A dataset on above- and below-ground traits of 21 species found in banana cropping systems, cultivated individually

Abstract

The data presented in this article describe 21 species that can be found in banana cropping systems: 17 cover crops species, 2 spontaneous species and 2 cultivars of banana. The cover crop species belongs mainly to Fabaceae family, but also to Poaceae, Euphorbiacea and Asteraceae. Four repetition of each species were cultivated individually, in the field, under non-limiting conditions. 40 variables were measured on whole plant, leaves and roots, at flowering or after six months of growth for longer cycle species. This dataset is made available to provide data on these species, enable comparisons between datasets and meta-analysis on cover crop or on species presented in arable fields. The data presented in this article were used in the research articles entitled “Trait-based characterisation of cover plants' light competition strategies for weed control in banana cropping systems in the French West Indies” (Tardy et al. 2015) and “Trait-based characterization of soil exploitation strategies of banana, weeds and cover plant species” (Tardy et al. 2017).

Specifications Table

Subject	Agricultural and Biological Sciences (General)
Specific subject area:	Description of aboveground and underground traits related to competition for resources of 17 cover crops, 2 spontaneous species and 2 cultivars of banana.
Type of data:	Table
How data were acquired:	Field measures of plants grown individually in the field. Instruments and methods: Scanner and WinRhizo Pro-analytical software (Regent Instruments) for leaf and root measurements 10 cm × 10 cm mesh grid positionned on vertical soil profiles for root impacts observations CHN analyser (Elementar Vario Macro Cube) and Dumas method for leaf total N quantification
Data format:	Raw
	analysed
Parameters for data collection:	Type of soil: andosols
	Irrigation: rain-fed regime, cumulated annual precipitation 2829 mm Fertilisation: 50 g of urea (46% N) applied at the base of each plant at the beginning of the experiment.
	Temperature: 25.6 °C averaged over the experiment, ranging from 22.8 °C to 29.7 °C.
	Plants were grown individually, in the field, in separated 16 m² plots.
Description of data collection:	The data were collected on each plants (4 per species/cultivars) at flowering for short cycle species, and after ∼6.5 months of growth for longer cycles or perennial plants. Well-exposed leaves were separated to determine some traits according to standardized protocols in ecology (SLA, LDMC, LNC). The rest of the plants were separated into stems, petioles and leaf blades and weighted. A 1-m deep and 1-m wide trench that was dug 20 cm from the base of each plant. The root intersections in the vertical soil profile were counted on a 5 cm × 5 cm mesh grid. For each plant, three cubes of 1000 cm3 of soil samples were removed at different positions in the root system.
Data source location:	City/Town/Region: Experimental station of Neufchateau, Capesterre Belle Eau Country: Guadeloupe, French West Indies Latitude and longitude (and GPS coordinates) for collected samples/data: 16°05′N, 61°35′W
Data accessibility:	Repository name: Cirad Dataverse Data identification number: / Direct URL to data: doi:10.18167/DVN1/HIEXNF
Related research article:	Tardy F., Damour G., Dorel M., Moreau D. 2017. Trait-based characterization of soil exploitation strategies of banana, weeds and cover plant species. PlosOne, 12(3): e0173066. http://dx.doi.org/10.1371/journal.pone.0173066 Tardy F., Moreau D., Dorel M., Damour G. 2015. Trait-based characterisation of cover plants' light competition strategies for weed control in banana cropping systems in the French West Indies. European Journal of Agronomy, 71: 10–18. http://dx.doi.org/10.1016/j.eja.2015.08.002

Value of the Data

• The data represent leaf, root and plant trait values of 21 species that can be found in banana cropping systems: 17 cover crops species, 2 spontaneous species and 2 cultivars of banana. They could be used by other researchers who need data on these species/varieties.

• The data enable other researchers to compare their own data with this dataset and to extent their analysis.

• These data could be used in meta-analysis on cover crops or on species present in arable fields.

Data description

The dataset presented in this article (doi:10.18167/DVN1/HIEXNF) is composed of 40 variables measured on 17 species of cover crops, 2 spontaneous species widely present in banana agrosystems in the French West Indies and 2 cultivars of banana, at flowering or after six months of growth for longer cycle species. The banana cultivars were: cultivar ‘902′ (MusaAAA, Cavendish subgroup, Bcav), which is currently used for produce bananas for export all over the world, and the hybrid cultivar‘Cirad925’ (Musa AAA, a new synthetic hybrid from CIRAD, B925), which shows improved resistance to the fungus Mycosphaerella fijiensis. The list of the species and varieties studied is provided in Table 1, along with their taxonomic groups, families and type (cover crop, spontaneous, banana). The cover crop species belongs mainly to Fabaceae family (12 species), but Poaceae (3 species), Euphorbiacea (1 species) and Asteraceae (1 species) were also studied. The spontaneous species belongs to Asteracea and Cucurbitacea families. The list of the variables is provided in Table 2 and 3. Some of them refer to whole plant (7 variables), leaves (21 variables), and roots (12 variables). Only one variable is a categorical variable, the other ones were quantitatively measured. Some variables are raw variables, while others were calculated. Calculation formulas are provided in Table 2. The length of the growth period before flowering (and the observation) is also provided.

Table 1.

List of the species/cultivars included in the dataset.

Abbreviation	Full names	Taxonomic group	Family	Type
AP	Arachis pintoi	dicot	Fabaceae	cover crop
B925	Musa SPP., AAA group, VAR. Cirad 925	monocot	Musaceae	banana
Bcav	Musa SPP., AAA group, VAR. Cavendish	monocot	Musaceae	banana
BD	Brachiaria decumbens	monocot	Poaceae	cover crop
BP	Bidens pilosa	dicot	Asteraceae	spontaneous
BR	Brachiaria ruziziensis	monocot	Poaceae	cover crop
CCG	Cajanus cajan VAR. Guadeloupe	dicot	Fabaceae	cover crop
CP	Centrosema pascuorum	dicot	Fabaceae	cover crop
CS	Crotalaria spectabilis	dicot	Fabaceae	cover crop
CZ	Crotalaria zanzibarica	dicot	Fabaceae	cover crop
DL	Dolichos lablab	dicot	Fabaceae	cover crop
GS	Gliricidia sepium	dicot	Fabaceae	cover crop
MD	Mucana deeringiana	dicot	Fabaceae	cover crop
N	Vigna unguiculata VAR. David	dicot	Fabaceae	cover crop
NW	Neonotonia wightii	dicot	Fabaceae	cover crop
M	Momordica charantia	dicot	Cucurbitacea	spontaneous
PN	Paspalum notatum	monocot	Poaceae	cover crop
PP	Pueraria phaseolides	dicot	Fabaceae	cover crop
RC	Ricinus communis	dicot	Euphorbiaceae	cover crop
SG	Stylosanthes guianensis	dicot	Fabaceae	cover crop
TP	Tagetes patula	dicot	Asteraceae	cover crop

Table 2.

List of the aboveground variables provided in the dataset.

Abbreviations	Variable names	Units	Organs	Calculation
H	Standing vegetative height	cm	plant
W1	Maximal crown width	cm	plant
W2	Crown width perpendicular to W1	cm	plant
A	Crown projected area	m²	plant	pi * W1* W2
DWs	Stem dry weight	g	plant
DWb,we	Leaf blade dry weight of well-exposed leaves	g	leaf
DWp,we	Petiole dry weight of well-exposed leaves	g	leaf
DWleaf,we	Leaf dry weight of well-exposed leaves	g	leaf	DWb,we + DWp,we
DWb	Leaf blade dry weight	g	leaf
DWp	Petiole dry weight	g	leaf
DWleaf	Leaf dry weight	g	leaf	DWb + DWp
BMa	Aboveground dry biomass	g	plant	DWs + DWleaf
PBR	Petiole to leaf blade weight ratio	g/g	plant	DWp/DWb
LMFab	Aboveground leaf mass fraction without petioles	g/g	leaf	DWb/BMa
LMFa	Aboveground leaf mass fraction with petioles	g/g	leaf	DWleaf/Bma
LDMC	Leaf dry matter content	mg/g	leaf
LDMCps	Leaf dry matter content at plant scale	mg/g	leaf
SLAb	Specific leaf area without petioles	m²/kg	leaf
SLA	Specific leaf area with petioles	m²/kg	leaf
SLAb,ps	Specific leaf area without petioles at the plant scale	m²/kg	leaf
SLAps	Specific leaf area with petioles at the plant scale	m²/kg	leaf
LARab,ps	Aboveground leaf area ratio without petioles at the plant scale	m²/kg	leaf	LMFab * SLAb,ps
LARaps	Aboveground leaf area ratio with petioles at the plant scale	m²/kg	leaf	LMFa * SLAb,ps
LARab	Aboveground leaf area ratio without petioles	m²/kg	leaf	LMFab * SLAb
LARa	Aboveground leaf area ratio with petioles	m²/kg	leaf	LMFa * SLAb
LA	Total leaf blade area	m²	leaf	DWb * SLAp,ps
LSA	Leaf to soil ratio	m²/m²	leaf	LA/A
LNC	Leaf dry matter content	%	leaf

Table 3.

List of the underground variables provided in the dataset.

Abbreviations	Variable names	Units	Organs
RDmax	Maximal rooting depth	cm	root
RDmed	Median rooting depth	cm	root
RWmax	Maximal rooting width	cm	root
Nod	Nodule activity	categorical	root
Diam	Mean root diameter	mm	root
SRL	Specific root length	m/g	root
RLD	Root length density	cm/cm3	root
RWD	Root weight density	g/cm3	root
RID0–20	Root impact density in the 0–20 soil layer explored by the roots	/dm²	root
RID20–40	Root impact density in the 20–40 soil layer explored by the roots	/dm²	root
RID40–60	Root impact density in the 40–60 soil layer explored by the roots	/dm²	root
RID60–80	Root impact density in the 60–80 soil layer explored by the roots	/dm²	root

Experimental design, materials, and methods

The experiment was conducted at the CIRAD experimental station of Neufchâteau in Guadeloupe (French West Indies), for a period of six months (24 April – 6 November 2013), in a 0.4 ha field previously used as fallow [1]. Soil was andosol (FAO World reference base for soil resources) and plants were rainfed. Cumulated precipitation, mean temperature and mean total solar radiation provide favourable conditions for plant growth all year round (respectively 2829 mm, 25.6 °C and 462 +/− 40 MJ m² month⁻¹ over the period of the experiment). Fertilisation and weed management around the plants [1; 2] were conducted in order to ensure non-limiting conditions of plant growth and to assess their growth potential in the field. Four plants of the twenty one species/cultivars (see ‘Data description’ and Table 1) were sown manually in separate 16 m² plots distributed randomly within 6 blocks in the field. These four plants corresponded to four repetitions per species/cultivar. On each plants, we measured variables and traits that we assumed related to resource acquisition [see 1; 2]. Traits were measured on each plants i) for short cycle species, when half the twigs had flowered, ii) for long cycles or perennial plants, at the end of the experiment (i.e. after ∼6.5 months of growth). The length of this growth period was reported as the number of days after sowing (DAS). Traits measurements methods are provided in the related research articles [1; 2], however, we provide deeper information below.

Aboveground measurements

All measured variables are presented in Table 2.

The standing vegetative height and crown widths were measured at one sampling date per species, with a tape measure. Standing vegetative height (H) was measured from the bottom of the plant at the soil interface to the top of the higher vegetative organ, without stretching the plant. We considered that the crown projection on the soil could be modelled by an ellipse. Two crown widths were then measured: W1, the maximal crown width and W2, the crown width perpendicular to W1. The crown projected area (A) was then calculated (Table 2).

At the top of each plant, three well-exposed leaves were harvested precociously, according to standardized protocols for the measurement of SLA [3]. Just after harvest, the leaves were placed in a plastic bag containing wet paper and stored in a cooler for less than 15 min. Then, the petioles1 and leaf blades were weighed and scanned at 200 dots per inch (scanner Epson expression 10,000XL Pro) separately. They were then oven dried at 70 °C for 48 h and weighted again. Petioles and leaf blades area were measured with WinRHIZO Pro 2009a software (Regent Instruments, Quebec, Canada). The dry weight of the leaf blades and petioles of the well-exposed leaves (DW_b,we resp. DW_p,we) were registered. The dry weight of the well-exposed leaves (DW_leaf,we) was calculated (Table 2). The leaf dry matter content (LDMC) was calculated by dividing the fresh biomass of the whole well-exposed leaves (petiole + leaf blade) by their dry biomass. The specific leaf area was calculated in two different ways. The specific leaf area with petiole (SLA) was calculated by dividing the whole leaf area (petiole + leaf blade) by its dry biomass. The specific leaf area without petiole (SLA_b) was calculated by dividing the leaf blade area by its dry biomass.2 Finally, the leaf nitrogen content (LNC) was determined by pooling the sampled well-exposed leaves of the four repetitions per species. LNC was determined as the total nitrogen content on a mass basis, measured according to Dumas method (CHN analyser, Elementar Vario Macro Cube).

A sample of leaves (petioles and leaf blades separately) was then collected on the whole plant to calculated specific leaf areas at the plant scale. To do so, petiole and leaf blade samples were weighed, scanned at 200 dots per inch and oven-dried for 48 h at 70 °C. The specific leaf area with petiole at the plant scale (SLA_ps) was calculated by dividing the whole leaf area of the sample (petiole + leaf blade) by its dry biomass. The specific leaf area without petiole at the plant scale (SLA_b,ps) was calculated by dividing the leaf blade area of the sample by its dry biomass.

The rest of the plant was finally harvested and separated into stems, petioles and leaf blades. Each component was weighed separately, oven-dried for 48 h at 70 °C and then weighted again. The leaf dry matter content at the plant scale (LDMC_ps) was calculated by dividing the total fresh biomass of the whole leaves (petiole + leaf blade, including the leaves used for SLAs determinations) by its dry biomass. The dry weight of the stems (DW_s), of the leaf blades (DW_b) and of the petioles (DW_p) (DW_s and DW_p including the leaves used for SLAs determinations) were registered. The total leaf blade area (LA), the leaf to soil ration (LSA), the leaf blade to petiole ratio (PBR), the total leaf dry weight (DW_leaf) and the aboveground dry biomass (BMa) were then calculated as described in Table 2. The aboveground leaf mass fraction with and without petioles (LMFa resp. LMFa_b) were calculated by dividing the leaf dry weight (DW_leaf resp. DW_b) by BMa. The aboveground leaf area ratio was calculated with and without petioles, on well-exposed leaves and at the plant scale (LARa, LARa_b, LARa_ps, LARa_b,ps) by multiplying the corresponding LMF and SLA (see Table 2 for the exact calculation formulas).

Belowground measurements

All measured variables are presented in Table 3.

Belowground traits were assessed, for each plant, in a 1-m deep and 1-m wide trench that was dug 20 cm from the base of the plant. The root intersections in the vertical soil profile were counted on a 5 cm × 5 cm mesh grid. The root impact density in soil layers explored by the roots were calculated as the number of root impacts observed divided by the surface of soil profile explored in this layer. For example, the root impact density in the 0–20 soil layer explored by the roots (RID_0–20) was calculated as the number of root intersections observed in this layer divided by the product of the height of the layer (20 cm) and the distance between the further root observed in this layer and the plant base. The root impact density in the 20–40, 40–60 and 60–80 soil layers explored by the roots (RID_20–40, RID_40–60 and RID_60–80) were calculated similarly. The maximal rooting depth (RD_max) was determined by the deepest root intersection that was observed. The maximal rooting width (RW_max) was determined by the furthest root intersection that was observed from the plant base, whatever its depth. The median rooting depth (RD_med) was calculated as the depth at which 50% of the root intersections were observed.

For each plant, three cubes of 1000 cm³ of soil samples were removed: i) under the base of the plant at a depth of 0 to 10 cm, ii) under the base of the plant at a depth corresponding to half the maximum rooting depth, iii) at half the maximum rooting width and depth. Each sample was carefully washed to collect fine and coarse roots. The presence and activity of nodules (Nod) was assessed with a four-category variable (0: absence of nodules, 1: small white nodules, 2: medium size pink nodules, 3: large pink nodules). The roots were scanned at 400 dots per inch (scanner Epson expression 10000XL Pro-scanner). The length and diameter of each root sample were measured with WinRHIZO Pro 2009a software (Regent Instruments, Quebec, Canada). The mean root diameter (Diam) was calculated by averaging the diameters of the three samples per plant. The roots contained in the three soil samples were then pooled and weighed after drying for 72 h at 70 °C. The specific root length (SRL) was calculated by dividing the total length of the roots in the three samples by their root dry biomass. The root length density (RLD) and the root weight density (RWD) were calculated by dividing, respectively, the total length and the total dry biomass of the roots in the three samples by the cumulated volume of these three samples (i.e. 3000 cm³).

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships which have, or could be perceived to have, influenced the work reported in this article.