Influence of Crop Residue Management on Maize Production Potential

Abstract

Residue management at the farm level is essential for ensuring sustainable agricultural productivity. This field experiment, initiated in 2005, provides maize data from 2016 to 2018. This study evaluates the impact of crop residue management and fertilization on maize yield and yield components. Maize was grown in a crop rotation sequence consisting of field pea (Pisum sativum L.), durum wheat (Triticum durum Desf.), milk thistle (Silybum marianum (L.) Gaertn.), and maize (Zea mays L.). The measures studied include aboveground biomass removal (K), aboveground biomass incorporation (R), mineral fertilizer application (F), and their combination (RF). The results indicate that R and RF significantly improve yield parameters, such as kernel number per ear (KNE), thousand seed weight (TSW), stalk yield, and harvest index (HI), compared to control (K) or aboveground biomass incorporation alone (R). Grain yield varied across the years, with significant increases being observed for the fertilizer treatments, particularly when combined with straw or stalk incorporation. A nominal increase in grain yield of 1.43 t ha⁻¹ for the F treatment and 1.86 t ha⁻¹ for the RF treatment represents an increase of 39% to 51% compared to K and R. Strong positive correlations were observed between grain yield and several factors, including ears per hectare (0.61), KNE (0.94), TSW (0.61), and HI (0.85). These findings underscore the role of crop residue management and promoting sustainable crop production.

1. Introduction

Adaptive measures for climate change can be categorized into national-level measures to support large-scale adaptation initiatives and regional-level measures through the implementation of region-specific programs and farm-level adaptations [1,2]. Farmers, through the daily cultivation of millions of hectares of arable land, can significantly contribute to climate change adaptation by employing appropriate agricultural interventions that do not disrupt their conventional farming practices. By adopting climate-resilient crops, and implementing soil conservation strategies, farmers can enhance the resilience of their farming systems [3]. These measures promote sustainable agricultural productivity, ensuring long-term food security and environmental health [4,5]. The crop yield with adaptation measures was increased compared to the crop yield without adaptation measures. Maximum temperature, precipitation, and study area along with geographical coordinates also had significant effects on changes in crop yield [6,7,8]. Farmers facing a significant change in climate conditions may autonomously adapt through the adoption of new practices [9]. Farm-level adaptations include the adoption of sustainable farming practices, the diversification of crops, and the use of climate-resilient technologies tailored to the specific conditions of local environments. Identifying the particular management conservation practices that can mitigate yield losses in each crop and region is therefore a research priority. Adaptation includes any simulated change in the timing or amount of fertilizer application, soil organic matter management, i.e., compost application, crop residue retention, and crop rotation [10,11,12,13,14]. Increasing crop production and soil carbon sequestration is critical for sustainable agricultural development. Straw returning, a common farming practice, positively affects grain yield and soil organic carbon [15,16]. Nevertheless, straw’s slow decomposition rate and high carbon–nitrogen ratio are significant obstacles to its effectiveness [17]. In in situ management options, crop residues are either mixed with soil or retained on the soil surface [18]. As a promising approach for achieving sustainable agriculture, partial organic substitution for synthetic fertilizer can affect the stoichiometric balance between organic C and inorganic N, thereby regulating nitrous oxide (N₂O) fluxes [19]. The amount of N fertilizer input required for maize production could be reduced by using tillage with continuous straw incorporation [20]. Agricultural practices that aim to increase soil organic carbon stocks and positively influence maize yield components include cover crops and residue management [21,22,23].

Yield is composed of physical components that directly correlate to the amount of grain produced by the crop. Yield components are interrelated, have compensatory effects, and develop sequentially at different stages. The first-order yield components of maize consist of the number of ears per square meter (or number of ears per plant), the number of kernels per ear, kernel weight, and kernel weight per ear [24,25]. This study aimed to evaluate the impact of different crop harvest residue management practices on key production parameters of maize.

2. Materials and Methods

2.1. Experimental Trials and Treatments

The field trials were conducted in the experimental plots of the Slovak University of Agriculture in Nitra (SUA), situated within the experimental site of Dolná Malanta, located in southwestern Slovakia (48°19′ N and 18°09′ E). The experimental areas belong to the maize production region, located in a very warm and dry sub-area at 173 m above sea level. According to the standard climatological normal 1991–2020, there is an average total annual precipitation of 550.2 mm and an average annual air temperature of 10.6 °C. The soil type was classified as Haplic Luvisol [26], with a bulk density of 1.5 g cm⁻³–1.68 g cm⁻³. The particle-size distribution was 360.4 g kg⁻¹ of sand, 488.3 g kg⁻¹ of silt, and 151.3 g kg⁻¹ of clay.

The field experiment was originally established in 2005 and was maintained continuously until 2020, with no alterations made to the experimental factors. In this paper, we present data specifically for maize from the 2016–2018 growing seasons, within a four-year crop rotation system. The crop rotation sequence included milk thistle, maize, field pea, and durum wheat. White mustard (Sinapis alba L.) was the catch crop grown in the intercrop periods between the milk thistle and maize and wheat and milk thistle crop sequences. The above-ground biomass of the catch crops was used as green manure mulch, with the crops being chopped before flowering, left on the surface for 3–4 weeks, and then incorporated into the soil. Standard agronomic practices were applied to all experimental plots. Stalk incorporation was carried out using standard tillage practices to incorporate residues into the topsoil.

Adaptation measures for aboveground biomass management combined with mineral fertilization were used. To estimate the influence of different utilizations of aboveground biomass of growing crops on grain yield and yield components of maize, the following treatments were used: K control treatment—stalk removal; R—conventional stalk incorporation; F—application of NPK mineral fertilizers only; RF—treatments interaction of stalk incorporation and NPK mineral fertilizers application. Before being incorporated into the soil, the maize stalks were mechanically crushed. Mineral fertilizers with doses of pure nutrients of phosphorus 48 kg P and potassium 200 kg K were applied each year, directly before plowing in the final third of November. Nitrogen was applied in two splits: 75 kg N before sowing and 75 kg N at the V8—10 leaf stage of the maize stand in the form of Calcium Ammonium Nitrate containing 27% N, with 50% in ammonium form and 50% in nitrate form. Phosphorus was applied as single superphosphate (18–20% P₂O₅), and potassium as 60% K₂O.

The treatments were arranged in a randomized complete block design with a factorial arrangement of treatments using four replications. Each treatment was applied to sub-plots that were 10 m long in 8 rows with a 70 cm inter-row spacing and 1 m buffer zones between plots to prevent cross-contamination. To eliminate the edge effect, the border rows were excluded from the evaluation. The sowing rate was 75 thousand germinated seeds per hectare. The sowing depth ranged from 5 to 6 cm. The preceding crop was the milk thistle. The catch crop, white mustard, was seeded at a rate of 16 kg per hectare. The grain variety LG 30.315, FAO 300, Sc (two-line hybrid) was used. Management data for the field experiment, in order of sowing date and harvest date, are organized as follows: 11 May 2016–27 October 2016; 10 April 2017–20 October 2017; 13 April 2018–11 October 2018.

2.2. Meteorological Data

The 2016–2018 growing seasons experienced different temperature and humidity conditions, which were reflected in the maize yield and yield components.

The years 2016 and 2017 were thermally normal according to the average annual temperatures and 2018 was classified as warm at 0.7 °C above normal (Figure 1). Still, growing problems emerged due to the lower doses of precipitation during the vegetation period of maize. The years 2017–2018 were classified as being severely below normal [27], and very dry weather conditions were noted with a deficit of precipitation in the range of 128 mm and 185 mm, respectively. The precipitation conditions in 2016 were classified as normal, with extra doses of 45.2 mm compared to the normal value, but May and July were extraordinarily wet (Figure 2). During the maize growing season, moisture conditions were affected by rainfall deficits in May 2017 (very dry, 14 mm less) and May 2018 (dry, 28.6 mm less). June 2016 was also very dry (14.4 mm less), June 2017 was dry (26.1 mm), and only June 2018 had normal moisture levels of 44.4 mm of rainfall.

2.3. Maize Yield Components Observed

In all replications, samples relating to grain yield and yield components (mechanical analysis) were collected from 10 plants growing continuously in one representative row inside each subplot (a total of 40 plants). Yield components observed included ears per hectare, kernel number per ear (KNE), which was counted as the average number of grains in all ears from 10 plants, and thousand seed weight (TSW) at 14% moisture. Stalks yield at 15% moisture was calculated from a 100 g sample of dry corn stalks collected for moisture analysis by weighing before and after drying at 105 °C for 12–24 h until constant dry matter was achieved. The harvested dry matter was converted to a moisture content of 15%. The dry matter yield at harvest in t ha⁻¹ for grain was calculated using the formula TSW×G/1000. Here, TSW at harvest humidity, and G is the number of grains per hectare in millions, subsequently adjusted to a 14% grain moisture content. The harvest index (HI) was calculated as total biological yield/grain yield × 100.

2.4. Statistical Analysis

An analysis of variance (ANOVA) was employed to evaluate the effects of fertilization treatments, including biomass and industrial fertilizers, under varying weather conditions across the assessed years on maize grain yield and its yield components using STATISTICA software version 13 (StatSoft Inc., Tulsa, OK, USA). The Shapiro–Wilk test was used for the normality test of the data, and the results were normal. Post hoc comparisons were conducted using Fisher’s least significant difference (LSD) test at the 0.05 significance level. The relationship between the two variables was determined by the Pearson correlation coefficient of the three continuous years.

3. Results

3.1. Analysis of Variance for Grain Yield and Yield Components

The ANOVA results in

Table 1. Analysis of variance (ANOVA) for yield and yield component traits of maize for the years 2016–2018 at Slovak University of Agriculture in Nitra, Slovakia.

Effect	SS	DF	MS	F-Value	p-Value
Grain yield
Treatment	32.907	3	10.969	37.189	0.00000
Year	15.514	2	7.757	26.299	0.00000
Stalk yield
Treatment	24.850	3	8.283	5.377	0.00805
Year	24.908	2	12.454	8.085	0.00312
Ears per hectare
Treatment	1.642	3	5.471	1.663	0.21046
Year	4.556	2	2.278	6.924	0.00588
Kernel number per ear
Treatment	60627	3	20.209	25.851	0.00000
Year	22493	2	11.246	14.386	0.00019
Thousand Seed Weight
Treatment	5708	3	1.903	17.05	0.00002
Year	402	2	201	1.80	0.19389
Harvest Index
Treatment	299.01	3	99.67	11.975	0.00015
Year	99.81	2	49.90	5.996	0.01011

Note: SS: sum of squares, DF: degree of freedom, MS: mean square.

revealed significant effects of the treatments on grain yield, stalk yield, kernel number per ear, thousand seed weight, and harvest index, but not on ears per hectare, demonstrating that the evaluated treatments considerably impacted these parameters. Additionally, yearly variation significantly affects most of these parameters, particularly grain yield, stalk yield, ears per hectare, kernel number per ear, and harvest index except thousand seed weight. These results underscore the importance of treatment and yearly environmental factors in maize production.

The interaction effects of year and treatments on yield and the yield components of maize evaluated were non-significant, so they are not included in the table.

3.2. Yield Components and Grain Yield

The number of ears per hectare ranged from the control treatment K at 67,259 to the RF treatment at 71,839, with a mean density of 68,658 ± 6824 ears per hectare. The treatments had no significant (p = 0.21046) influence on the number of ears per hectare with a low F-value (1.663), indicating minimal treatment differences (Table 1). The effect of year was significant (p = 0.00588), suggesting yearly variation is a contributing factor that influenced the number of maize ears. In the agroclimatic conditions of the crop growing seasons of 2016–2017, we achieved an almost identical number of ears per hectare within the range of 66,010 to 66,985. In 2018, a significantly higher number of ears per hectare was recorded, reaching 72,978 ears per hectare.

The treatment and year effects significantly influenced kernel number per ear (KNE). Across treatments and years, the KNE averaged 303 ± 50 kernels per ear. The lowest kernel numbers were observed in the maize ears grown under all control treatments (K), ranging from 242.9 to 280.6. Due to the yearly conditions, significantly different values for the KNE were achieved across the three years, with 276 grains in 2016, 305 grains in 2017, and 329 grains in 2018. All of the treatment effects were highly significant (p = 0.00000) with high F-values (25.851), indicating strong differences between the treatments (Table 1). Figure 3 presents a line graph with error bars, illustrating the impact of treatments on KNE.

The fertilization treatments (F) and the interaction of fertilization and the incorporation of aboveground biomass (RF) had a significantly positive effect on the increase in KNE compared to the control treatment (K) and the treatment with the incorporation of aboveground biomass alone (R) (Table 1, Figure 3). According to the KNE values achieved, there are two distinguished ranges: 262–273 grains for treatments K and R, and a significantly higher level for fertilized treatments F and RF with 333–343 grains per ear. An increase in KNE of 60–71 kernels was achieved in the industrial fertilizer treatments (F), representing 22% to 27%. The increase in the RF treatment compared to the K or R treatment was between 70 and 81 grains, representing an increase of 25% and 31%. Treatments with the application of industrial fertilizers (F) and those with incorporation of above-ground biomass combined with industrial fertilizers (RF) achieved a significantly higher KNE over all three years of evaluation, regardless of the climatic conditions of the evaluated year.

The thousand seed weight (TSW) of maize was 211.2 ± 17 g on average. The impact of year conditions on TSW variability was not significant (p = 0.193795) and TSW ranged from 207 g in 2016 to 214 g in 2018 within a narrow interval. The control (K—202.8 g) and stalk incorporation (R—198 g) treatments show significantly lower TSWs compared to mineral fertilization (F—221.9 g) and the interaction treatment (RF—220.0). The TSW was significantly increased by more than 10% in the F and RF with almost identical TSW values compared to the stalk incorporation (R) or the control (K) treatments.

The treatments, including fertilizers and aboveground biomass incorporation, significantly influenced maize grain yield and achieved higher F-values (37.189), indicating strong differences between the treatments (Table 1). The influence of yearly conditions was also significant with a high F-value (26.299). When averaged across treatments, it can be seen that the maize grain yields differed significantly among the years, with yields of 3.79 t ha⁻¹, 4.40 t ha⁻¹, and 5.18 t ha⁻¹ in 2016, 2017, and 2018, respectively. The average grain yield (GY) was 4.46 t ha⁻¹, with a high standard deviation of 1.18 t ha⁻¹.

The grain yield in the control treatment (K) and the treatment with conventional stalk incorporation (R) was found to be almost identical when averaged over three years, with an average yield ranging from 3.60 to 3.69 t ha⁻¹ (Figure 4).

The grain yield under the F and RF treatments was significantly higher and formed a homogeneous group with an average yield of 5.06 t ha⁻¹ (F) and 5.49 t ha⁻¹ (RF), which represents a net increase in grain yield of 1.43 t ha⁻¹ for the mineral fertilizer treatments (F) and 1.86 t ha⁻¹ for the fertilized treatments interacting with the incorporation of biomass from the preceding crop (RF) compared to the K and R treatments. This represents an increase in grain yield ranging from 39% to 51%.

The total average stalk yield was 11.05 ± 1.52 t ha⁻¹, with the annual average ranging from 10.04 t ha⁻¹ in 2016 to 11.7 t ha⁻¹ in 2018. It predicts a lower variability in the given trait in response to environmental conditions than maize grain yield. During the three-year field trial, the lowest significant stalk yield was recorded in 2016 for the control treatment (K), with a yield of 8.97 t ha⁻¹, and the highest stalk yield was observed in 2018 for the RF treatment with 13.15 t ha⁻¹. The F and RF treatments yielded significantly more than the R and K treatments, with stalk yields ranging from 11.73 to 11.81 t ha⁻¹ compared to 10.26 to 10.40 t ha⁻¹, respectively (Figure 5).

The harvest index (HI) across the evaluated years was 28.43 ± 4.28. In 2018, the HI was significantly higher at 30.47 compared to the range of 27.25–27.59 observed in 2016–2017.

A significantly better proportion of economic yield (grain) to total biological yield (Figure 6) was found for the fertilizer treatments F (29.9) and RF (31.75) in comparison to the K (25.66) and R (26.42) treatments.

3.3. Correlations Among Measured Traits

The relationship between yield and maize yield components is presented in

Table 2. Pearson correlation coefficients (r) for the relationship between yield and yield component. N = 48; data from field trials between 2016 and 2018 at Slovak University of Agriculture in Nitra, Slovakia.

Parameters	Means	GY	E	KNE	TSW	HI
Stalk yield	11.05 ± 1.52	0.62 *	0.51 *	0.57 *	0.24 ns	0.13 ns
Grain yield (GY)	4.46 ± 1.18		0.61 *	0.94 *	0.61 *	0.85 *
Ears per ha (E)	68658 ± 6824			0.41 *	−0.01 ns	0.42 *
Kernel number per ear (KNE)	303.03 ± 50.16				0.52 *	0.80 *
TSW (thousand seed weight)	211.16 ± 17.07					0.66 *
Harvest index (HI)	28.43 ± 4.28

ns: non-significant, *: significant at p < 0.01.

. The variables include stalk yield, grain yield, ears per hectare, kernel number per ear, TSW, and harvest index. The Pearson correlation coefficients indicated several significant positive relationships among the evaluated traits. Grain yield (GY) has confirmed positive correlations with E (r = 0.61), KNE (r = 0.94), TSW (r = 0.61), HI (r = 0.85), and stalk yield (0.62). Ears per hectare (E) showed significant positive correlations with KNE (r = 0.41), HI (r = 0.42), stalk yield (0.51), and GY (0.61). No relationship between ears per hectare and TSW was confirmed. KNE had significant positive correlations with TSW (r = 0.52), HI (r = 0.80), stalk yields (0.57), GY (0.94), and E (0.41). TSW showed a significant positive correlation with grain yield (r = 0.61), KNE (0.52), and HI (r = 0.66). No relationship between TSW and ears per hectare or stalk yield was confirmed. Stalk yield was revealed to have significant positive correlations with grain yield (r = 0.62), ears per hectare (r = 0.51), and KNE (r = 0.57). The relationship between stalk yield and TSW or stalk yield and HI was non-significant. HI has a positive correlation with ears per hectare (0.42), TSW (0.66), and there was a generally strong relationship between grain yield (0.85) and KNE (0.80).

A higher correlation coefficient was determined between GY and KNE. Figure 7 shows the relationship between GY (in tons per hectare) and KNE in maize.

The linear regression line indicates the trend for the relationship between grain yield as the dependent variable (GY) and KNE as the independent variable. The histogram for grain yield shows a distribution that appears to be slightly skewed, while the histogram for KNE shows a more symmetric distribution. The correlation coefficient of 0.9357 indicates a very strong positive linear relationship between GY and KNE.

4. Discussion

Incorporating above-ground biomass into the soil has long-term benefits for crop productivity. However, the positive effects of such practices, including enhanced soil fertility and improved yield components, typically become evident only after several years of continuous application [28]. Moreover, the effects of straw return on grain yield are influenced by the straw return amounts, straw return methods, and straw return duration [16]. The evaluated treatment had a highly significant effect on GY but did not significantly impact the number of ears per hectare. The positive response of maize to management practices is consistent with the findings of [29], which indicate that maize is highly responsive to conservation practices, with a projected mean yield loss of −21% without adaptation and −7.5% with adaptation practices.

However, other factors such as kernel size, plant density, and environmental conditions such as drought influence yield, and balancing all these components are essential for optimal maize production [30,31,32]. The effect of the year on ear formation was significant, suggesting yearly variation is a contributing factor. Traits responsible for improved grain yield differed across environments because the relative importance of the determinant processes of kernel setting varies across them [33]. The management of aboveground biomass incorporation from cultivated crops (R) did not significantly improve the maize yield parameters compared to the control treatment. The incorporation of aboveground biomass can lead to effects such as nitrogen immobilization, also known as nitrogen depression. The application of industrial fertilizers significantly influenced the KNE in the F and RF treatments. KNE also depended on the dose and type of nitrogen fertilizer [34,35]. TSW is a valuable parameter for crop improvement strategies and overall crop management decisions. Kernel weight is determined during the grain-filling phase [36] and a water deficit at this stage decreased TSW [37]. In our trial, in July, the amounts of precipitation were exceptionally different between 2016 and 2018, with a deficit in August 2017 and 2018, but no significant influence of yearly conditions on the variability of the TSW was detected. The mineral fertilization (F) and interaction (RF) treatments resulted in significantly higher TSWs, indicating their positive effect on grain formation and ultimately increasing TSW. The interaction of stalk incorporation and mineral fertilization (RF) resulted in the highest TSW, suggesting a synergistic effect of combining these treatments. Straw incorporation is a widely used field management measure, but issues are associated with its high carbon–nitrogen (C:N) ratio. Ammoniated straw treatments aim to reduce the straw C:N ratio and the incorporation of ammoniated straw can enhance maize yield and yield stability and reduce the net GHG budget [38]. An adaptive measure involving the incorporation of above-ground biomass can also be associated with nitrogen depression from the preceding crop [39]. No-tillage with straw mulching is also not a suitable adaptive measure for maize [40]. Consequently, tillage practices combined with residue incorporation and N fertilization are crucial for crop productivity [41,42].

In our field trial, maize treated with fertilizers since the study began in 2005 responded positively to industrial fertilizers (F), including the split application of N (50% in ammonium form and 50% in nitrate form) and fertilizer treatments with the incorporation of the preceding crop of biomass together with industrial fertilizer (RF), with increased grain yields. Despite the long-term practice of straw return, extending for over 10 years, as reported by [43], standalone organic matter input from the forecrop was not reflected by the yield increase in the R treatments. Yield increases in the fertilized treatments were nominally greater than the yield differences observed across the evaluated growing seasons. Therefore, the impact of the applied adaptation measures exceeded the influence of or fluctuations in agrotechnical conditions during the observation years of 2016–2018.

The stalk yield reflects the environmental conditions affecting vegetative growth and determines the amount of organic matter incorporated into the soil. The aboveground dry matter yield is also an important part of the harvest index. The difference in dry matter of stalk yield between the fertilized and unfertilized treatments was 1.43 t ha⁻¹, which is comparable to the differences observed in grain production for the same treatments. This indicates that stalk yield is less sensitive to environmental changes compared to the grain yield, but the effect of different nitrogen rates on the mass per plant is evident [44]. A more pronounced effect of fertilization on the above-ground biomass of silage maize at a rate of 120 kg N compared to the unfertilized control, representing a 38% increase, was also reported [45]. This contrasts with the 15% increase observed in our experiment with FAO 300 grain maize cultivation. The HI of a crop is a measure of the efficiency with which a plant converts the dry matter it accumulates into the harvested yield. The HI, through its values, reflects the influence of the year as well as experimental interventions. Its pattern is similar to that observed for grain yield and stalk yield, which have already been discussed. The HI in the F and RF treatments indicates that the applied measures significantly increase HI. This finding aligns with the results reported by [31], who observed that increases in maize grain yield are attributed to a higher dry matter accumulation in aboveground biomass and an enhanced HI [46], and the two main ways to improve maize HI are through an increase in kernel setting and a decrease in vegetative shoot biomass [47].

The correlation analysis indicates several important relationships between maize yield components. The determined correlations of GY with TSW (r = 0.61), KNE (r = 0.94) and harvest index (r = 0.85) indicate that seed weight, number of kernels in ears, and the proportion of harvestable products are also significant factors. Our findings are consistent with previous research highlighting the importance of vegetative growth within yield [31]. Unlike wheat, a close positive correlation exists in maize between dry matter accumulation, grain yield, and plant height [48]. Relationships between production potential and yield traits such as 100 kernel weight, kernel number per row, and the row number are also crucial [47]. In the latest published research [32], a positive correlation between GY and TSW (r = 0.48) was found, supporting the importance of seed weight; however, there was a moderate correlation (r = 0.28) between grain yield and grain weight per ear, suggesting that while seed weight is important, it may not be the sole factor influencing yield.

5. Conclusions

The study underscores the significant impact of treatment interventions on maize grain yield and its components. Fertilization, particularly the combination of mineral fertilizers with aboveground biomass incorporation (RF treatment), consistently enhanced kernel number per ear (KNE), thousand seed weight (TSW), stalk yield, and overall grain yield, and also improved the HI. In contrast, treatments involving only aboveground biomass incorporation showed minimal changes, indicating that biomass management alone is insufficient to achieve optimal yields. The strong positive relationships between grain yield and factors like KNE, TSW, and HI highlight the importance of these parameters in maize production. Overall, the results emphasize the critical role of targeted fertilization strategies. We recommend the incorporation of aboveground crop biomass combined with mineral fertilization on all fields where farmyard manure (FYM) is not applied.