Integrating nitrogen fertilization with crop residue management to improve nitrogen-use efficiency of crops

doi:10.21203/rs.3.rs-2965637/v1

Nitrogen-use efficiency (NUE) of crops is critical for addressing global food security in response to climate change effects. The objective of our study was to evaluate the effects of N fertilization integrated with crop residue management to optimize NUE of crops. A replicated 2 x 4 split-plot experiment in randomized complete block design was conducted during the 2020–2022 on farmers’ fields at Bogura, Cumilla, and Mymensingh sites of Bangladesh. The main plots were two levels of crop residues (no residue, NR vs. 30% residue, CR) combined with sub-plots of four levels of N fertilizers (control, CL; farmers’ practice, FP; national recommended dose, RD, and 125% of RD, 125RD) on potato (Solanum tuberosum, L.), maize (Zea mays, L.), and rice (Oryza sativa, L.) systems. N fertilization when interacted with residue retention progressively increased crop yield. Residue alone contributed significantly to increase NUE of potato and maize by 9 and 6%, respectively. The NUE of rice increased significantly, while the NUE of maize decreased with N fertilization. The comparison of NUE models suggested that the nationally recommended N fertilization should be adjusted to 169, 152, 187, 92, and 112 kg/ha for potato, maize, Boro, Aus, and Aman rice, respectively. For potato and Aman rice, the SNMI showed better results, whereas for Boro, Aus, and maize, utilizing both NUE and SNMI provided maximum benefit from N management.

Nitrogen management index

rice

maize

potato

agroecological zone

subtropical climate

Nitrogen (N) is the most limiting nutrient essential for plant growth (Fageria & Baligar, 2005; Chen et al., 2014; Jahangir et al., 2022). The primary source of N used globally is urea, accounting for 48% of the 107 million tons (67.8 million tons) fertilizers used for crop production in 2017 (IFA, 2019). However, the NUE of crops is less than 50%; though NUE is an important index for assessing crop N requirements to maximize economic returns (Fageria & Baligar, 2005; Lassaletta et al., 2014).

Over the years, research studies had focused on rationalizing N fertilization on rice globally, which had an impact on the high-yield and high-efficiency production of rice (Qi-chun & Guang-huo, 2002; Dai et al., 2003; Lassaletta et al., 2014;). However, none of these studies have determined N optimization to obtain maximum efficiency when considering the different indices of NUE, including N response index (NRI) and sustainable N management index (SNMI) (Johnson & Raun, 2003; Zhang & Davidson, 2022).

The NUE metric assesses how effectively N is used by crops in agricultural production, while the SNMI comprises the efficiency concept of both NUE and land-use efficiency in terms of crop production (Zhang & Davidson, 2022). Moreover, inappropriate N fertilization often accelerates agroecosystem disservices (Zachos et al., 2005; Lassaletta et al., 2014; van Grinsven et al., 2015; Pituello et al., 2016; Schauberger et al., 2018; Erisman, 2021). Under global climate change effects, the accelerated agroecosystem disservices promote a reevaluation of N fertilization with the purpose of increasing NUE to maximize crop productivity. The SNMI has the advantage of tracking both increasing the benefits of N for crop production and decreasing the expenses associated with the environmental N losses (Zhang et al., 2022).

Under climate-smart agriculture, crop residue, as a biological primer, had significant positive influences on soil health, N uptake, and crop yield, and therefore, may have potential to improve NUE of crops. Global crop residue can store carbon at approximately 1.5 Pg (Kumar & Goh, 1999). However, in developing countries, residue burning due to disease control and intensive farming is very common, which favors edge-of-field N loss (Gupta & Sidhu, 2009). Emerging nations in South Asia have no choice but to engage in extensive year-round agriculture (three to four-fold per year) in order to provide food security for a large and growing population (Jahan et al., 2016).

Long-term intensive agricultural practices result in the deterioration of physical, chemical, and biological properties associated with soil health (Bonanomi et al., 2011; Chen et al., 2014; Zhou & Wu, 2015), which consequently affected crop yield and food quality (Steiner et al., 2007; Zoran et al., 2014). If managed accordingly, the nutrient-enriched crop residue can improve microbial diversity and efficiency, increase C sequestration and improve soil aggregate stability associated with soil health to support food security (Janzen & Kucey, 1988; Karlen et al., 1994; Cropping, 2005; Blanco-Canqui, 2013; Alam et al., 2020). Residue retention in conjunction with N fertilization has recently drawn considerable attention to improve soil-crop-water ecosystems (Bell et al., 2018; Xiao et al., 2021). The Integrated Soil Fertility Management (ISFM) paradigm also acknowledges the interactive advantages of integrating chemical fertilization and organic amendments to sustain nutrient management practices with improved agroecosystem services (Gentile et al., 2008).

In Bangladesh, the most important agronomic crops grown in floodplain soils are rice, potatoes, and maize, which require more N fertilizer with inefficient NUE, such as 33% for maize, 40–50% for potato, and 25–35% for rice (Jahangir et al., 2022). Residue management increases N uptake by crops and therefore, increases crop yields by influencing several indices of NUE, for instance, NRI and SNMI (Kumar & Goh, 1999; Johnson & Raun, 2003; Huang et al., 2013; Zhang & Davidson, 2022). A viable alternative to open-field hazardous burning of crop residue would be proactive crop residue retention to manipulate these indices for improving NUE of crops (Huang et al., 2013).

There are limited research investigating the effects of crop residue management integrated with N fertilization on NUE, SNMI, and crop yield to sustain agricultural production with increased environmental compatibility. We hypothesized that residue management coupled with N fertilization would enhance NUE of crops over time across agroecological zones. To test the hypothesis, our objectives were to: (i) determine the effects of residue retention and N fertilization on NUE, SNMI, and yield of potato, maize, and rice; (ii) compare maximum crop yield, minimum N requirement for per ton of yield production, and reevaluate the optimization of N fertilization; and (iii) examine the current SNMI of Bangladesh with regional data towards preventing zero hunger.

2.1 Experimental site description

The experiment was established on farmers’ fields in the Bogura district (Sherpur sub-district at 25°01'0.12" N and 89°19'0.12" E), Cumilla district (Chandina sub-district at 23°45'0.57" N and 90° 99'0.77" E), and Mymensingh district (Muktagacha sub-district at 24°45'53.42" N and 90°15'25.13" E) of Bangladesh (Fig. 1). The Mymensingh site is located in Agro-ecological Zone 28, which is comprised of Madhupur Tract loam soil (Eutric Gleysols) and contains 49% sand, 40% silt, and 11% clay, and has a bulk density of 1.2 g/cm³, pH of 5.3, total organic C of 8.12 g/kg, total N of 0.73 g/kg, available P of 5.9 mg/kg, exchangeable K of 43 mg/kg, and available S of 12.8 mg/kg. In contrast, the Bogura site with a Grey Karatoya Bangali Floodplain soil (Aeric Haplaquept) is located in Agro-ecological Zone 4, which contains sand 32%, silt 53%, and clay 15%, with a bulk density of 1.26 g/cm³, pH of 5.5, total organic C of 8.1 g/kg, total N of 1 g/kg, available P of 55.5 mg/kg, exchangeable K of 46.9 mg/kg, and available S of 16.4 mg/kg. The Cumilla site comprised of Meghna Estuarine Floodplain silt loam soil (Aeric Haplaquept) situated in Agro-ecological Zone 19 and contains sand 15%, silt 73%, and clay 13%, with a bulk density of 1.32 g/cm³, pH of 6.3, total organic C of 10.3 g/kg, total N of 1.1 g/kg, available P of 56.9 mg/kg, exchangeable K of 58.7 mg/kg, and available S of 16.3 mg/kg. All the sites are under sub-tropical climatic conditions and the maximum and minimum rainfall data are presented in Fig. 2.

2.2 Experimental design and crop management

A 2 x 4 split-plot experiment in randomized complete design with three replications was conducted during the 2020–2021 and 2021–2022 crop growing seasons at all sites. Crop residue retention was assigned as no residue (NR) and 30% residue (CR) in the main plots, and N fertilization rates were assigned as control (CL), farmers' practice (FP), recommended N dose (RD), and 125% of RD (125RD) in the sub-plots.

The cropping sequences were Potato-Boro-T., Aus-T. and Aman rice (P-R-R-R) in Bogura; Boro-T., Aus-T. and Aman rice (R-R-R) in Cumilla; and Maize-T. and Aman rice (M-R) in Mymensingh. For potatoes, CL (0), FP @ 138, RD @ 135, and 125RD @ 169 kg N/ha were applied. In Boro rice, CL (0), FP @ 120, RD @ 150, and 125RD @ 187 kg N/ha were applied. In T. Aus rice, CL (0), FP @ 77, RD @ 74, and 125RD @ 92 kg/N ha were applied, whereas T. Aman rice had CL (0), FP @ 98, RD @ 90, and 125RD @ 122 kg/N. Maize received CL (0), FP @ 152, RD @ 225, and 125RD @ 281 kg/N. While FP rates were assessed (n = 60) from a survey, the RD rates were based on Bangladesh national fertilizer recommendations (FRG, 2018).

Potatoes were grown at the Bogura site from October to February, while maize was grown at the Mymensingh site from December to May (midwinter to pre-monsoon season). Both T. Aus and T. Aman rice crops were grown from May to July (monsoon) and August to November (post monsoon to prewinter), respectively, in 2020-21 (First year) and 2021-22 (Second year). Moreover, transplanted Boro rice was grown from January to May (post-winter to pre-monsoon) at both the Bogura and Cumilla sites.

The N, P, K, S, Mg, Zn, and B fertilizer sources were urea, triple super phosphate, muriate of potash, gypsum, magnesium sulphate, zinc sulphate, and boric acid, respectively. During the final stage of land preparation, P, K, S, Mg, Zn, and B were incorporated into the soil as basal application following the Bangladesh national fertilizer recommendation guide. For maize, the N fertilizer was applied in three equal splits at 15, 35, and 55 days following seed sowing, while for potatoes, it was applied in two equal splits at 15 and 35 days after planting. For Boro rice, N was applied at 12, 37, and 57 days after transplantation. In contrast, N fertilizer was applied at 12 and 38 days in T. Aus and 12, 27, and 35 days in T. Aman rice after transplantation.

Potato (Diamond, cv.) and maize (BARI hybrid maize-14) seeds were planted/sown at the rate of 2 and 30 kg/ha, respectively. The seed-to-seed distance in each line of maize seeds was 30 cm, and the lines were spaced 60 cm apart. Potato seeds were sown on ridges at 60 cm spacing and 20 cm apart. Boro, T. Aus, and T. Aman rice were transplanted at the rate of 40 kg/ha with 20 cm spacing. The rice cultivars were BRRI-49, BINA-19, BRRI-71 in Boro, T. Aus, and T. Aman, respectively, at all the sites.

Three days prior to final land preparation, the field was sprayed with non-selective herbicide glyphosate (Round up®) at the rate of 1.85 kg/ha. Furthermore, Pretilachlor (Superhit®), a post-emergence herbicide, was applied at the rate of 450 g/ha seven days after rice seedlings transplantation. When necessary, Brifer 5G and Cidial 5G (ACI Bangladesh Ltd.) were implemented.

2.3 Crop yield and N-use efficiency

For all rice crops, a 4 m² area in the middle of each replicated plot was harvested. For maize, a 2 m² area was harvested. Grain yield (GY) of Boro, T. Aus, T. Aman, maize, and tuber yield of potatoes was calculated in a dry-matter basis by using Eq. 1 (Akter et al., 2023).

GY or tuber yield (ton/ha) = \(\frac{\text{G}\text{Y}, \text{t}\text{u}\text{b}\text{e}\text{r} \text{y}\text{i}\text{e}\text{l}\text{d} \left(\text{k}\text{g}\right) \times 10}{\text{A}\text{r}\text{e}\text{a} \text{o}\text{f} \text{t}\text{h}\text{e} \text{p}\text{l}\text{o}\text{t} \left({\text{m}}^{2}\right)}\) Eq. 1

The rice and maize grain and straw, potato tuber, and haulm N uptake were determined at oven-dried moisture basis.

Total plant N was determined by the Kjeldahl method as described by Jackson (1973) and expressed as kg/ha. The Eq. 2 was used to calculate the NUE (Moll et al., 1982):

NUE =\(\frac{{\text{N} \text{u}\text{p}\text{t}\text{a}\text{k}\text{e} }_{\text{F}\text{e}\text{r}\text{t}\text{i}\text{l}\text{i}\text{z}\text{e}\text{d} \text{p}\text{l}\text{o}\text{t}} \left(\text{k}\text{g}/\text{h}\text{a}\right)-{\text{N} \text{u}\text{p}\text{t}\text{a}\text{k}\text{e} }_{\text{C}\text{o}\text{n}\text{t}\text{r}\text{o}\text{l} \text{p}\text{l}\text{o}\text{t}} \left(\text{k}\text{g}/\text{h}\text{a}\right) }{\text{T}\text{o}\text{t}\text{a}\text{l} \text{N} \text{i}\text{n}\text{p}\text{u}\text{t} (\text{k}\text{g}/\text{h}\text{a})}\) Eq. 2

Here, N uptake (kg/ha) was calculated as per the Eq. 3 (Assefa et al., 2021).

N uptake (kg/ha) = \(\frac{\text{N}\text{u}\text{t}\text{r}\text{i}\text{e}\text{n}\text{t} \text{c}\text{o}\text{n}\text{c}\text{e}\text{n}\text{t}\text{r}\text{a}\text{t}\text{i}\text{o}\text{n} \left(\text{%}\right)\times \text{D}\text{r}\text{y} \text{B}\text{i}\text{o}\text{l}\text{o}\text{g}\text{i}\text{c}\text{a}\text{l} \text{Y}\text{i}\text{e}\text{l}\text{d} \left(\text{k}\text{g}/\text{h}\text{a}\right) }{100}\) Eq. 3

According to Pythagorean's Theorem for finding a triangle's hypotenuse, the mathematical definition of SNMI is as follows (Eq. 4) (Zhang & Davidson, 2022). The definition of SNMI based on normalized (NUE*) and N yield (NYield*).

SNMI = \(\sqrt{{\left(1-\text{N}\text{Y}\text{i}\text{l}\text{e}\text{d}\text{*}\right)}^{2}+{\left(1-\text{N}\text{U}\text{E}\text{*}\right)}^{2}}\) Eq. 4

Here, NYiled* was calculated from the Eq. 5 or 6

if NYield_ref < NYield; then NYield* = 1 Eq. 6

Here, NYield_ref = 90 kg ha^− 1yr^− 1 (Zhang & Davidson, 2022)

and if NUE ≤ NUE_ref ; then NUE* was estimated from Eq. 7. In this experiment, it was NUE ≤ NUE_ref.

The N response index (NRI) was calculated from Eq. 8 (Johnson and Raun 2003).

NRI = \(\frac{\text{M}\text{a}\text{x}\text{i}\text{m}\text{u}\text{m} {\text{Y}\text{i}\text{e}\text{l}\text{d}}_{\text{N} \text{F}\text{e}\text{r}\text{t}\text{i}\text{l}\text{i}\text{z}\text{e}\text{d} \text{c}\text{r}\text{o}\text{p}} \left(\text{t}\text{o}\text{n}/\text{h}\text{a}\right)}{{\text{Y}\text{i}\text{e}\text{l}\text{d}}_{\text{C}\text{o}\text{n}\text{r}\text{o}\text{l} \text{p}\text{l}\text{o}\text{t} \left(\text{t}\text{o}\text{n}/\text{h}\text{a}\right)}}\) Eq. 8

Kg N/ton yield was calculated as the Eq. 9, where kg N/ton yield represents the requirement of N (kg) to produce 1 ton yield.

Kg N/ton = \(\frac{\text{T}\text{o}\text{t}\text{a}\text{l} \text{N} \text{i}\text{n}\text{p}\text{u}\text{t} \text{b}\text{y} \text{f}\text{e}\text{r}\text{t}\text{i}\text{l}\text{i}\text{z}\text{e}\text{r} \left(\text{k}\text{g}/\text{h}\text{a}\right)}{\text{T}\text{o}\text{t}\text{a}\text{l} \text{y}\text{i}\text{e}\text{l}\text{d} \left(\text{t}\text{o}\text{n}/\text{h}\text{a}\right)}\) Eq. 9

2.4 N-use efficiency indices, N fertilization, and crop yield model to calculate N optimum

Statistically maximum NUE, grain yield, kg N/ton of yield, and minimum SNMI were taken into account and marked with red markers in an Excel scatter X, Y plot against N rate, where maximum NRI and minimum N rate were considered for all types of crops (potato, Boro, T. Aus, T. Aman, and maize) in order to develop the model to achieve a potentially optimal N rate. Data from Bogura and Mymensingh sites over the past two years were utilized for potatoes (n = 48) and maize (n = 48), respectively. However, for the Boro (n = 96) and T. Aus (n = 96) rice models, the average of two years data sets from two locations (Bogura and Cumilla) were taken into consideration, while for the T. Aman (n = 144)) rice model, the average of two years’ data from all three sites (Bogura, Cumilla, and Mymensingh) were utilized.

2.5 Soil analysis

Soil pH was determined (dry soil: water, 1:2.5) by electrode method (Jackson, 1973). Total organic C was determined in finely-ground (< 0.125 µg) soil by K₂Cr₂O₇ and concentrated H₂SO₄ wet oxidation method (Walkley & Black 1934). Total N was measured in finely-ground (< 0.125 µg) soil by a micro-kjeldahl digestion and distillation method (Jackson, 1973). Soil available P was measured using the Olsen method (1954). Exchangeable K in soil was extracted with 1 M neutral ammonium acetate followed by ammonia distillation using the method described by Knudsen et al. (1983). Soil available S was determined by following Hunt (1980).

Bulk density was determined by standard core method using soil mass over volume ratio (Blake & Hartge, 1986). Soil particle size analysis was performed by the standard Bouyoucos hydrometer method after oxidizing the soil organic matter with 5% H₂O₂ followed by overnight dispersion with 10% Na-hexametaphosphate solution (Gee & Bauder, 1979).

2.6 Statistical Analysis

A two-way analysis of variance (ANOVA) was performed using residue management and N fertilization as fixed independent factors. The data distribution for normality was performed before the ANOVA test. The data were statistically examined to find out the variations between residue management and N fertilization rates simple and interactive effects. The Tukey-Kramer Multiple Comparisons Test was used in post-hoc analyses to distinguish the significant differences among main- and sub-plots variations and their interactions at p ≤ 0.05, unless otherwise mentioned. All the statistical analyses were performed using Statistix-10® and the graphic illustrations were created using Microsoft Excel.

3.1 Residue and N fertilization effects on crop yield

The interaction of residue x fertilizer affected crop production, including tuber yield of potatoes and grain yield (GY) of all rice types (Boro, T. Aus and T. Aman) at Bogura site in both years (Table 5). Regardless of the residue levels, both tuber and haulm in all treatment combinations were greater in the 1st year and were identical compared to the control (CL); however, potato tuber production decreased in the 2nd year. Nevertheless, the RD and 125RD treatments in combination with both CR (GY at 6.94 t/ha in CR and RD, 7.72 t/ha in CR and 25RD) and NR (GY at 6.58 t/ha in NR and RD, 7.11 t/ha in NR and 125RD) resulted maximum GY in Boro rice in the 2nd year, whereas only 125RD resulted the maximum results in the 1st year (GY at 7.2 t/ha in NR and 125RD, 7.59 t/ha in CR and 125RD). Moreover, the FP, RD, and 125RD with both residue levels produced the highest GY in both years for T. Aus and T. Aman rice (Table. 5).

At Cumilla site, the interaction of residue x fertilizer significantly impacted GY of all rice crops (Boro, T. Aus, and T. Aman) in both years, with the exception of T. Aus rice in the 2nd year. In this case, only the fertilizer effect on GY in the 2nd year of T. Aus rice was significant, with 125RD treatment producing the highest results (GY at 5.33 t/ha). In contrast, Boro and T. Aman rice produced the highest and identical GY for both years when the FP, RD, and 125RD were coupled with both residue levels. The CR and 125RD produced more than 7 t/ha GY in Boro rice (Table. 6).

The interaction of residue x fertilizer had a significant effect on maize GY in the 2nd year at Mymensingh site. The maximum GY of maize was recorded for the FP, RD, and 125RD treatments in combination with different residue levels in the 2nd year. In contrast, the effect of fertilization was significant on GY of T. Aman and maize in both years. The FP (10.36 t/ha), RD (10.31 t/ha), and 125RD (10.1 t/ha) treatments resulted highest GY of maize in the 1st year. Besides that, only 125RD treatment produced highest GY of T. Aman rice in both years (5.28 t/ha in the 1st year and 5.5 t/ha in the 2nd year) (Table 6).

3.2 Residue and N fertilization effects on N-use efficiency of crops

At Bogura site, while the interaction of residue x fertilizer on N-use efficiency (NUE) of Boro and T. Aman was significant in the 1st year, it was significant on potato, T. Aus, and T. Aman in the 2nd year. The maximum NUE was recorded in the RD and 125RD regardless of the CR or NR in T. Aus in the 2nd year. Under CR, the maximum NUE was observed in 125RD (0.5) for Boro rice. In the 1st year, the NUE of T. Aman rice was its maximum in the RD (0.42) and FP (0.4) with NR and CR 125RD (0.38). In the 2nd year, by excluding the NR and FP, each treatment combination resulted in similar and maximum NUE of crops (Table 1). Residue effect on NUE of potato and Boro rice was significant in both years, while the effect of N fertilizer was significant on T. Aus rice in the 1st year. The maximum NUE of crops was recorded in the CR (0.62 for potato and 0.45 for Boro rice) rather than the NR (0.53 for potato and 0.4 for Boro rice). The highest NUE of crops was recorded in 125RD (0.31) and FP (0.27) for T. Aus rice (Table 1).

The NUE of crops was significantly affected by the interaction of residue x N fertilization for Boro rice in the 1st year and T. Aus and T. Aman rice in both years at Cumilla site. Excluding the CR and FP, other treatment combinations resulted in the maximum and statistically similar NUE of Boro rice. Besides that, the FP (0.3), RD (0.52), and 125RD (0.46) in combination with NR, resulted highest NUE of crops, while only 125RD showed the highest NUE (0.43) for T. Aus rice in the 1st year. In contrast, excluding the NR and RD and CR and FP, other treatment combinations yielded the highest NUE of T. Aus rice in the 2nd year. Without the NR and RD, other treatments showed the similar and highest NUE of T. Aman rice in the 1st year, while the CR and RD (0.52) resulted the highest NUE of crops in the 2nd year. Furthermore, residue management significantly influenced the NUE of Boro rice in the 2nd year, while the maximum NUE (0.42) of crops was observed in the CR (Table 2).

At Mymensingh site, the interactive effects of residue x N fertilization variably affected the NUE of maize for both years, and also for T. Aman in the 1st year. In maize, the CR and FP consistently improved NUE of crops (0.55 in the 1st year and 0.72 in the 2nd year). In contrast, the 125RD, either with NR or CR, had the minimum NUE of crops, while other treatment combinations resulted in the similar and maximum NUE of T. Aman rice in the 1st year. Nitrogen fertilization had a significant effect on T. Aman rice in the 2nd year. The maximum NUE of crops was observed in the RD (0.43) and 125RD (0.44) at different N fertilization rates (Table 2).

3.3 Residue and N fertilization effects on sustainable N management index

Residue x N fertilization had a significant interaction to influence sustainable N management index (SNMI) of potatoes for both years, Boro rice in the 1st year, and also T. Aus and T. Aman rice in the 2nd year at Bogura site. While the lowest SNMI was recorded in the FP (0.6 in NR and 0.66 in CR) and RD (0.66 in NR and 0.59 in CR), either with the NR or CR on potatoes in the 1st year, the CR and125RD (0.44) had the lowest SNMI in the 2nd year. In contrast, under the NR, the FP (0.62) and RD (0.57) and under the CR, the RD (0.58) resulted in the minimum SNMIs of Boro rice in the 1st year. The SNMI of T. Aus rice in the 2nd year, the RD, and 125RD regardless of the residue levels resulted in the minimum SNMI values, while in the T. Aman rice, without the NR, the FP and other treatment combinations showed the similar and lowest SNMI values. The effect of N fertilization on SNMI of Boro and T. Aus rice was significant both years. The RD (0.59) and 125RD (0.61) had the lowest SNMI values of T. Aus rice, while the FP (0.74) and 125RD (0.69) resulted in the minimum SNMI values (Table 3).

At Cumilla site, the SNMI values of Boro, T. Aman and T. Aus rice were significantly affected by the residue x N fertilization in both years. The RD (0.61 in NR and 0.68 in CR) and the 125RD (0.68 in NR and 0.6 in CR), either with NR or CR, had the minimum SNMI values of Boro rice. However, with NR, the RD (0.62) and 125RD (0.55) and the 125RD (0.59) with CR had the minimum SNMIs of T. Aus rice in the 1st year. Similarly in the 2nd year, SNMI was the lowest in NR and FP (0.5), NR and 125RD (0.5), CR and RD (0.41), and CR and 125RD (0.43) in T. Aus rice. In T. Aman rice, without NR and RD, other treatments resulted in the minimum SNMI values in the 1st year, whereas the CR and 125RD had the minimum SNMI in the 2nd year. The effect of crop residue on SNMI of Boro rice was significant in the 2nd year, where the CR (0.58) showed the minimum SNMI values (Table 4).

The SNMI values of maize and T. Aman rice did significantly affect by the interaction of residue x N fertilization in both years at Mymensingh site. The CR and FP treatment resulted in the lowest SNMI values (0.45 in the 1st year; 0.28 in the 2nd year) of maize. In contrast, without the NR and RD and NR and FP other treatment combinations resulted in the minimum SNMI values of T. Aman rice in both years (Table 4).

3.4 N-use efficiency model comparisons among different crops

Averaged across years, the CR and 125RD treatment combination resulted in the maximum NRI (3.6), NUE (0.6), tuber yield (35.5 kg/ha), and N uptake (147.9 kg/ha); N fertilization at 169 kg/ha was the most optimized rate for growing potatoes (Fig. 3). The correlation of SNMI was higher with N fertilization rates (R² = 0.86) and tuber yield (R² = 0.63) than that of the NUE (Fig. 4), suggesting that SNMI is more optimized N indicator than the NUE for growing potatoes. For maize, reduced N fertilization (FP @ 152 kg/ha) in combination with residue management yielded the maximum NRI (3.9), NUE (0.64), and grain yield (11.4 ton/ha), and the minimum 13.5 kg N/ton of yield requirement and SNMI (0.36), though the N uptake was not the highest, it still improves the maximum efficiency indices to optimize N fertilization for growing maize (Fig. 3). The correlation of SNMI and NUE is similar with both N fertilization and maize yield (Fig. 4), suggesting both indicators can be simultaneously used for ensuring maximum N-use efficiency in maize production.

The CR and 125RD combination showed the maximum NRI (1.8), NUE (0.44), grain yield (7.6 ton/ha), and N uptake (149.1 kg N/ha) with the minimum SNMI (0.56) for Boro rice. This implies 187 kg N/ha coupled with residue management is the optimum dose expected to obtain maximum N-use efficiency (Fig. 3). Both NUE and SNMI indices showed similar correlation with grain yield, whereas the SNMI (R²= -0.83) with N fertilization showed similar correlation than that of the NUE (R² = 0.82) of Boro rice, which accounted more than 80% of the variability in grain yield explained by all these indices (Fig. 4). In contrast, NR and 125RD treatment combination resulted in the maximum NRI (1.5), NUE (0.41), grain yield (5.2 ton/ha), and N uptake (98.3 kg/ha) of T. Aus rice with the minimum SNMI (0.6), therefore implying that 92 kg N/ha had the higher efficiency that maximizes the N-use indices (Fig. 3). The correlation of NUE and SNMI with N fertilization and T. Aus rice yield had similar correlations to account for variability in the grain yield (Fig. 4). For T. Aman rice, the NR and 125RD combination had the highest NRI (1.7), NUE (0.4), grain yield (5.5 ton/ha), and N uptake (92.5 kg/ha), where the SNMI (0.6) was its minimum, which indicates that 112 kg N/ha is the most appropriate rate to obtain the maximum N-use efficiency for growing T. Aman rice (Fig. 3). The correlation of SNMI (R²= -0.29) was slightly higher with N fertilization than that of the NUE (R² = 0.15). Similarly with T. Aman GY, the SNMI had a stronger correlation (R² = 0.7) than that of the NUE (R² = 0.59), indicating SNMI is a better N indicator than the NUE to account significant grain yield variability (Fig. 4).

4.1 Crop yield

Our results implied that N fertilization integrated with crop residue management significantly increased crop yields, except for potato tuber yields. A significant decrease in potato yield in the 2nd growing year when compared to the 1st year was due to varietal differences. In contrast, a significant increase in maize and rice grain yield was due to improved soil fertility in response to greater availability of labile carbon to carryout soil biological functions and their metabolic efficiency to release essential nutrients from decomposing crop residues and soil native organic matter (Smith et al., 1992; Hadas et al., 2004; Singh & Rengel, 2007). As expected, the decomposing residues and their metabolites are not only improved soil fertility, but increased soil water-holding capacity to improve soil quality and support crop productivity (Halder et al., 2023; Singh & Rengel, 2007). While N is the most critical essential nutrient required by the plants (Bernard & Habash, 2009; Wang et al., 2021); however, the FP, RD, and 125RD treatments did not consistently increase maize yield with N fertilization, indicating a lack of sufficient N or partial availability of N to achieve the highest grain yield and efficiency for maize. Rice yield was at its maximum in response to RD and 125RD treatments due to optimization of N availability to rice under water-logged conditions. Several research studies have sought to rationalize N fertilization of rice globally, which has an impact on the production (Qi-chun & Guang-huo, 2002; Dai et al., 2003; Lassaletta et al., 2014). Adhikari et al. (2021) reported that the highest rice yield in Nepal was observed in response RD and 125RD treatments, which is very much analogous to our study results. Nevertheless, Ahmed et al. (2005) reported to achieve the highest rice yield at lower N rates. Adding N fertilizer can frequently result in a large improvement in crop yield in soils that have inherently reduced soil fertility with a limited biological efficiency, which could be the reasons for variable results.

4.2 N-use efficiency of crops

Significant improvement in the NUE of crops by residue management at all sites was expected to be associated with the mulching effect to preserve soil moisture followed by the release of nutrients, especially N and labile C, from decomposing residues (Joern & Vadas et al., 2004; Scopel et al., 2004). Moreover, the formation of organically-bound ammonium compounds from the urea hydrolysis and decomposing crop residues to humic compounds may prolong the residence time of NH₄⁺ for NO₃⁻ in the soil (Lu et al. 2015; Huang & Hardie, 2009). These available N (NH₄⁺ and NO₃⁻) compounds subsequently uptake by growing crops, thus increasing the NUE of crops (Panuccio et al., 2001). It is suggested that crop residue management can lead to a reduction in routine N fertilization required to achieve targeted crop yield. However, a reduction in NUE of crop with residue management in T. Aus at Cumilla site in the 1st year, might be due to accelerated N leaching, denitrification, and erosion from soil, resulting from the effects of torrential rain during the growing season. Another explanation for this disparate result is that NUE of crop is more likely to be a genetic, physiological, environmental, and agronomic parameter than the N fertilization alone (Congreves et al., 2021).

With increasing N fertilization rates, the NUE of maize diminished which may be associated with increased vegetative growth compared to the grain yield. Lower N fertilization rates resulted in the maximum NUE in C₄ plants (for maize: NUE in FP > RD > 125RD) than that of the C₃ plants which is identical to our experiment results (Sage & Pearcy, 1987), The C₄ plants, like maize, are more efficient in photosynthesis than the C₃ rice, which require extra energy in fixing CO₂ into 4 C molecules before entering the Calvin cycle (Burgess & Wang 2022), and need more N for higher energy expenditure C₄ photosynthetic pathway. Therefore, it is possible that maize was utilizing lower rates of N more efficiently than higher rates of N fertilization. Accordingly, maize with higher N rates have experienced a lower NUE due to the lack of appropriate N fertilization.

The effect of N fertilization was significant on NUE of Boro, T. Aus, and T. Aman for at least one year at each location. The NUE may actually decline if the amount of N taken by the plant does not increase grain yield proportionately to the amount of external N inputs. Meanwhile, rice has a greater N fertilization boundary limit than maize for simultaneously improving NUE without a decline. It is reported that the NUE increased with increasing N fertilization in the sandy soils (Ye et al., 2007), which is analogous to the NUE of T. Aman rice observed at Mymensingh site. In other soils, the NUE of crops showed a non-linear response to N fertilization (Ye et al., 2007), which might be identical our results on T. Aman rice at Cumilla site. Across our research studies, the mean NUE increased by 1% for rice, 9% for potato, and 6% for maize over the years and the overall residue contribution to improve NUE was 3% to justify the long-term effects of N fertilization to improve NUE of crops.

4.3 Sustainable N management index

Sustainable N management is one of the critical challenges to address global food security, including Bangladesh. The SNMI value was 0.67 in Bangladesh until 2015 (Sustainable Development Report, 2022), when averaged across crops, sites and year, while the SNMI value of 0 is the long-term goal for this indicator to grow major agronomic crops. Our results have shown that crop residue management combined with N fertilization significantly decreased the SNMI values. While the mean SNMI of rice (averaged across types, site, and year) was 0.62, the SNMI values of potatoes and maize were 0.59 and 0.50, respectively. Averaged across all crops, the mean SNMI value was 0.61, which was lower than Bangladesh's current SNMI values (0.67). Based on our computation of the statistical trend over time (2000-15), the SNMI should be 0.49 in 2023, which suggests Bangladesh's current SNMI is 10 year. behind (2013) what the nation's SNMI is supposed to be in 2023, considering universal reference yield 90 kg N/ha. Even while our experimental data shown that the present SNMI is 8% lower than it was in 2015, this was mostly accomplished by boosting yield production without improving the NUE of crops (Zhang et al., 2022). Our results also suggested that crop residue is contributing to lower down SNMI by 3% over a period of two years (NR SNMI: 0.62 vs. CR SNMI: 0.59), whereas the overall national progress was 8% during the past seven yr.

Crop residue when interacting with N fertilizer progressively increased crop yield. Residue alone improved the NUE of crops by 9% and 6% for potato and maize, respectively. With N fertilization, the NUE of rice significantly increased; however, the NUE of maize decreased. Compared to the national SNMI value in 2015, the calculated SNMI in 2022 is 0.61, indicating a 6% improvement in NUE. The potential N fertilization rates were 169, 152, 187, 92, and 112 kg/ha for optimizing growth of potato, maize, Boro, T. Aus, and T. Aman rice, respectively, to attain maximum efficiency. Instead of NUE, the SNMI is suggested when growing potato and T. Aman rice, whereas both indicators can be used simultaneously for Boro, T. Aus, and maize. However, this still leaves the goal of zero hunger by 12% behind the expected SNMI in 2022, and long-term crop residue management can assist in achieving this goal.

Consent for Publication

The final version of the manuscript was reviewed and approved by all authors.

Competing Interest

The authors declare no competing interests.

Conflict of Interest

The authors declare that there is no potential conflict of interests.

Funding

This research was financially supported by BAURES (Bangladesh Agricultural University Research System) Endowment Program, Project code- BAU/139/2022

Acknowledgments

We sincerely thank Dr. Bradford Sherman for his assistance in editing this manuscript's English and fixing the manuscript's grammar. His proficiency as a native speaker has significantly improved the precision and caliber of our study. We are really grateful for his kind assistance and support.

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Table 1

The effect of crop residue, N fertilizer, and their interaction effect on NUE in potato, Boro, T. Aus, and T. Aman rice in Bogura, 2020-21 & 2021-22
		Bogura
Residue	N Rate	Potato		Boro		T. Aus		T. Aman
		2020-21	2021-22	2020-21	2021-22	2020-21	2021-22	2020-21	2021-22
NR		0.53 ± 0.01b	0.46 ± 0.01b	0.4 ± 0.01	0.4 ± 0.01 b	0.27 ± 0.02	0.38 ± 0.02	0.39 ± 0.01	0.35 ± 0.03
CR		0.62 ± 0.01 a	0.55 ± 0.01 a	0.45 ± 0.02	0.45 ± 0.01 a	0.27 ± 0.02	0.36 ± 0.02	0.37 ± 0.01	0.39 ± 0.01
Statistics (p = 0.05)		0.08 (*)	0.04 (*)	ns	0.05 (*)	ns	ns	ns	ns
	FP	0.58 ± 0.07	0.51 ± 0.03	0.41 ± 0.02	0.42 ± 0.04	0.27 ± 0.02 ab	0.29 ± 0.03 b	0.38 ± 0.01	0.31 ± 0.06 b
	RD	0.56 ± 0.05	0.49 ± 0.05	0.43 ± 0.01	0.4 ± 0.04	0.23 ± 0.01 b	0.41 ± 0.03 a	0.39 ± 0.03	0.42 ± 0.01 a
	125RD	0.58 ± 0.02	0.51 ± 0.05	0.44 ± 0.06	0.45 ± 0.01	0.31 ± 0.02 a	0.39 ± 0.02 a	0.37 ± 0.01	0.39 ± 0.01 a
Statistics (p = 0.05)		ns	ns	ns	ns	0.05 (**)	0.07 (**)	ns	0.044 (***)
NR	FP	0.51 ± 0.02	0.47 ± 0.01 ab	0.38 ± 0.02 b	0.38 ± 0.02	0.25 ± 0.01	0.32 ± 0.02 ab	0.4 ± 0.02 ab	0.24 ± 0.01 b
	RD	0.51 ± 0.02	0.45 ± 0.02 b	0.43 ± 0.02 ab	0.36 ± 0	0.24 ± 0.02	0.44 ± 0.02 a	0.42 ± 0.01 a	0.41 ± 0.02 a
	125RD	0.56 ± 0.02	0.45 ± 0 b	0.39 ± 0.01 b	0.44 ± 0.02	0.33 ± 0.03	0.37 ± 0.02 ab	0.37 ± 0.02 bc	0.39 ± 0.01 a
CR	FP	0.65 ± 0.02	0.54 ± 0.02 ab	0.43 ± 0.01 b	0.46 ± 0.02	0.28 ± 0.03	0.27 ± 0.02 b	0.37 ± 0.01 bc	0.37 ± 0.01 a
	RD	0.61 ± 0.01	0.54 ± 0.01 ab	0.42 ± 0.02 b	0.44 ± 0.02	0.23 ± 0.02	0.39 ± 0.02 ab	0.36 ± 0.01 bc	0.43 ± 0.02 a
	125RD	0.6 ± 0.02	0.56 ± 0.01 a	0.5 ± 0.03 a	0.45 ± 0.02	0.29 ± 0.02	0.41 ± 0.01 a	0.38 ± 0.01 abc	0.38 ± 0.02 a
Statistics (p = 0.05)		ns	0.1 (*)	0.08 (*)	ns	ns	0.11 (*)	0.04 (*)	0.12 (**)

In each column, the means ± standard error values denoted by the same letter are not significantly different at the p<0.05 level, *; significantly different at the p<0.05 level, **; significantly different at the p<0.01 level, ***; and significantly different at the p<0.001 level, ns; not significantly different. On the other hand, LSD value (p=0.05) assigned with asterisks represents the critical number that defines significant deference among the treatment combination.

Table 2

The effect of crop residue, N fertilizer, and their interaction effect on NUE in Boro, T. Aus, and T. Aman rice in Cumilla; maize and T. Aman in Mymensingh, 2020-21 & 2021-22
		Cumilla						Mymensingh
Residue	N Rate	Boro		T. Aus		Aman		Maize		T. Aman
		2020-21	2021-22	2020-21	2021-22	2020-21	2021-22	2020-21	2021-22	2020-21	2021-22
NR		0.36 ± 0.02	0.35 ± 0.01 b	0.39 ± 0.03 a	0.47 ± 0.02	0.39 ± 0.02	0.29 ± 0.02 b	0.42 ± 0.04 b	0.52 ± 0.02 b	0.41 ± 0.01	0.4 ± 0.02
CR		0.31 ± 0.03	0.42 ± 0.01 a	0.31 ± 0.03 b	0.54 ± 0.02	0.39 ± 0.01	0.45 ± 0.03 a	0.47 ± 0.02 a	0.58 ± 0.04 a	0.38 ± 0.01	0.43 ± 0.01
Statistics (p = 0.05)		ns	0.04 (*)	0.06 (*)	ns	ns	0.04 (**)	0.06 (*)	0.06 (*)	ns	ns
	FP	0.26 ± 0.04 b	0.37 ± 0.04	0.28 ± 0.02 b	0.47 ± 0.01 b	0.4 ± 0.03	0.3 ± 0.07 c	0.54 ± 0.01 a	0.65 ± 0.07 a	0.4 ± 0.01 a	0.38 ± 0.03 b
	RD	0.35 ± 0.03 a	0.39 ± 0.05	0.34 ± 0.08 b	0.5 ± 0.09 ab	0.37 ± 0.04	0.43 ± 0.09 a	0.47 ± 0 b	0.53 ± 0.01 b	0.42 ± 0.02 a	0.43 ± 0.01 a
	125RD	0.4 ± 0 a	0.4 ± 0.02	0.44 ± 0.02 a	0.53 ± 0.03 a	0.4 ± 0	0.38 ± 0.08 b	0.34 ± 0.05 c	0.48 ± 0.02 c	0.36 ± 0.02 b	0.44 ± 0 a
Statistics (p = 0.05)		0.05 (***)	ns	0.06 (***)	0.05 (*)	ns	0.04 (***)	0.04 (***)	0.04 (***)	0.04 (*)	0.03 (**)
NR	FP	0.31 ± 0.02 ab	0.32 ± 0.02 b	0.3 ± 0.03 a	0.5 ± 0.02 ab	0.43 ± 0.02 a	0.23 ± 0.02 d	0.53 ± 0.02 ab	0.57 ± 0.02 b	0.41 ± 0.02 ab	0.35 ± 0.02 b
	RD	0.39 ± 0.02 a	0.34 ± 0.02 b	0.42 ± 0.02 ab	0.42 ± 0.02 c	0.33 ± 0.01 b	0.35 ± 0.01 c	0.46 ± 0.01 c	0.54 ± 0.01 b	0.44 ± 0.01 a	0.42 ± 0.02 a
	125RD	0.4 ± 0.02 a	0.38 ± 0.02 ab	0.46 ± 0.02 a	0.5 ± 0.02 ab	0.4 ± 0.01 ab	0.31 ± 0.01 c	0.28 ± 0.02 e	0.46 ± 0.01 c	0.38 ± 0.02 bc	0.44 ± 0.01 a
CR	FP	0.22 ± 0.01 b	0.41 ± 0.01 ab	0.25 ± 0.03 c	0.47 ± 0.02 bc	0.38 ± 0.01 ab	0.36 ± 0.03 c	0.55 ± 0.02 a	0.72 ± 0.01 a	0.39 ± 0.01 abc	0.41 ± 0.01 a
	RD	0.32 ± 0.01 a	0.44 ± 0.01 a	0.26 ± 0.02 c	0.59 ± 0.03 a	0.41 ± 0.02 ab	0.52 ± 0.03 a	0.47 ± 0.01 bc	0.52 ± 0.01 bc	0.4 ± 0 abc	0.44 ± 0.01 a
	125RD	0.4 ± 0.02 a	0.41 ± 0 ab	0.43 ± 0.01 ab	0.57 ± 0.03 a	0.4 ± 0.03 ab	0.46 ± 0.02 b	0.39 ± 0.01 d	0.5 ± 0.01 bc	0.34 ± 0.03 c	0.44 ± 0.01 a
Statistics (p = 0.05)		0.12 (*)	0.09 (*)	0.14 (*)	0.12 (**)	0.09 (*)	0.06 (*)	0.11 (*)	0.13 (**)	0.07 (*)	0.05 (*)

In each column, the means ± standard error values denoted by the same letter are not significantly different at the p<0.05 level, *; significantly different at the p<0.05 level, **; significantly different at the p<0.01 level, ***; and significantly different at the p<0.001 level, ns; not significantly different. On the other hand, LSD value (p=0.05) assigned with asterisks represent the critical number that defines significant deference among the treatment combination

Table 3

The effect of crop residue, N fertilizer, and their interaction effect on SNMI in potato, Boro, T. Aus, and T. Aman rice in Bogura, 2020-21 & 2021-22
		Bogura
Residue	N Rate	Potato		Boro		T. Aus		T. Aman
		2020-21	2021-22	2020-21	2021-22	2020-21	2021-22	2020-21	2021-22
NR		0.67 ± 0.03	0.54 ± 0.01 a	0.6 ± 0.01	0.63 ± 0.02	0.73 ± 0.02	0.38 ± 0.02 a	0.61 ± 0.01	0.64 ± 0.03 a
CR		0.68 ± 0.03	0.45 ± 0.01 b	0.55 ± 0.02	0.65 ± 0.03	0.74 ± 0.01	0.36 ± 0.02 b	0.65 ± 0.01	0.61 ± 0.01 b
Statistics (p = 0.05)		ns	0.04 (*)	ns	ns	ns	0.02 (*)	ns	0.02 (*)
	FP	0.63 ± 0.03 b	0.49 ± 0.03	0.59 ± 0.02 c	0.71 ± 0.03 a	0.74 ± 0.01 ab	0.29 ± 0.03 b	0.63 ± 0.02	0.7 ± 0.07 a
	RD	0.6 ± 0.01 b	0.51 ± 0.05	0.57 ± 0.01 b	0.59 ± 0.03 b	0.77 ± 0.01 a	0.41 ± 0.03 a	0.63 ± 0.0	0.56 ± 0.01 b
	125RD	0.79 ± 0 a	0.49 ± 0.05	0.56 ± 0.06 a	0.61 ± 0.02 b	0.69 ± 0.02 b	0.39 ± 0.02 a	0.63 ± 0.01	0.61 ± 0.01 b
Statistics (p = 0.05)		0.05 ***	ns	0.03 (***)	0.04 (*)	0.05 (**)	0.07 (**)	ns	0.05 (***)
NR	FP	0.6 ± 0 b	0.53 ± 0.01 ab	0.62 ± 0.02 a	0.62 ± 0.02	0.75 ± 0.02	0.68 ± 0.02 a	0.61 ± 0.02	0.77 ± 0.02 a
	RD	0.61 ± 0.01 b	0.55 ± 0.02 a	0.57 ± 0.02 b	0.64 ± 0.02	0.76 ± 0.02	0.56 ± 0.02 b	0.59 ± 0.01	0.55 ± 0.02 b
	125RD	0.79 ± 0.01 a	0.55 ± 0 a	0.61 ± 0.01 a	0.56 ± 0.01	0.67 ± 0.03	0.63 ± 0.02 ab	0.64 ± 0.01	0.61 ± 0.01 b
CR	FP	0.66 ± 0.02 b	0.46 ± 0.02 ab	0.57 ± 0.01 b	0.54 ± 0.02	0.72 ± 0.02	0.74 ± 0.03 a	0.65 ± 0.01	0.63 ± 0.01 b
	RD	0.59 ± 0 b	0.46 ± 0.01 ab	0.58 ± 0.02 ab	0.56 ± 0.02	0.79 ± 0.01	0.62 ± 0.02 ab	0.67 ± 0.01	0.57 ± 0.02 b
	125RD	0.78 ± 0.03 a	0.44 ± 0.01 b	0.5 ± 0.03 c	0.55 ± 0.02	0.71 ± 0.02	0.59 ± 0.01 b	0.62 ± 0.01	0.62 ± 0.02 b
Statistics (p = 0.05)		0.08 (*)	0.1 (*)	0.04 (**)	ns	ns	0.11 (*)	ns	0.07 (**)

In each column, the means ± standard error values denoted by the same letter are not significantly different at the p<0.05 level, *; significantly different at the p<0.05 level, **; significantly different at the p<0.01 level, ***; and significantly different at the p<0.001 level, ns; not significantly different. On the other hand, LSD value (p=0.05) assigned with asterisks represent the critical number that defines significant deference among the treatment combination

Table 4

The effect of crop residue, N fertilizer, and their interaction effect on SNMI in Boro, T. Aus, and T. Aman rice in Cumilla; maize and T. Aman in Mymensingh, 2020-21 & 2021-22
		Cumilla						Mymensingh
Residue	N Rate	Boro		T. Aus		Aman		Maize		T. Aman
		2020-21	2021-22	2020-21	2021-22	2020-21	2021-22	2020-21	2021-22	2020-21	2021-22
NR		0.64 ± 0.02 b	0.65 ± 0.01 a	0.65 ± 0.03 b	0.53 ± 0.02	0.61 ± 0.02	0.75 ± 0.03 a	0.58 ± 0.04 b	0.48 ± 0.02 a	0.62 ± 0.01	0.61 ± 0.02
CR		0.69 ± 0.03 a	0.58 ± 0.01 b	0.74 ± 0.04 a	0.46 ± 0.02	0.61 ± 0.01	0.57 ± 0.03 b	0.53 ± 0.02 a	0.42 ± 0.04 b	0.65 ± 0.01	0.58 ± 0.01
Statistics (p = 0.05)		0.03 (*)	0.05 (*)	0.02 (**)	ns	ns	0.09 (*)	0.03 (*)	0.04 (*)	ns	ns
	FP	0.74 ± 0.05 a	0.63 ± 0.04	0.79 ± 0.02 a	0.52 ± 0.02 a	0.6 ± 0.03 b	0.76 ± 0.08 a	0.46 ± 0.01 c	0.35 ± 0.07 c	0.64 ± 0	0.64 ± 0.04 a
	RD	0.65 ± 0.03 b	0.6 ± 0.04	0.71 ± 0.09 b	0.5 ± 0.09 ab	0.63 ± 0.04 a	0.58 ± 0.1 c	0.53 ± 0 b	0.47 ± 0.01 b	0.62 ± 0.02	0.58 ± 0.01 b
	125RD	0.6 ± 0 b	0.6 ± 0.02	0.57 ± 0.02 c	0.47 ± 0.03 b	0.6 ± 0 b	0.63 ± 0.09 b	0.66 ± 0.05 a	0.52 ± 0.02 a	0.66 ± 0.02	0.56 ± 0 b
Statistics (p = 0.05)		0.05 (***)	ns	0.06 (***)	0.05 (*)	0.02 (*)	0.04 (***)	0.04 (***)	0.05 (***)	ns	0.04 (***)
NR	FP	0.69 ± 0.01 ab	0.68 ± 0.02	0.77 ± 0.02 a	0.5 ± 0.01 bc	0.57 ± 0.01 b	0.84 ± 0.01 a	0.47 ± 0.02 de	0.43 ± 0.02 b	0.63 ± 0.03 ab	0.67 ± 0.02 a
	RD	0.61 ± 0.02 b	0.65 ± 0.01	0.62 ± 0.02 b	0.6 ± 0.02 a	0.67 ± 0.01 a	0.69 ± 0.02 b	0.54 ± 0.01 c	0.46 ± 0.01 ab	0.6 ± 0.01 b	0.59 ± 0.02 b
	125RD	0.6 ± 0.01 b	0.62 ± 0.02	0.55 ± 0.01 b	0.5 ± 0.02 bc	0.6 ± 0.01 ab	0.71 ± 0.02 b	0.72 ± 0.02 a	0.54 ± 0.01 a	0.64 ± 0.02 ab	0.56 ± 0.01 b
CR	FP	0.78 ± 0.02 a	0.59 ± 0.02	0.82 ± 0.01 a	0.54 ± 0.03 ab	0.63 ± 0.02 ab	0.67 ± 0.01 b	0.45 ± 0.02 e	0.28 ± 0.02 c	0.64 ± 0.02 ab	0.6 ± 0.02 b
	RD	0.68 ± 0.01 b	0.56 ± 0.01	0.81 ± 0.03 a	0.41 ± 0.03 c	0.59 ± 0.02 b	0.48 ± 0.02 d	0.53 ± 0.02 cd	0.48 ± 0.01 ab	0.63 ± 0.02 ab	0.57 ± 0.02 b
	125RD	0.6 ± 0.01 b	0.59 ± 0	0.59 ± 0.02 b	0.43 ± 0.03 c	0.6 ± 0.02 ab	0.54 ± 0.02 c	0.61 ± 0.01 b	0.5 ± 0.01 ab	0.67 ± 0.01 a	0.56 ± 0.01 b
Statistics (p = 0.05)		0.11 (*)	ns	0.1 (**)	0.11 (**)	0.09 (**)	0.09 (*)	0.05 (*)	0.09 (**)	0.08 (*)	0.06 (*)

In each column, the means ± standard error values denoted by the same letter are not significantly different at the p<0.05 level, *; significantly different at the p<0.05 level, **; significantly different at the p<0.01 level, ***; and significantly different at the p<0.001 level, ns; not significantly different. On the other hand, LSD value (p=0.05) assigned with asterisks represent the critical number that defines significant deference among the treatment combination

Table 5

The effect of crop residue, N fertilizer, and their interaction effect on potato, Boro, T. Aus, and T. Aman yield (t/ha) in Bogura, 2020-21 & 2021-22
		Potato		Boro		T. Aus		T. Aman
		Tuber Yield		Grain Yield		Grain Yield		Grain Yield
Residue	Fertilizer	2020-21	2021-22	2020-21	2021-22	2020-21	2021-22	2020-21	2021-22
NR		33.8 ± 2.97	22.91 ± 2.84	5.66 ± 0.43	6.19 ± 0.26	4.23 ± 0.16	4.57 ± 0.22	4.5 ± 0.2	5 ± 0.23
CR		31.22 ± 2.89	24.93 ± 3.07	5.77 ± 0.44	6.43 ± 0.36	4.15 ± 0.14	4.64 ± 0.24	4.46 ± 0.22	5.22 ± 0.24
Statistics (p = 0.05)		ns	ns	ns	ns	ns	ns	ns	ns
	CL	16.93 ± 0.81 c	7.35 ± 0.41 b	3.64 ± 0.15 d	4.84 ± 0.17 d	3.55 ± 0.15 b	3.48 ± 0.11 b	3.36 ± 0.13 b	3.92 ± 0.09 c
	FP	38.6 ± 1.14 ab	28.58 ± 1.02 a	5.51 ± 0.11 c	6.25 ± 0.23 c	4.33 ± 0.13 a	4.81 ± 0.15 a	4.69 ± 0.11 a	5.33 ± 0.24 b
	RD	34.58 ± 1.13 b	29.41 ± 1.06 a	6.3 ± 0.21 b	6.76 ± 0.17 b	4.25 ± 0.12 a	4.87 ± 0.21 a	4.89 ± 0.09 a	5.38 ± 0.1 ab
	125RD	39.91 ± 2.41 a	30.33 ± 1.37 a	7.39 ± 0.29 a	7.41 ± 0.23 a	4.62 ± 0.14 a	5.27 ± 0.17 a	4.98 ± 0.09 a	5.78 ± 0.13 a
Statistics (p = 0.05)		4.42 (***)	2.27 (***)	0.77 (***)	0.49 (***)	0.52 (***)	0.51 (***)	0.34 (***)	0.42 (***)
NR	CL	18.19 ± 0.38 b	7.02 ± 0.76 b	3.67 ± 0.33 d	4.86 ± 0.09 c	3.51 ± 0.15 b	3.42 ± 0.06 b	3.41 ± 0.23 b	3.87 ± 0.12 b
	FP	40.4 ± 1.69 a	28.34 ± 1.81 a	5.41 ± 0.21 c	6.23 ± 0.12 b	4.26 ± 0.19 ab	4.83 ± 0.25 a	4.61 ± 0.03 a	5.04 ± 0.4 a
	RD	36.11 ± 1.72 a	27.37 ± 1.01 a	6.34 ± 0.36 bc	6.58 ± 0.07 ab	4.3 ± 0.04 ab	4.79 ± 0.14 a	4.98 ± 0.17 a	5.36 ± 0.15 a
	125RD	40.49 ± 4.35 a	28.91 ± 1.91 a	7.2 ± 0.52 ab	7.11 ± 0.18 a	4.84 ± 0.15 a	5.23 ± 0.24 a	4.99 ± 0.06 a	5.72 ± 0.07 a
CR	CL	15.67 ± 1.24 b	7.69 ± 0.39 b	3.62 ± 0.04 d	4.81 ± 0.37 c	3.59 ± 0.3 ab	3.53 ± 0.22 b	3.3 ± 0.17 b	3.98 ± 0.15 b
	FP	36.8 ± 0.64 a	28.83 ± 1.36 a	5.61 ± 0.11 c	6.27 ± 0.49 b	4.4 ± 0.23 ab	4.79 ± 0.22 a	4.78 ± 0.22 a	5.63 ± 0.21 a
	RD	33.05 ± 1.05 a	31.45 ± 0.65 a	6.26 ± 0.29 bc	6.94 ± 0.32 ab	4.21 ± 0.27 ab	4.94 ± 0.44 a	4.79 ± 0.06 a	5.4 ± 0.18 a
	125RD	39.34 ± 3.13 a	31.76 ± 1.91 a	7.59 ± 0.31 a	7.72 ± 0.38 a	4.39 ± 0.13 ab	5.31 ± 0.29 a	4.98 ± 0.18 a	5.85 ± 0.28 a
Statistics (p = 0.05)		7.58 (*)	8.5 (*)	0.97 (*)	1.59 (*)	1.87 (*)	1.16 (*)	0.45 (*)	0.82 (*)

In each column, the means ± standard error values denoted by the same letter are not significantly different at the p<0.05 level, *; significantly different at the p<0.05 level, **; significantly different at the p<0.01 level, ***; and significantly different at the p<0.001 level, ns; not significantly different. On the other hand, LSD value (p=0.05) assigned with asterisks represent the critical number that defines significant deference among the treatment combination

Table 6

The effect of crop residue, N fertilizer, and their interaction effect on Boro T. Aus, and T. Aman yield (t/ha) in Cumilla; maize and T. Aman yield (t/ha) in Mymensingh, 2020-21 & 2021-22
		Cumilla						Mymensingh
		Boro		T. Aus		T. Aman		Maize		T. Aman
		Grain Yield		Grain Yield		Grain Yield		Grain Yield		Grain Yield
Residue	Fertilizer	2020-21	2021-22	2020-21	2021-22	2020-21	2021-22	2020-21	2021-22	2020-21	2021-22
NR		6.08 ± 0.28	6.52 ± 0.34	3.36 ± 0.21	4.51 ± 0.24	4.54 ± 0.14	4.43 ± 0.14	8.59 ± 0.8	9.29 ± 1.23	4.37 ± 0.19	4.31 ± 0.29
CR		6.13 ± 0.3	6.87 ± 0.37	3.05 ± 0.14	4.55 ± 0.28	4.66 ± 0.17	4.79 ± 0.22	8.91 ± 0.87	9.73 ± 1.28	4.62 ± 0.22	4.61 ± 0.33
Statistics (p = 0.05)		ns	ns	ns	ns	ns	ns	ns	ns	ns	ns
	CL	4.73 ± 0.09 c	4.81 ± 0.06 c	2.4 ± 0.1 b	3.18 ± 0.08 c	3.76 ± 0.12 b	3.66 ± 0.16 c	4.24 ± 0.41 b	2.5 ± 0.31 b	3.57 ± 0.13 c	2.86 ± 0.1 c
	FP	6.15 ± 0.26 b	7.01 ± 0.15 b	3.35 ± 0.2 a	4.77 ± 0.22 b	4.73 ± 0.07 a	4.73 ± 0.09 b	10.36 ± 0.38 a	11.48 ± 0.71 a	4.52 ± 0.1 b	4.65 ± 0.22 b
	RD	6.35 ± 0.09 b	7.21 ± 0.28 ab	3.48 ± 0.22 a	4.85 ± 0.16 ab	4.88 ± 0.05 a	4.92 ± 0.09 ab	10.31 ± 0.49 a	12 ± 0.37 a	4.62 ± 0.1 b	4.82 ± 0.11 b
	125RD	7.18 ± 0.16 a	7.75 ± 0.12 a	3.58 ± 0.11 a	5.33 ± 0.09 a	5.02 ± 0.06 a	5.13 ± 0.19 a	10.1 ± 0.36 a	12.07 ± 0.27 a	5.28 ± 0.22 a	5.5 ± 0.17 a
Statistics (p = 0.05)		0.79 (***)	0.62 (***)	0.48 (***)	0.49 (***)	0.32 (***)	0.38 (***)	1.54 (***)	1.9 (***)	0.52 (***)	0.46 (***)
NR	CL	4.66 ± 0.12 c	4.78 ± 0.08 c	2.45 ± 0.2 d	3.29 ± 0.13	3.74 ± 0.06 c	3.65 ± 0.06 c	4.24 ± 0.64	2.5 ± 0.43 b	3.49 ± 0.23	2.78 ± 0.03
	FP	6.19 ± 0.42 a	6.83 ± 0.17 ab	3.38 ± 0.43 ab	4.9 ± 0.36	4.64 ± 0.03 ab	4.6 ± 0.12 ab	9.97 ± 0.58	10.95 ± 1.39 a	4.42 ± 0.19	4.42 ± 0.24
	RD	6.48 ± 0.08 a	6.84 ± 0.46 ab	3.88 ± 0.28 a	4.6 ± 0.2	4.81 ± 0.07 a	4.73 ± 0.01 ab	10.58 ± 0.5	11.68 ± 0.44 a	4.55 ± 0.02	4.68 ± 0.14
	125RD	6.97 ± 0.12 a	7.63 ± 0.23 a	3.73 ± 0.12 ab	5.27 ± 0.09	4.95 ± 0.03 a	4.75 ± 0.13 ab	9.57 ± 0.37	12.01 ± 0.3 a	5.02 ± 0.32	5.36 ± 0.07
CR	CL	4.81 ± 0.15 bc	4.83 ± 0.1 bc	2.35 ± 0.09 cd	3.07 ± 0.08	3.77 ± 0.26 bc	3.67 ± 0.35 bc	4.23 ± 0.66	2.5 ± 0.55 b	3.64 ± 0.17	2.94 ± 0.22
	FP	6.1 ± 0.41 ab	7.2 ± 0.21 a	3.33 ± 0.16 ab	4.64 ± 0.33	4.82 ± 0.12 a	4.87 ± 0.08 a	10.76 ± 0.47	12 ± 0.58 a	4.61 ± 0.04	4.89 ± 0.35
	RD	6.21 ± 0.12 a	7.58 ± 0.18 a	3.08 ± 0.12 bc	5.1 ± 0.15	4.95 ± 0.01 a	5.12 ± 0.03 a	10.05 ± 0.93	12.31 ± 0.61 a	4.69 ± 0.2	4.96 ± 0.15
	125RD	7.4 ± 0.25 a	7.87 ± 0.05 a	3.43 ± 0.15 ab	5.4 ± 0.17	5.09 ± 0.1 a	5.52 ± 0.14 a	10.62 ± 0.47	12.12 ± 0.51 a	5.54 ± 0.26	5.64 ± 0.35
Statistics (p = 0.05)		1.32 (*)	2.22 (*)	0.76 (*)	ns	0.88 (*)	1.08 (*)	ns	3.08 (*)	ns	ns

In each column, the means ± standard error values denoted by the same letter are not significantly different at the p<0.05 level, *; significantly different at the p<0.05 level, **; significantly different at the p<0.01 level, ***; and significantly different at the p<0.001 level, ns; not significantly different. On the other hand, LSD value (p=0.05) assigned with asterisks represent the critical number that defines significant deference among the treatment combination.

No competing interests reported.

Integrating nitrogen fertilization with crop residue management to improve nitrogen-use efficiency of crops

Status:

Version 1

Abstract

Figures

1. Introduction

2 Materials and methods

2.1 Experimental site description

2.2 Experimental design and crop management

2.3 Crop yield and N-use efficiency

2.4 N-use efficiency indices, N fertilization, and crop yield model to calculate N optimum

2.5 Soil analysis

2.6 Statistical Analysis

3. Results

3.1 Residue and N fertilization effects on crop yield

3.2 Residue and N fertilization effects on N-use efficiency of crops

3.3 Residue and N fertilization effects on sustainable N management index

3.4 N-use efficiency model comparisons among different crops

4. Discussion

4.1 Crop yield

4.2 N-use efficiency of crops

4.3 Sustainable N management index

5. Conclusions

Declarations

References

Tables

Additional Declarations

Status:

Version 1