peraire-Brudey, for her help in field measurements. We also thank Vitropic SA for providing the planting material.
Funding statement
This work was funded by the European Regional Development Fund for the RIVAGE project. The research work was carried out in the framework of the CIFRE scheme, which is financed by the French Ministry of Higher Education, Research and Innovation.
Competing interests
Manon Rapetti was employed by Vitropic SA for a doctoral position. The other authors declare none.
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