Yield and Growth of Maize and Marandu Grass Intercropping in Crop-Livestock Integration in the Cerrado of Matopiba

Abstract

The objective was to determine the growth and yield of maize plants and Urochloa brizantha cv. Marandu (Marandu grass) in a crop-livestock integration system in Eastern Maranhão. Two trials were carried out: (1) maize intercropping x maize monoculture, (2) Marandu grass intercropping x Marandu grass monoculture. The two experiments were conducted in the field, in a randomized block design with plots divided over time. In the trial with maize, eight assessments were made: plant height, number of leaves, stem diameter, leaf area, leaf area index, and grain yield at R6. In the Marandu grass trial, collections were carried out at 12 different times, divided into a first period up to maize harvest and a second post-intercropping period. Canopy height, tiller population density, living leaves per tiller, number of tillers, leaf area, leaf area index (LAI) and leaf:stem ratio were evaluated. Following analysis of variance, “t” test was carried out for cultivation systems and regression analysis for collection times. For the variables analyzed in maize, no significant differences were observed resulting from treatments with intercropping or maize monoculture. As for Marandu grass, negative effects of the intercropping were observed, reducing tiller population density, leaf area and LAI. Marandu grass from the intercropping, even in the weeks following maize harvest, showed a higher leaf:stem ratio due to the preferential allocation of photoassimilates to produce leaves to the detriment of stems.

Keywords:
interspecific competition; biomass partitioning; integrated systems; Urochloa brizantha cv; Marandu; Zea mays.

HIGHLIGHTS

• Production of maize + brachiaria in the Cerrado of Matopiba.

• Growth dynamics in brachiaria plants after intercropping with maize + animal grazing.

• Crop-livestock integration x monoculture.

INTRODUCTION

The adoption of integrated production systems, such as integrated crop-livestock system (ICL), is an alternative that seeks to increase the sustainability of production systems in the Cerrado. These systems consist of intercropping annual commercial crops, especially maize (Zea mays), with perennial forage grasses [¹]. This allows for the provision of various environmental services and increased productivity through nutrient cycling and improved soil fertility [²]. Furthermore, it secures sufficient forage to permit livestock farming in the off-season [³].

The interaction between maize and species of the Urochloa genus can negatively affect growth and development of crops, leading to economic losses and, in some cases, making the system unfeasible [⁴]. To this end, a better understanding of the interaction between species allows growers to make decisions and choose appropriate management practices, thereby achieving success in integrated systems.

Despite the existence of reports in the literature addressing the effects of interspecific competition in intercropping systems involving maize and forage grasses [³], there is a lack of information about variations in the biometric characteristics of plants throughout their development cycle. Likewise, there is no information about the biomass partitioning of forage grasses intercropped with maize, especially for the conditions of the Cerrado in northeastern Brazil. Therefore, it is necessary to evaluate the growth of maize and Marandu grass growing in monoculture and intercropped to optimize the management of integrated production systems [⁵].

In this study, the hypotheses are (i) unlike maize, the biomass production of the forage grass Urochloa brizantha cv. Marandu (Marandu grass) is negatively affected by intercropping and (ii) intercropping with maize affects the biomass partition between the vegetative fractions of the forage grass. Therefore, the objective was to determine the growth dynamics and yield of maize and Marandu grass grown in intercropping and monoculture under the conditions of Eastern Maranhão, Brazil.

MATERIAL AND METHODS

The experiment was conducted under field conditions at Barbosa Farm, located in the municipality of Brejo, Maranhão, Brazil (03°42'44” S; 42°55'44'' W). The soil in the experimental area is classified as dystrophic Yellow Argisol (Ultisol), according to the Brazilian Soil Classification System [⁶], with a sandy loam texture. The region’s biome is Cerrado [⁷,⁸] and the climate is Aw (tropical with a dry period between July and November and a rainy period between December and June) [⁹].

Data on air temperature (maximum, mean, and minimum, in °C) and rainfall (mm) were collected using a meteorological station installed within the experimental area over the crop development cycle. After harvesting the maize grains, data were obtained from the Chapadinha meteorological station, Maranhão [¹⁰]. Total precipitation during the experimental period (from February to November 2022) was 1,108 mm(Figure 1).

Figure 1
Variation in minimum, maximum and mean air temperature and daily rainfall during the experimental period, between February/2022 and November/2022. Data obtained from a meteorological station installed at Barbosa Farm, in Brejo, Maranhão state, Brazil.

Before setting up the experiments, soil samples were collected in the 0-20 and 20-40 cm layers in the experimental area for chemical characterization of soil fertility (Table 1) [¹¹]. The experiments were conducted in a rainfed system, with maize and Marandu grass sown on February 4, 2022, intercropped and in monoculture. Both crops were sown simultaneously, but maize was machine-sown in rows spaced 0.5 m apart and plants spaced 0.25 m apart in the row, while Marandu grass was sown by broadcast. A hybrid maize (MS 3845 status - P3845VYHR [Pioneer® seeds]) was used in monoculture and intercropping systems, with seeds featuring YHR and Leptra® technology. In Marandu grass cultivations, the Marandu grass (Urochloa brizantha cv. Marandu) was used. The total maize stand was approximately 80,000 plants ha^-1, while for Marandu grass, 6 kg ha^-1 of seeds were used.

Table 1
Chemical and granulometric characteristics of the soil in the experimental area, in the 0-20 and 20-40 cm layers. Barbosa Farm, Brejo, Maranhão state, Brazil, 2022.

Layer	pH	SOM	P	K	Ca	Mg	EA	SB	CEC	V	m
cm		g kg-1	mg dm -3	---------------------- cmolcdm-3------------------------						--------------%-------------
0-20	6.00	2.1	17.8	0.05	0.8	0.4	2.7	1.3	4.1	34	two
20-40	5.36	1.47	4.5	0.03	0.2	0.1	3.5	0.5	4.0	12	47
	Cu	Fe	Mn	Zn	B	S	Na	Al	Sand	Silt	Clay
	--------------------mg dm - 3-------------						--cmolcdm-3--		--------%------
0-20	0.09	12	0.39	2.1	0.1	5.4	0.01	0.04	77.1	15.5	7.2
20-40	0.05	203	0.02	0.5	0.1	6.3	0.01	0.44	72.4	19.5	7.9

Before sowing the crops, 1.0 t ha^-1 of dolomitic limestone (88% ECCE) and 0.5 t ha^-1 of gypsum were broadcasted over the whole area. At base fertilization, 340 kg ha^-1 of NPK 12-30-00 formulation (40.8 kg ha^-1 N and 102 kg ha^-1 P₂O₅) were applied directly to the furrow. The first top dressing was carried out 7 days after emergence (DAE) using 200 kg ha^-1 of 10-00-30 NPK (20 kg ha^-1 N and 60 kg ha^-1 K₂O); the second top dressing was done at 30 DAE using 200 kg ha^-1 of 10-00-30 (20 kg ha^-1 N and 60 kg ha^-1 K₂O). The application of fertilizers and pesticides was carried out in accordance with the standard planting and fertilizer management operations at Barbosa Farm. In areas with Marandu grass intercropping and monoculture, the herbicides nicosulfuron Nortox® (200 ml ha^-1), FACERO® SC (atrazine, 3L ha^-1) and pH reducer TA35 (50 ml ha^-1) were applied 15 days after sowing; at the second application, Proclaim ® (Emamectin Benzoate, 200 ml ha^-1), Nomolt (Teflubenzurom, 250 ml ha^-1), Perito (Acephate, 200 ml ha^-1)^, Priori (Azoxystrobin, 300 ml ha^-1), mineral oil (Iharol, 200 ml ha^-1) and pH reducer TA50 (50 ml ha^-1) were used. These applications were carried out to suppress dicotyledonous weeds and forage growth, so that there was no interspecific competition with maize.

Two experiments were conducted, both with a randomized block design in split-plots. In the first experiment, the treatments were composed of maize monoculture and maize intercropped with Marandu grass (plots), with evaluations carried out over eight collection times (subplots), at development stages V2, V6, V12, VT, R2, R3, R4, and R6 [¹²]. In the second experiment, the treatments consisted of Marandu grass monoculture and intercropped with maize (plots), with evaluations carried out over 12 collection times (subplots). The first eight collections were synchronized with the evaluations carried out in the maize crop while the other four collections were carried out after the harvest in the months of August, September, October and November. In both experiments, four replications were used.

After maize harvest (July), Marandu grass (intercropping and monoculture) was grazed by cattle (3.5 AU ha^-1) between the months of July and August. At the Barbosa Farm, there was a rotation of grazing paddocks, in each of which the animals remained grazing for twenty-eight days. Then, they were relocated to another paddock. After the animals left, there was regrowth of the forage grass, which was used as soil cover for direct sowing in the following year's soybean harvest.

The accumulation of degree days (°C) was calculated during the maize and Marandu grass cycles [¹³], based on maximum and minimum temperature data, recorded from the period of emergence until the collection of plant material. For maize, accumulated degree day was calculated between 0 and 105 DAE; for Marandu grass, the accumulation was calculated for the period between 0 and 278 DAE. The methodology considers the lower basal temperature (Tb) and the upper basal temperature (TB). The Tb and TB for maize were 10°C, and 35°C, respectively [¹⁴]. For Marandu grass, Tb was 10.3°C and TB was 30°C [¹⁵].

In the proposed methodology [¹³], the accumulated temperature has five conditions, so that of these conditions, equations 1 and 2 were adjusted to the climatic conditions of the experiment:

(1) $$\text{TB>TM>Tm>Tb DD}=\frac{\text{TM}-\text{Tm}}{2}+\text{TM - Tb}$$

(2) $$\text{TM>TB>Tm>Tb DD}=\frac{2\left(\text{TM}-\text{Tm}\right)+\left(\text{Tm}-\text{Tb}\right)+{\left(\text{TM}-\text{Tm}\right)}^2-\left(\text{TM}-\text{TB}\right)}{2\left(\text{TM}-\text{Tm}\right)}$$

Where: DD= degree days; TB= upper basal temperature (maize = 35°C, Marandu grass= 30°C); Tb= lower basal temperature (maize = 10°C, Marandu grass = 10.3°C); TM= maximum temperature; Tm = minimum temperature.

The biometric data measured in maize were: plant height (cm), stem diameter (mm), number of leaves, leaf area (cm²), measured with an area meter (Licor model LI-3100®), and leaf area index [¹⁶]. For Marandu grass, canopy height (cm), tiller population density, living leaves per tiller, number of tillers, leaf:stem ratio, leaf area (cm²), measured with an area meter (Licor model LI-3100®), and leaf area index (LAI) [¹⁶], which considers the relationship between the plant's total leaf area (m²) per unit of land (m²) available for the plant, using the equation: LAI = $\frac{LA}{S}$. Where: LA = Total leaf area (cm²); S= space available for the plant (space occupied/number of plants).

In the experiment with maize, grains were collected at the R6 stage to evaluate the following yield components: yield (kg ha^-1), ear weight (g), weight of a thousand grains (g), ear insertion height (m), and final plant height (m).

For the experiment with monoculture and intercropped Marandu grass, the data were evaluated in two different periods, one relating to the intercropping with maize (synchronized with maize experiment) and the other, in the post-intercrop period.

The data obtained were subjected to analysis of variance following a split-plot statistical scheme (cropping treatments considered as plots and evaluation times as subplots). When significant differences were found (P<0.05), the 't' test was used to compare treatments in the plots and regression analysis was used for the evaluation times (subplots) using the statistical software Sisvar ® version 5.8 [¹⁷]. Non-linear models were used, with model parameters estimated using the dynamic curve fitting function to select the model that expressed statistical significance (for the model parameters) and the highest coefficient of determination (R²) on the SigmaPlot ® program version 10.0 (Systat Software, San Jose, CA). The Gaussian and lognormal models used to generate the peak curves and the 3-parameter sigmoid model of the sigmoidal curve are described in equations 1 and 2, respectively:

(1) $$y=a{e}^{\left[-0.5{\left(\frac{x-xo}{b}\right)}^2\right]}$$

(2) $$y=a{e}^{\left[-0.5\left(\frac{\ln {\left(\frac{x}{xo}\right)}^2}{b}\right)\right]}$$

Where: y= growth or accumulation variable; a = maximum value of the variable (regardless of the model chosen); x0 = value of x in the DAE that provides the maximum value for the peak equations or inflection point of the curve in DAE for the sigmoidal equation; b = amplitude of the value of x in DAE between the inflection point and the maximum point for the peak equations or growth rate or accumulation (average) for the sigmoidal equation.

From the fitted model, it was possible to accurately determine the value of the inflection point (PI) in the curve, according to the equation: PI = x0 - b.

Mathematically, PI corresponds to the value of x, at which the curvature of the fitted model changes sign. In practice, this corresponds to the value of x in DAE, at which the maximum daily accumulation rate, although positive, decreases.

RESULTS AND DISCUSSION

Accumulated degree days

The accumulation of degree days until tasseling (VT) was 1490. At the end of the cycle (R6), the accumulation was 2665 (Table 2) at 105 DAE. The main factor that influences maize development cycle is temperature because the plant’s phenological stages are determined by the number of hours of daily heat expressed in accumulated degree days (ADD) [¹⁸]. Other studies have demonstrated total ADD lower than that observed in this study due to varying cultivation cycles. Under higher latitude conditions (20° 45' S) in Viçosa, Minas Gerais state [¹⁴], an ADD of 1600 was observed in maize over a 138-day cultivation cycle. Under similar latitude conditions (22° 41' S), an ADD of 1596 was observed in maize plants with a 139-day cultivation cycle in Piracicaba, São Paulo state [¹⁹]. For conditions at high latitudes in the Northern Hemisphere (41° 55 N), in Illinois, USA, an ADD of 1400 was observed at the R6 stage [²⁰], in maize plants with an average cycle of 120 days. These data demonstrate a tendency for ADD to decrease until the R6 stage with increasing latitude. Possibly, the greater proximity to the equator results in higher temperatures, favoring the faster ADD, even with a tendency to reduce the duration of the crop cycle.

Table 2
Accumulation of degree days during the development cycle of maize and Marandu grass in monoculture and intercropping cultivation and of Marandu grass in the post-intercropping period with maize. Brejo, Maranhão state, 2022.

DAE	Maize		Marandu grass
	Phenological stage	ADD	Period	ADD
0	VE	0	Planting	0
10	V2	432	Intercropping	559
24	V6	820	Intercropping	807
38	V12	1202	Intercropping	1031
50	VT	1490	Intercropping	1277
63	R2	1766	Intercropping	1541
77	R3	2061	Intercropping	1789
91	R4	2343	Intercropping	2067
105/106	R6	2665	Post- Intercropping	2329
159	-	-	Post- Intercropping	3273
192	-	-	Post- Intercropping	3859
221	-	-	Post- Intercropping	4402
278	-	-	Post- Intercropping	5500

For Marandu grass, both in monoculture and intercropping cultivation, ADD was 5500 from the beginning to the end of the cultivation cycle, from the months of February to November 2022 (Table 2). At the time of harvesting maize grains, ADD in Marandu grass was 2329. When the animals left the Marandu grass area, ADD was 3273.

In the present study, ADD for Marandu grass plants at 64 DAE was 1541. This value is higher than the 1400 ADD observed in another study carried out with 60-day-old Urochloa brizantha plants in Rio Claro, São Paulo state (22° 24' S) [²¹]. In Santa Maria, Rio Grande do Sul state (29° 43' S), an ADD of 1104 was observed in Urochloa, over a period of 46 days [²²]. This author also found that the accumulation of 180 GD is ideal for the emergence of new tillers in grasses of the Urochloa genus.

Similar to what was observed for maize, there is a downward trend in ADD as latitude increases. In Brazil, tropical forage grasses show slow growth in periods with low rainfall, typical of periods of drought and high temperatures in low latitude regions with bimodal precipitation. Very low or very high temperatures negatively affect the average growth rate in Urochloa brizantha [²¹]. The various pasture management techniques aim to explore the yield potential of these forages. However, it is essential to have favorable climatic conditions so that there is no suppression of plant growth [²³].

Biometric responses of maize monoculture and maize intercropping

There was no significant effect of the interaction between cultivation systems and collection times (DAE) for plant height, stem diameter, number of leaves, leaf area and leaf area index (Table 3). However, there was a significant effect (P <0.01) of the cultivation factor for stalk diameter, with a higher value for single maize (15.24 mm), compared to intercropped maize (14.51 mm). All attributes were significantly (P <0.01) influenced by collection times (DAE).

Table 3
Analysis of variance regarding biometric variables in maize plants in intercropped and single cultivation. Brejo, Maranhão state, 2022.

Cultivation (C)	PH (m)	SD (mm)	NL	LA (cm2 plant-1)	LAI
MI	1.70 a	14.51b	11.59 a	2100 a	3.36 a
MM	1.69 a	15.24 a	11.59 a	2104 a	3.37 a
F Test	ns	**	ns	ns	ns
DAE
10	0.22	6.13	5.40	167	0.27
24	0.86	16.43	6.93	2434	3.90
38	1.64	16.88	12.06	3908	6.25
50	2.12	15.36	14.59	3276	5.24
63	2.07	16.09	14.06	3468	5.55
77	2.12	16.06	14.06	1609	2.58
91	2.05	16.29	13.66	1448	2.32
105	2.07	15.46	11.97	507	0.81
F Test	**	**	**	**	**
C x DAE	ns	ns	ns	ns	ns
CV1 (%)	8.61	5.51	3.16	20.38	20.39
CV2 (%)	4.88	7.32	4.29	21.09	21.09

• PH - plant height, SD- stem diameter; NL - number of leaves, LA - leaf area, LAI - leaf area index, MI - maize intercropping, MM - maize monoculture, CV1 - coefficient of variation associated with the plot, CV2 - coefficient of variation associated with the subplot.
• ^**
  and ns: significant at 1% and not significant by the 't' test (p <0.05), respectively. Means followed by the same letter do not differ from each other based on the 't' test at 5% probability.

The curve models as a function of DAE have been fitted to all variables, with coefficients of determination (R²) above 0.87, explaining most of the variability. The fitting coefficients of the equation (a, b and x0) were significant at 1% probability for the variables plant height, leaf area and LAI. For the number of leaves, there was a significant effect at 1% for parameter a, and at 5% for parameters b and x0. For stem diameter, parameter a was significant at 1%, while parameters b and x0 were non-significant (Table 4).

Table 4
Estimation of model parameters for plant height, stem diameter, number of leaves, leaf area and leaf area index (LAI), inflection point (PI) and coefficient of determination (R2) in maize cultivated in monoculture and intercropping throughout the development cycle. Brejo, Maranhão state, 2022.

Variables	Model parameters (1)
	a (2)	b (3)	x 0(4) DAE		PI	R2	Function
Plant height (m)	2.10**	7.70**	26.98**		-	0.99	Sigmoid
Stem diameter (mm)	16.08**	0.60ns​	10.29 ns		-	0.98	Sigmoid
Number of leaves	13.80**	1.18*	69.51*		68.33	0.87	Normal log
Leaf area (cm2)	3.925**	0.53**	40.81**		40.28	0.94	Normal log
LAI	6.28**	0.53**	40.80**		40.27	0.94	Normal log

• ⁽¹⁾
  The values represent the average of the biometric evaluations of the cultivar;
• ⁽²⁾
  Maximum observed value;
• ⁽³⁾
  Average growth rate;
• ⁽⁴⁾
  Inflection point;
• ^**
  ,
• ^*
  and ns: significant at 1%, 5% and not significant by t-test (p <0.05), respectively.

Plant height of maize plants increased exponentially until VT (accumulation of 1400 degree days), with an estimated maximum value of 2.10 m, remaining constant until physiological maturity (Figure 2a). For the variables stem diameter and number of leaves, maximum values were estimated at 16.88 mm at 10 DAE (Figure 2b) and 13.80 at 69 DAE (Figure 2c), respectively.

Figure 2
Plant height (a), stem diameter (b), number of leaves (c) andleaf area (d) of maize cultivated in monoculture and intercropping as a function of accumulated degree day throughout the production cycle. Brejo, Maranhão state, 2022.

The maximum plant height found in this study was similar to that found in a study carried out in the state of Mato Grosso do Sul [²⁴]. The authors observed maximum values of 2.13 m and minimum values of 1.73 m in maize hybrids with YHR Pioneer® and Leptra ® technologies. In another study [²⁵], plant height values of 2.30 m at 110 DAS and stem diameter of 24.70 mm and 26.10 mm at 60 DAS were observed in Pioneer 30K73® maize hybrids grown in Paraguay. The authors also reinforce that stem is where most of the maize plants' starch reserves are accumulated, which will be mobilized to the grains at the reproductive stages. It is important to highlight that the reserve remobilization process occurs without changing stem diameter or plant height values, which demonstrate stability of the values once the maximum point is reached (Figure 2).

The maximum estimated leaf area in maize was 3925 cm² per plant, at 40.81 DAE (Figure 2d). Likewise, the maximum estimated LAI was 6.28 at 40.80 DAE (Figure 3). However, contrary to what was observed for stem diameter and plant height, after the maximum points, there was a decrease in leaf area and LAI because of the beginning of the leaf senescence process, when the forming grains become drains and the leaves are now used as a source of nutrients. In general, plants with more leaves and leaf area tend to have greater accumulation of dry matter due to the increase in photosynthetic area [¹⁹]. Under these conditions, there is an increase in the production of photoassimilates with a consequent increase in the total biomass of the plant and grains [²⁶]. These authors also emphasize that when entering the reproductive stage, maize plants do not show increases in growth, as the plant stops growing leaves and stems, and reproductive structures, and instead starts to mobilize photoassimilates from these organs to the grains. Maize plants show an exponential increase in LAI and leaf area during the vegetative period of the crop, linear and positive during tasseling (VT), followed by a linear and slightly negative variation until the beginning of leaf senescence, with a subsequent decrease until R6 [²⁷].

Figure 3
Leaf area index-LAI of maize cultivated in monoculture and intercropping as a function of accumulated degree day throughout the production cycle. Brejo, Maranhão state, 2022.

Maize yield and yield components

In relation to grain yield, plant height, ear insertion height, ear weight, and thousand-grain weight, there was no significant effect of neither intercropping nor monoculture cultivations (Figure 4). For intercropped maize, the yield was 5284 kg ha^-1 and for maize monoculture, the yield was 4785 kg ha^-1 (Figure 4a). For ear weight, an average value of 372 g was observed in maize+Marandu grass intercropping and 333 g in maize monoculture (Figure 4b). For the thousand-grain weight variable, the averages were 263 g in intercropped maize and 253 g in maize monoculture (Figure 4c). The ear insertion height was 1.14 m in intercropped maize and 1.07 m in maize monoculture (Figure 4d). The final height of plants in intercropped maize was 2.11 m, while in maize monoculture, it was 2.14 m (Figure 5).

Figure 4
Means for grain yield (a), ear weight (b), thousand-grain weight (c) andear insertion height (d) in maize monoculture and maize intercropped with Urochloa brizantha. Brejo, Maranhão state, 2022.

Figure 5
Plant height in maize monoculture and maize intercropped with Urochloa brizantha. Brejo, Maranhão state, 2022.

The absence of interference from intercropping in maize grain productivity has been observed in other studies. The productivity of second-crop maize in municipalities in Mato Grosso do Sul state was not significantly influenced by intercropping with cover crops [³]. The authors found maize productivity slightly lower than those observed in the present study, ranging from 2.2 to 4.4 t ha^-1. Other authors [²⁸] evaluated the intercropping of maize with several species of crotalaria and verified the competitive effect of maize with Crotalaria juncea, but absence of competition between maize + C. spectabilis, maize + C. ochroleura and maize + Crotalaria species mix. The definition of intercropping arrangements that do not impair maize yield is relevant because intercropping improves soil fertility and productive sustainability and can lead to increases in yield of subsequent crops [³, ²⁹, ²]. It should also be noted that the yield observed in the present study is similar to the national average (5248 kg ha^-1) of the 2021/2022 season [³⁰].

Biometric responses of Marandu grass monoculture and Marandu grass+maize intercropping

The canopy height and leaf:stem ratio were not influenced by the cultivation system. For the other variables, highest values were found in monoculture Marandu grass, compared to intercropped Marandu grass.There was also a significant effect of the interaction between cultivation systems and evaluation times for all attributes analyzed over the period from 11 to 106 DAE (Table 5).

Table 5
Analysis of variance of biometric characteristics associated with Marandu grass plants in monoculture cultivation and intercropped with maize. Brejo, Maranhão state, 2022.

Cultivation (C)	CH	TPD	LLT	NT	LA (cm2)	LAI	L:S
BI	36.63 a	3.29 b	4.01 b	6.45b	279b	0.69 b	1.61 a
BM	37.02 a	11.07 a	4.69 to	13.97 a	1336 a	3.37 a	1.23 a
F Test	ns	**	**	**	**	**	ns
DAE
11	13.75	2.28	3.22	1.60	114	0.29	1.84
25	12.40	2.72	4.94	6.55	136	0.34	1.7
37	10.75	5.65	3.32	11.30	337	0.85	2.33
50	27.65	8.12	3.77	10.02	368	0.92	1.98
64	52.60	7.70	4.65	16.07	441	1.10	0.96
78	51.36	9.57	4.77	10.10	769	2.03	0.97
92	67.90	10.70	5.15	11.85	2100	5.25	0.87
106	58.21	10.70	4.96	14.20	2195	5.48	0.72
F Test	**	**	**	**	**	**	**
C x DAE	**	**	**	**	**	**	ns
CV 1 (%)	17.92	34.87	9.43	27.38	39.03	39.81	68.16
CV 2 (%)	16.67	31.07	17.40	24.20	33.01	33.04	67.46

• IB -Marandu grass intercropping, BM - Marandu grass monoculture, CH - canopy height, TPD - tiller population density (tillers m²), LLT - living leaves per tiller, NT - number of tillers, LA - leaf area, LAI - leaf area index, FC - leaf:stem ratio, DAE - days after emergence, CV1 - coefficient of variation associated with the plot, CV2 - coefficient of variation associated with the subplot.
• ^**
  and ns: significant at 1% and not significant by “t” test (p <0.05), respectively. Means followed by the same letter do not differ from each other using the “t” test at 5% probability.

At 11 DAE, greater canopy height and a lower number of living leaves per tiller were observed in intercropped Marandu grass (Figure 6). This trend was reversed at 92 and 106 DAE, when Marandu grass monoculture began to present the highest canopy heights. In the intercropping, the maximum canopy height value (57 cm) was estimated at 81 DAE. In Marandu grass monoculture, the highest estimated height (75 cm) occurred at 102 DAE (Table 6).

Table 6
Estimation of model parameters adjusted for canopy height (AD), tiller population density (DPD), living leaves per tiller (LLT), number of tillers (NT), leaf area (LA) and leaf area index (LAI), inflection point (IP) and coefficient of determination (R2) for Marandu grass monoculture (BM) and in intercropping with maize (MI), throughout the development cycle. Brejo, Maranhão state, 2022.

Variables	Model parameters (1)
	a (2)	b (3)	x 0 (4) (DAE)	PI	R2	Function
ADBI	57**	33**	81**	48	0.84	Gaussian
AD BM	75**	33**	102**	69	0.97	Gaussian
DPD BI	4.8**	43**	89**	46	0.86	Gaussian
DPD BM	16**	46**	96**	50	0.96	Gaussian
LLT BI	4.9**	50**	79**	29	0.73	Gaussian
LLT BM	5.3**	74ns	95 ns	21	0.46	Gaussian
NT BI	9.0**	36*	69**	30	0.62	Gaussian
NT BM	19**	46*	86**	40	0.79	Gaussian
LABI	1049ns	11ns	109**	98	0.77	Gaussian
LA BM	4340**	12**	97**	85	0.94	Gaussian
LAI BI	2.6ns​	11ns	109*	98	0.77	Gaussian
LAI BM	10**	13**	97**	84	0.94	Gaussian
L:S BI	2.5**	26**	40**	14	0.50	Gaussian
L:S BM	1.6**	35**	42**	7	0.48	Gaussian

• ⁽¹⁾
  The values represent the average of the biometric evaluations of the cultivar;
• ⁽²⁾
  Maximum observed value;
• ⁽³⁾
  Average growth rate;
• ⁽⁴⁾
  Amplitude in the value of x in DAE between the inflection point and the maximum point.
• ^**
  ,
• ^*
  and ns: significant at 1%, 5% and not significant by the “t” test (p <0.05), respectively. BC - intercropped Marandu grass, BM - Marandu grass monoculture, DAE - days after emergence.

Figure 6
Canopy height (a), tiller population density (b), living leaves per tiller (c) and number of tillers (d) in single Marandu grass plants and in intercrop with maize, due to the accumulation of degree days throughout the production cycle. Brejo, Maranhão state, 2022. (* significant at 5% probability, using the “t” test).

Marandu grass monoculture showed a higher tiller population density in all assessments from 25 DAE onwards. The quantity of green leaves per tiller was higher in Marandu grass monoculture at 11 and 92 DAE. At 37 DAE (1031 ADD), a greater number of tillers and leaf area were observed in Marandu grass monoculture. Monoculture cultivation also showed greater leaf area and LAI at 78, 92 and 106 DAE (Figure 6). In turn, the leaf:stem ratio was higher in Marandu grass intercropping at 37 and 50 DAE.

The structure of a pasture is determined by its morphology, architecture, spatial distribution of leaves, leaf:stem ratio, living:dead leaves ratio, green leaf density, tiller population density, and canopy height. The composition of this structure directly affects the production and quality of forage and, consequently, its consumption by animals [³¹].

Studies with grasses demonstrate that there is a relationship between light interception and forage canopy height, regardless of the time of year and the physiological stage of the plants, indicating that height can be used as a criterion for decision-making in pasture management [³²]. For example, evaluating reference conditions for the use of Urochloa brizantha cv. Marandu under a rotational system, a study [³³] established a pre-grazing height of 25 cm for plants subjected to 95% light intensity while a15 cm height for the rainy season and 10 cm for the dry season, respectively, in post-grazing. However, height varies across species and cultivars of the same species and is greatly influenced by climatic factors (photoperiod, temperature, light), water and nutrient availability in soil, in addition to the genotype [³⁴]. For the conditions of the present study, the data show that the cultivation condition (monoculture or intercropping) is a preponderant factor in defining the architecture and composition of grass fractions, possibly because of the difference in light availability since all other factors were also made available to plants.

The maximum values of living leaves per tiller (4.9) were observed in Marandu grass intercropping at 79 DAE, and in Marandu grass monoculture (5.4) at 95 DAE (Table 6). The number of living leaves per tiller is defined by the species [³⁵]. However, data from this study demonstrate that competition for resources such as light tends to reduce the total number of living leaves per tiller, although this condition apparently results in an earlier peak in the number of leaves. This anticipation of the peak of leaf production in intercropped Marandu grass plants may be the result of an ecophysiological adaptation of the plant, which starts directing photoassimilates primarily towards the formation of leaf blades, as a way of optimizing light interception in conditions of low availability of light.

The maximum estimated number of tillers occurred at 69 DAE in Marandu grass intercropping (9) and at 86 DAE in Marandu grass monoculture (19), (Table 6). Tiller production and tillering duration vary between species and cultivars and can be influenced by nutritional, environmental, and management factors. Thus, the number of tillers is related to the production of new tillers, which is a continuous process and can be accelerated by the defoliation of the plant and an increase in light incidence at the base of the canopy. Therefore, the maintenance of the number of tillers occurs through a continuous emergence of living tillers to replace dead ones.This is one of the characteristics that allow for the maintenance and continuous growth/regrowth in forage grasses [³⁶].

Regarding the leaf:stem ratio, the maximum values were estimated in Marandu grass in intercropping cultivation (2.5) at 40 DAE, and in single Marandu grass (1.6), at 42 DAE (Table 6). The higher leaf:stem ratio in the intercropped Marandu grass suggests that in this system the plants primarily directed photoassimilates to the production of leaf blades to the detriment of stems to adapt to the low-light environment and to optimize the interception of diffuse light that can penetrate the maize canopy. However, the leaf:stem ratio affects the architecture of plants in pastures and the quality of forage for animal consumption [³¹]. Studies of the leaf:stem ratio in forage grasses are important because leaves are the organ preferentially consumed by animals and the main source of nutrients for ruminants in a grazing system [³⁷].

The highest leaf area values were estimated for Marandu grass intercropping (1049 cm² plant^-1) at 109 DAE, and for Marandu grass monoculture (4340 cm² plant^-1) at 97 DAE (Table 6; Figure 7). For LAI, the maximum values were observed in Marandu grass intercropping (2.6) at 109 DAE and at 97 DAE (10) in Marandu grass monoculture (Table 6). In studies with tropical grasses, it is reported that leaf area and LAI are the ideal parameters for evaluating and defining the moment of cutting or grazing, thus interrupting canopy growth and obtaining maximum accumulation of forage with maximum leaf production [³⁴]. The leaves of forage grasses are the main source of interest in agriculture. The data from this study demonstrate that although in intercropping systems, Marandu grass gives preference for the allocation of photoassimilates in the leaves to the detriment of other vegetative structures such as culms. In monoculture cultivation, Marandu grass produces substantially more leaf area, which makes this cultivation system most suitable when seeking exclusively to produce forage. However, other factors must be taken into consideration when the objective goes beyond forage production and includes the production of maize grains concomitantly with forage production, or the production of vegetation cover that allows the adoption of more conservationist and sustainable practices of soil management throughout successive cropping cycles [²].

Figure 7
Leaf area (a), leaf area index (LAI) (b) and leaf:stalk ratio (c) in single Marandu grass plants and in intercrop with maize, due to the accumulation of degree days throughout the production cycle. Brejo, Maranhão state, 2022. (* significant at 5% probability, using the “t” test).

Biometric responses in Marandu grass monoculture and intercropping in a cultivation subsequent to the maize harvest

There was no significant effect of the Marandu grass cultivation system in the post-maize harvest period for the number of living leaves per tiller (Table 7). However, for leaf area, leaf area index and leaf:stem ratio, a difference was observed between the cultivation systems in the period after maize harvest, between 106 and 278 DAE. For all variables, a significant effect of the interaction between cultivation systems and evaluation times was also observed.

Table 7
Analysis of variance of biometric variables related to Marandu grass in the period after intercropping with maize. Brejo, Maranhão state, 2022.

Cultivation (C)	LLT	LA (cm2)	LAI	L:S
BI	3.84a	352b	0.88b	2.21a
BM	4.38a	1064a	2.66a	0.83b
F Test	ns	**	**	**
DAE
106	4.96	2195	5.48	0.72
159	2.96	98	0.24	0.42
192	4.40	260	0.65	1.76
221	4.50	443	1.10	0.95
278	3.35	304	0.76	3.65
F Test	**	**	**	**
C x DAE	**	**	**	**
CV1 (%)	28.59	66.76	66.73	33.28
CV2 (%)	13.05	37.61	37.61	49.31

• BI - Marandu grass intercropping, BM - Marandu grass monoculture, LLT - living leaves per tiller, LA - leaf area, LAI - leaf area index, DAE - days after emergence, CV₁ - coefficient of variation associated with the plot, CV₂ - coefficient of variation associated with the subplot.
• ^**
  and ns: significant at 1% and not significant by t test (p <0.05), respectively. Means followed by the same letter do not differ from each other using the “t” test at 5% probability.

The high variation coefficient for the attributes after maize harvest is justified by the relationships between production, leaf nutrient content parameters and environmental factors, such as the relative air humidity, temperature, soil pH, OM content and the soil available P, K and Ca [³⁶]. In addition, grazing intensity impacts the spatial heterogeneity and productivity in integrated crop-livestock systems [³⁷].

In the post-intercropping period, Marandu grass in monoculture showed a greater quantity of living leaves per tiller than Marandu grass in intercropping at 106 and 221 DAE (2329 and 4402 ADD, respectively), greater leaf area and leaf area index than Marandu grass in intercropping at 106 DAE (2329 ADD) and a higher leaf:stem ratio than the Marandu grass in intercropping at 198 and 278 DAE (3859 and 5550 ADD, respectively) (Figure 8).

Figure 8
Living leaves per tiller (a), leaf area (b), leaf area index (LAI) (c) and leaf:stem ratio (d) in Marandu grass monoculture and intercropping systems in the maize post-harvest period due to the accumulation of degree days throughout the production cycle. Brejo, Maranhão state, 2022. (* significant at 5% probability by “t” test).

In intercropped Marandu grass, the maximum estimated LLT value was 1.5 leaves at 107 DAE, while in Marandu grass monoculture, it was 4.7 leaves at 105 DAE (Table 8). The productivity of a forage grass depends on the continuous emission of leaves and tillers, which is an important process in the restoration of leaf area under mowing or grazing conditions, in conjunction with the physiological age at which the plants are harvested [³⁸]. In the present study, after the grazing phase, the plants continued to produce new leaves and tillers. However, this process was slowed down by the fact that the plants were in a dry period.

Table 8
Estimation of model parameters adjusted for living leaves per tiller (LLP), leaf area (LA), leaf area index (LAI), leaf:stem ratio (L:S), inflection point (IP) and coefficient of determination (R2) in Marandu grass, throughout the development cycle. Brejo, Maranhão, 2022.

Variables	Model parameters (1)
	a(2)	b (3)	x0 (4) (DAE)	y0 (5)	R2	Function
LLPBI	1.5ns​	-0.8ns​	107ns	3.3*	0.51	Sigmoidal
LLP BM	4.7ns​	-0.9ns​	105ns	4.0*	0.28	Sigmoidal
LA BI	915ns	-2.1ns​	121**	189ns	0.96	Sigmoidal
LA BM	3017ns	-1.5ns​	122**	367ns	0.98	Sigmoidal
LAI BI	2.0ns​	-1.94ns​	122ns	0.4ns​	0.96	Sigmoidal
LAI BM	7.5ns​	-1.4ns​	122ns	0.9ns​	0.98	Sigmoidal
L:S BI	4.5**	162 ns	148ns	4.6**	0.81	Gaussian
L:S BM	-3.8ns​	135 ns	163ns	4.2ns​	0.94	Gaussian

• ⁽¹⁾
  Values represent the average of the biometric evaluations of the cultivar;
• ⁽²⁾
  Maximum observed value;
• ⁽³⁾
  Average growth rate;
• ⁽⁴⁾
  Inflection point;
• ⁽⁵⁾
  Amplitude in the value of x in DAE between the inflection point and the maximum point.
• ^**
  ,
• ^*
  and ns: significant at 1%, 5% and not significant by t-test (p <0.05), respectively. BI - Marandu grass intercropping, BM - Marandu grass monoculture, DAE - days after emergence.

It is also noted that at 121 DAE, the Marandu grass plants from the intercropping system had a significantly smaller leaf area (915 cm² plant^-1) than the Marandu grass plants from the monoculture cropping system (3017 cm² plant^-1). Similarly, LAI was 2.0 in intercropped plants and 7.5 in monoculture crop plants at 122 DAE. However, this difference between the systems was diluted over time, possibly due to the grazing practice applied to the areas. Some authors observed that LAI increases according to the light interception level of the canopy, photosynthetic efficiency, and growth of forage plants, which justifies the higher values reported in Marandu grass monoculture [³⁴]. The light restriction imposed by maize on Marandu grass in the intercropping system limited the emission of new leaves and the composition of LAI since light restriction values greater than 50% can substantially reduce pasture production [³⁹,⁴⁰].

The maximum estimated leaf:stem ratio in Marandu grass intercropping was 4.5 at 148 DAE and 3.8 in Marandu grass monoculture at 163 DAE (Table 8). The environmental conditions influence the plants’ growth and nutritional value, the latter of which is closely related to consumption and use by animals. Thus, studies of the dynamics of leaf and tiller growth, nutritional value and growth analysis of perennial forage grasses are important for defining forage plant management strategies under different environmental conditions [⁴¹].

Much of the current research on grasses has been dedicated to studying the structural characteristics of the pasture based on variables such as leaf size, tiller density and number of leaves per tiller, with the tiller being considered the basic unit of development in forage plants [²³]. Tillering is important for biomass production and an essential characteristic for pasture productivity [44]. The higher leaf:stem ratio of Marandu grass intercropping compared to Marandu grass monoculture, estimated even weeks after maize harvest, indicates that the process of prioritizing the partition of assimilates to the leaves to the detriment of the stems caused by shading in the intercrop is a non-reversible process in the short term. This is a remaining effect of the intercropping phase even when lighting conditions are reestablished. Therefore, even after maize harvesting, Marandu grass is unable to fully recover its vegetative structure, due to the limited development of leaves and tillers imposed during the intercropping period.

The results highlighted that the Marandu grass exhibits lower values of biometric components in intercropping systems compared to monoculture and that eventual benefits from residual fertilization from maize did not overcome the limitations with luminosity stress imposed by the cereal crop in the beginning of the season.

Despite this, a higher leaf:stem ratio gives the grass better adaptation to grazing or tolerance to cutting, as it shows a phenological moment in which the apical meristems are closer to the soil and, therefore, are less vulnerable to destruction by animal grazing or cutting by machine [⁴³]. Under the edaphoclimatic conditions where the study was conducted, the post-intercropping phase was restricted to the dry season. Under these conditions, it was not possible to evaluate the regenerative potential of Marandu grass from either the intercropping or the monoculture systems after removing the grazing animals because in the following rain cycle, the area was desiccated and used for grain production. Therefore, further research is necessary to access the regeneration capacity of Marandu grass plants from monoculture and intercropping systems, grazed and subjected to a new growth cycle in the rainy season. Additional research is also necessary to evaluate animal performance during the grazing in monoculture and intercropping forage. Such analysis is relevant especially considering the lower forage parameters in intercropping system compared to monoculture, which implies that the available area for the grazing under these conditions must be larger, with implications for the subsequent area available for cash grain crops.

CONCLUSION

Intercropping with Marandu grass does not negatively affect the biometric variables and yield of maize plants. Conversely, intercropping with maize negatively affects the growth of Marandu grass plants, reducing tiller population density, leaf area, and leaf area index. The higher leaf:stem ratio in Marandu grass intercropping is a result of the preferential allocation of photoassimilates to the formation of leaves to the detriment of stems, thereby optimizing the interception of diffuse light. However, this condition is not reversed in the short term with the reestablishment of light conditions after maize harvest. Despite that, the intercropping of maize with Marandu is a promising alternative for maize and forage production during the off-season period in the Cerrado of Matopiba.

• Funding:
  This research was funded by Fapema (Fundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do Maranhão), code: BM-02196/21, and CNPq (National Council for Scientificand Technological Development), code: 431305/2018-8.
• Institutional Review Board Statement: “Not applicable” for studies not involving humans or animals.
• Informed Consent Statement: “Not applicable.” for studies not involving humans.

Use of Generative Artificial Intelligence

The authors declare that no generative artificial intelligence (AI) or AI-assisted technologies were used to generate or modify the scientific content of this manuscript, including the conception of the study, data collection, data analysis, interpretation of results, or creation of original text, figures, tables or graphical abstracts, apart from routine tools for spelling, grammar checking and reference management that do not create original scholarly content.

Acknowledgments:

To FAPEMA, to CNPq, to CAPES, to Embrapa Mid-North and to Universidade Federal do Piauí.

Data Availability Statement:

The data will be provided upon request.

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• Editor-in-Chief:
  Bill Jorge Costa

• Associate Editor:
  Bill Jorge Costa

Publication Dates

• Publication in this collection
  17 Aug 2026
• Date of issue
  2026

History

• Received
  21 May 2025
• Accepted
  24 Sept 2025