Strategic scheduling of urea foliar application and irrigation for moth bean: a path to improve Productivity, profitability and quality in Western dry region of India

Abstract

In the western arid regions, where monsoon seasons often include regular and extended dry spells, agricultural practices need to be tailored to these challenging conditions. This research aimed to understand the effects of foliar urea application and different irrigation scheduling on crop productivity, profitability, and quality in arid region, and was conducted over two consecutive Kharif seasons of 2020 and 2021. The use of 2% urea at flowering + pod formation stages resulted in a notable improvement in yield parameters, number, weight, and buildup of dry matter. Improvement in these parameters led to significantly higher moth bean yield, by a margin of 20 – 22% as compared to other treatments. On the basis of pooled mean of two years, foliar spray of 2% urea at flowering + pod formation stages improved the protein content by 6 to 7%, protein productivity by 27–31%, physical water productivity by ∼20% and net monetary returns by 31–34% as compared to single foliar application. Similarly, irrigation at branching + pod formation stages registered higher growth parameters, grain yield (8%), profitability (13%), nutrient uptake, and residual soil fertility in moth bean as compared to other irrigation treatments. In conclusion, it is recommended that the application of urea (2%) by foliar spray at the flowering + pod formation stages and the modification of irrigation to the branching stage + pod formation stage, from the existing recommendation (flowering + pod formation), were more profitable and productive during early, prolonged dry spells with high temperatures, which are more typical in western dry regions for moth beans. Notably, it assists in fulfilling the protein needs of the vegetarian populace of western Rajasthan, India, where moth beans play a vital role in the diet.

Key words:

• Moth bean
• foliar application
• irrigation scheduling
• water productivity
• protein yield

Reviewing Editor:

• Manuel Tejada, Universidad de Sevilla, Spain

Subject:

• Botany
• Soil Sciences
• Agriculture & Environmental Sciences

1. Introduction

Moth bean (Vigna aconitifolia (Jacq.) Maréchal) is a versatile, minor legume crop that is native to the Indian subcontinent. This legume is known for its ability to thrive in arid conditions, making it a valuable crop in regions with limited rainfall and challenging farming environments. Its resilience has made it a staple in areas where water is scarce. With an average productivity of 346 kg per hectare, the moth bean was grown on 9.93 lakh hectares of land in India during the 2020–21 growing season, producing a total of 3.43 lakh tonnes (Kanishka et al., 2023). Moth bean is well known for its adaptation to rainfed conditions in arid and semi-arid regions because of its tolerance to drought and high temperatures. The plant is capable of producing a yield with as little as 50–60 mm of rainfall, spread over 3–4 showers during its growing period (Brink et al., 2006). The nutritional value of moth bean is noteworthy (20–24% protein), particularly in cereal-based vegetarian diets in developing countries (Takahashi et al., 2016). So, people mainly consume it in the arid and semi-arid regions of South Asian nations, with India being a prime example.

Moth bean productivity often falls short of its potential despite its resilience to adverse environments. This is due to inefficient agricultural methods and environmental limitations. There are numerous challenges hindering the cultivation of moth bean in the western part of India. The dominant challenge in this region is the scarcity of water, which is exacerbated by its semiarid climate (Morante-Carballo et al., 2022). Additional factors that worsen these problems include temperature oscillations, erratic rainfall, and limited access to modern agricultural practices. These effects lower the yield and, as a result, have an impact on farmers’ profitability. Addressing these challenges requires innovative and sustainable agricultural practices.

In leguminous crops, the degeneration of root nodules, which are responsible for biological nitrogen fixation, commences after the flowering stage. This degeneration leads to a decline in active nodulation and the process of biological nitrogen fixation, consequently resulting in reduced productivity (Ali et al., 2016). The foliar fertilization with urea spray during the reproductive stages of pulses is a cost-effective strategy to enhance plant nitrogen uptake, prolong green leaf area duration, increase photosynthetic efficiency, and ultimately improve grain yield and protein content, especially in nutrient-deficient sandy soils (Gupta et al., 2011). Urea, a widely utilized nitrogen fertilizer, exhibits a desirable characteristic of rapid foliar penetration and subsequent translocation to the cytosol (Witte et al., 2002). Therefore, applying urea as a foliar spray during the reproductive growth stages of crops can enhance both crop productivity and quality.

The crop severely affected by the low and sporadic rainfall, which resulted in prolonged dry spells of 30–35 days, accompanied by high temperatures exceeding 40 °C. These conditions significantly reduced crop productivity, falling below its potential (<200 kg ha⁻¹). The crop is especially prone to water stress during the flowering and pod development stages (Halder et al., 2021). Water stress ultimately leads to the cessation of growth, desiccation, or the demise of crops during their active development phase, as it inhibits photosynthesis, nutrient uptake, root nodulation and other physiochemical processes (Barnabás et al., 2008) resulting a lower yield. Implementing efficient irrigation strategies has become imperative to enhance crop yields and promote resilience to drought conditions. The ideal scheduling of irrigation enhances crop yield through the efficient utilization of irrigation water at the most critical stages under water stress conditions, which depends on the soil, climate, and plant characteristics (Kadasiddappa et al., 2017).

Previous research studies have demonstrated the beneficial effects of foliar urea (nitrogen) application on various pulse crops, including cow pea (Bute et al., 2019), lentil (Ram et al., 2018), green gram (Muthal et al., 2016), and chickpea (Dewangan et al., 2017) under rainfed conditions. Additionally, appropriate irrigation scheduling has been shown to have a positive impact on the performance of black gram (Lakshmi et al., 2018), green gram (Malik et al., 2006), and cowpea (Patidar et al., 2015). However, the effects of foliar application of urea and irrigation scheduling on moth bean have not been extensively investigated and are not clearly understood.

Therefore, we hypothesized that supplementing basal nitrogen fertilization with foliar urea application and optimizing irrigation scheduling would mitigate the adverse effects of early-season drought stress, thereby improving moth bean productivity and profitability and fulfilling the protein requirements of farmers in the western arid region of India.

2. Materials and methods

2.1. Experimental site and Weather description

A two-year field experiment was conducted during the consecutive kharif seasons of 2020 and 2021 at the experimental farm of the ICAR-Indian Institute of Pulses Research, located at the Regional Research Center in Bikaner, Rajasthan, India (28.07° N, 73.32° E, 245 m altitude). The dominant physical and chemical properties of the soil in the experimental fields are summarized in Table 1. The soil was loamy sand in texture, with low available soil nitrogen (89 kg ha⁻¹), medium phosphorous (16.5 kg ha⁻¹), and potassium (190 kg ha⁻¹). The soil electrical conductivity, pH, and organic matter were 0.24 dS m⁻¹, 8.3, and 0.10%, respectively.

Table 1. Physico-chemical properties of the study site.

Parameters	Values	Method
pH(1:2)	8.30	Glass electrode pH meter method (Richards, 1954)
EC (1:2) (dS m^−1)	0.24	Conductivity bridge method (Richards, 1954)
SOC (%)	0.10	Wet digestion method (Walkley & Black 1934)
Available N (kg ha^−1)	89.0	Alkaline permanganate method (Subbiah & Asija, 1956)
Available P (kg ha^−1)	16.5	Olsen’s method (Olsen et al., 1954)
Available K (kg ha^−1)	190	Flame photometric method (Jackson, 1973)
Sand (%)	87.9	International pipette method (Piper, 1966)
Silt (%)	7.5
Clay (%)	4.6
Soil type	Loamy sand
Bulk density (g cm^−3)	1.54	Core sampling (Chopra & Kanwar, 1976)

The experimental site experiences a hot and arid climate, with the peak temperature reaching 46 °C in May and the lowest temperature dropping to 2.2 °C in January. The average annual precipitation of the region is 286 mm, of which 63% is recorded from July–September.

2.2. Experimental design and field implementation

This experiment was laid out in a factorial randomized complete block design with three nitrogen management practices (N₁: Foliar spray of urea (2%) at the flowering stage, N₂: Foliar spray of urea (2%) at the pod formation stage, and N₃: Foliar spray of urea (2%) at the flowering and pod formation stages) and three irrigation scheduling strategies (I₁: Vegetative/branching stage, I₂: Vegetative/branching + pod formation stage, and I₃: Flowering stage + pod formation stage) comprising nine treatment combinations with a gross plot size of 5.4 m x 6 m and three replications for each treatment, the total gross plot area was 32.4 m². The net plot size was decreased to 16.8 m² (4.2 m x 4 m) for observational purposes. Foliar applications of a 2% urea solution (46% nitrogen) were applied during the flowering (BBCH-61) and pod formation (BBCH-72) stages. Each application utilized 400 liters of water per hectare, resulting in a urea usage rate of 8 kg ha⁻¹ spray⁻¹.

To reduce the lateral movement of water, a one-meter buffer strip was used to divide the experimental unit. Using the surface flood irrigation approach, each experimental unit received irrigation through a 75 mm PVC pipeline that was directly connected through a tubewell outlet. For each irrigation, a fixed depth of 60 mm irrigation water was applied to the plot. The water discharge rate of the tube well was determined for each irrigation using the direct flow measurement method. This involved placing a container of known volume (100 liters) at the entry point of the experimental field below the pipe and then measuring the time it took to fill the container. We followed the method of Ali (2010) to determine the irrigation time. The amount of time required to apply irrigation water to each experimental plot for a depth of 60 mm was determined using the formula (1) $$\begin{array}{c}\text{Time\hspace{0.17em}of\hspace{0.17em}irrigation\hspace{0.17em}}\left(t\right)=\text{Gross\hspace{0.17em}irrigation\hspace{0.17em}requirment\hspace{0.17em}}\left(\text{GIR}\right)\\ \frac{\text{Aarea\hspace{0.17em}of\hspace{0.17em}the\hspace{0.17em}plot\hspace{0.17em}}\left(m^2\right)\left(A\right)}{\text{Inflow\hspace{0.17em}rate\hspace{0.17em}of\hspace{0.17em}water\hspace{0.17em}}\left(\text{lit\hspace{0.17em}per\hspace{0.17em}sec}\right)\left(Q\right)\text{\hspace{0.17em}X\hspace{0.17em}}60}\end{array}$$(1)

2.3. Crop management

After receiving a sufficient amount of rain, the field was prepared with one harrowing, followed by one cultivator operation and planking. The moth bean crop variety RMO-2251 was sown on 8 August and 20 July 2020, and 2021, respectively. The crop was planted using the Kera method with a row spacing of 30 cm and a seed rate of 15 kg ha⁻¹. Seeds were treated with 2 g thiram + 1 g carbendazim/kg seed to control fungal diseases. Prior to sowing, the recommended dose of mineral nitrogenous and phosphatic fertilizers was applied as a basal application using di-ammonium phosphate at a rate of 86 kg ha⁻¹, which supplies 15 kg N ha⁻¹ and 40 kg P₂O₅ ha⁻¹.

2.4. Sampling and measurements

2.4.1. Crop growth, yield components and yields

At physiological maturity, five plants were randomly selected from each net plot and cut close to the ground. To calculate the buildup of dry matter, samples were weighed after being dried at 65 °C. The average number of primary branches per plant was determined by counting the number of branches on each of the five plants, the average number of primary branches per plant was determined. The mean value was used as a representative value. Five randomly chosen plants were observed to have their root nodules weighed and counted at the flowering stage. The nodules were weighed on a precision scale with a sensitivity of 0.01 g to ascertain their dry weight after being dried for 48 h at 65 °C. At a moisture content of 10%, the grain yield was calculated and expressed as kg ha⁻¹. The biological yield, which was expressed in kg ha⁻¹, was obtained from the net plot’s whole aboveground vegetation. The protein content of seeds was determined using the Kjeldahl method, which involves measuring the nitrogen concentration and multiplying it by 6.25. Grain protein yield was calculated by multiplying the grain protein content by the grain yield (kg ha⁻¹).

2.4.2. Water productivity

Physical water productivity (PWP_IR+P) and economic water productivity (EWP_IR+P) in terms of the applied irrigation water (IR) and precipitation (P) were determined (Frizzone et al., 2021) using the following equations: (2) $${\mathrm{\text{PWP}}}_{(\mathrm{\text{IR}}+\mathrm{P})}=\frac{\text{Crop marketable yield}(\mathrm{\text{Grain}}+\mathrm{\text{Haulm}})\left(\mathrm{\text{kg}}\mathrm{ }{\mathrm{\text{ha}}}^{-1}\right)}{\text{Total water use}(\mathrm{\text{IR}}+\mathrm{P})\left({\mathrm{m}}^3\mathrm{ }{\mathrm{\text{ha}}}^{-1}\right)}$$(2) (3) $${\mathrm{\text{EWP}}}_{(\mathrm{\text{IR}}+\mathrm{P})}=\frac{\text{Gross returns}\left(\mathrm{₹}\mathrm{ }{\mathrm{\text{ha}}}^{-1}\right)}{\text{Total water use}(\mathrm{\text{IR}}+\mathrm{P})\left({\mathrm{m}}^3\mathrm{ }{\mathrm{\text{ha}}}^{-1}\right)}$$(3)

2.4.3. Economics

The economic analysis for each treatment in the experiment was carried out separately while considering the current prices of all relevant inputs. Gross returns were calculated based on the five-year average price of moth bean in the agricultural market. The net return (₹ ha⁻¹) was calculated by deducting the production cost from the gross return, as shown in Eq. (4) $$\begin{array}{l}\text{Net\hspace{0.17em}retun\hspace{0.17em}}\left(�\hspace{0.17em}{\text{ha}}^{-1}\right)=\\ \text{Gross\hspace{0.17em}return\hspace{0.17em}}\left(�\hspace{0.17em}{\text{ha}}^{-1}\right)-\text{\hspace{0.17em}Cost\hspace{0.17em}of\hspace{0.17em}production\hspace{0.17em}}\left(�\hspace{0.17em}{\text{ha}}^{-1}\right)\end{array}$$(4)

The benefit-to-cost (B:C ratio) was determined using Eq. (5) $$\mathrm{B}:\text{C ratio}=\frac{\text{Net return}\left(\mathrm{₹}\mathrm{ }{\mathrm{\text{ha}}}^{-1}\right)}{\text{Cost of cultivation}\left(\mathrm{₹}\mathrm{ }{\mathrm{\text{ha}}}^{-1}\right)}$$(5)

The daily production capacity of a specific treatment, referred to as production efficiency (PE), was measured in kilograms per hectare per day (kg ha⁻¹ day⁻¹) and was calculated using the following formula: (6) $$\mathrm{\text{PE}}\mathrm{ }\left(\mathrm{\text{kg}}\mathrm{ }{\mathrm{\text{ha}}}^{-1}\mathrm{ }{\mathrm{\text{day}}}^{-1}\right)=\frac{\text{Total grain yield}\left(\mathrm{\text{kg}}\mathrm{ }{\mathrm{\text{ha}}}^{-1}\right)}{\text{Cropping period}\left(\mathrm{\text{Days}}\right)}$$(6)

Monetary efficiency (ME) is a measure of the daily economic return capacity for each treatment, and is expressed in units of ₹ ha⁻¹ day⁻¹. This value was calculated using the following equation: (7) $$\mathrm{\text{ME}}\mathrm{ }\left(\mathrm{₹} {\mathrm{\text{ha}}}^{-1}\mathrm{ }{\mathrm{\text{day}}}^{-1}\right)=\frac{\text{Total net returns}\left(\mathrm{₹}\mathrm{ }{\mathrm{\text{ha}}}^{-1}\right)}{\text{Croping period}\left(\mathrm{\text{Days}}\right)}$$(7)

2.4.4. Nutrient uptake and available nutrients

Soil and plant samples were collected each year at the time of harvest. Soil samples were dried in the shade and prepared for laboratory analysis using the methods outlined in Table 1. The plant samples were dried in an oven, ground, and subsequently analyzed for nutrient content. The nutrient uptake of both the grain and haulm was determined by multiplying their respective yields by their nutrient contents. The amount of nutrients taken up by both grains and haulm was combined to calculate the total nutrient uptake (TNU), which was then expressed in kilograms per hectare.

2.5. Statistical analyses

Using JMP^® version 16.0 for factorial design, the analysis of variance (ANOVA) approach was used to analyze the data acquired for different parameters. The significance of the treatment effect was assessed using the F-test, and mean comparisons were carried out at the 5% significance level using the least significant difference (LSD). Correlation analysis was carried out using the GGally package within the R programming environment.

3. Results

3.1. Weather during the crop growing season

The weather data for both study years, including air temperature, rainfall, evaporation, relative humidity, and the number of rainy days during crop growth seasons were obtained from an automatic weather station 200 m away from the study location, as shown in Figure 1. The average temperatures for the moth bean growing seasons in 2020 (August to October) and 2021 (July to September) were 31.2 °C and 31.6 °C, respectively, while the total rainfall was 114.5 mm and 225.4 mm. Although the rainfall received during the crop period (from sowing to harvest) was 90 mm in 2020, it increased to 120 mm in 2021. During the first year of the study, there were fewer rainy days at the branching stage and no rainfall was recorded from the flowering to maturity stages. However, excessive rainfall was observed during the flowering to maturity stage in the second year.

Figure 1. Weekly mean maximum and minimum temperatures, cumulative weekly rainfall and evaporation, mean weekly relative humidity, and cumulative weekly number of rainy days. (A) 2020 and (B) 2021 during the moth bean growing season at the experimental site.

3.2. Growth parameters and yield

The growth parameters and yield of moth bean are listed in Table 2. Upon perusal of the data, it was found that the analysis of variance revealed significant differences in the timing of the urea foliar spray and irrigation scheduling for all parameters studied, except for dry matter accumulation at physiological maturity. Variations from year to year had a major impact on the amount of dry matter accumulated at physiological maturity and on the number of branches per plant. The analysis of variance indicated non-significant interaction effects between urea foliar spray (N) × irrigation scheduling (I) and year (Y) for all measured attributes (Table 2). This result implies that the effects of irrigation scheduling and urea foliar spray application were independent and did not influence each other.

Table 2. Effect of urea foliar application and irrigation scheduling on growth parameters and yields of moth bean (pooled of two years, 2020 and 2021).

Treatments	Dry matter accumulation (g plant^−1)	No. of branches plant^−1	No. of nodules plant^−1	Nodule weight plant^−1	Grain yield (kg ha^−1)	Biological yield (kg ha^−1)
Urea foliar application (N)
N1	8.59 ± 0.27b	5.72 ± 0.42b	23.09 ± 1.84	81.84 ± 1.96b	727 ± 33.74b	2673 ± 105.11b
N2	8.6 ± 0.42b	5.49 ± 0.51b	23.48 ± 1.58	81.51 ± 3.14b	739 ± 41.12b	2754 ± 184.01b
N3	9.83 ± 0.29a	6.84 ± 0.46a	25.57 ± 1.35	92.22 ± 1.81a	887 ± 50.41a	3336 ± 207.71a
Irrigation scheduling (I)
I1	8.5 ± 0.41b	4.85 ± 0.41b	20.6 ± 1.58b	76.69 ± 2.35b	635 ± 31.73b	2354 ± 115.49b
I2	9.07 ± 0.30a	6.67 ± 0.42a	26.91 ± 1.66a	91.08 ± 1.68a	891 ± 39.75a	3307 ± 173.88a
I3	9.47 ± 0.33a	6.53 ± 0.5a	24.62 ± 1.19ab	87.8 ± 2.53a	827 ± 40.47a	3102 ± 174.04a
Years (Y)
2020	9.45 ± 0.32a	5.49 ± 0.35b	25.04 ± 1.44	87.14 ± 2.25	792 ± 42.25	3025 ± 183.61
2021	8.57 ± 0.24b	6.54 ± 0.41a	23.05 ± 1.14	83.24 ± 1.99	776 ± 30.95	2817 ± 102.66
Anova
Y	0.0109	0.0033	0.2902	0.0743	0.648	0.1676
N	0.0045	0.0043	0.5071	0.0002	0.0011	0.0015
I	0.044	<0.0001	0.0285	<0.0001	<0.0001	<0.0001
N × I	0.3507	0.0765	0.2681	0.0824	0.1456	0.0608
Y × N × I	0.6816	0.0809	0.659	0.5484	0.0818	0.0722

N₁: Foliar spray of urea (2%) at the flowering stage, N₂: Foliar spray of urea (2%) at the pod formation stage, N₃: Foliar spray of urea (2%) at the flowering and pod formation stages, I₁: Vegetative/branching stage, I₂: Vegetative/branching + pod formation stage, I₃: Flowering stage + pod formation stage. LSD post hoc test was applied, and the use of similar lowercase letters within a column signifies that there is no statistically significant difference at the 0.05 level of probability.

The data pooled over two years (2020 and 2021) revealed that the foliar spray of urea at the flowering and pod formation stage (N₃) recorded a significantly higher dry matter accumulation per plant (9.83 g), branches per plant (6.84), and nodule weight (92.22 g), which were 14.3%, 22.0%, and 13.0% higher, respectively, than the individual applications of urea foliar spray (N₁ and N₂). Irrigation scheduling at the branching and pod formation stage (I₂) resulted in higher values of branches (6.67), number of nodules (26.91), and nodule weight per plant (91.08 g), which was on par with irrigation at the flowering and pod formation stage (I₃) and significantly greater with single irrigation at the branching stage (I₁). The increments in growth parameters were 37.6%, 30.6%, and 18.8% for branches, number of nodules, and nodule weight per plant, respectively, compared to I₁.

Foliar application of 2% urea at the flowering + pod formation stage had a positive effect on growth parameters, eventually enhancing moth bean grain and biological yield. Higher grain (887 kg ha⁻¹) and biological yield (3336 kg ha⁻¹) were recorded with the application of 2% urea at the flowering and pod formation stage (N₃) compared to the single application (N₁ and N₂). The increases in grain and biological yields were 22.0% and 24.8%, respectively, compared to individual applications (N₁ and N₂). However, N₂ was found at par with N₁ with respect to grain and biological yield. In the context of irrigation scheduling, I₂, considered on par with I₃, showed notable advancements in both grain (891 kg ha⁻¹) and biological yield (3307 kg ha⁻¹) compared with I₁. Specifically, the grain and biological yields increased substantially, registering significant improvements of 30.2% and 40.5%, respectively, over the values observed under I₁.

3.3. Economics

The highest cost of production among foliar applications of urea and irrigation scheduling practices was under N₃ (₹ 18,572) and I₂ (₹ 18,374), respectively (Table 3). The highest net return (₹ 30,026) and B:C (1.61) ratio were recorded with the dual application of foliar urea spray (N₃), followed by the application of urea alone (N₁ and N₂). There was a monetary benefit of ₹ 7946 with the double application of urea foliar spray in moth bean compared to one foliar spray (N₁ and N₂). Similarly, the highest monetary efficiency (484.3 ₹ ha⁻¹day⁻¹) was recorded under N₃. With respect to irrigation scheduling, I₂ at par with I₃ gave the highest net returns (₹ 30,249) and B:C (1.64) ratio compared to I₁. The net returns under I₂ increased by ₹ 13,187 over I₁. A higher monetary efficiency (487.89 ₹ ha⁻¹day⁻¹) was recorded with I₂ as compared to I₁. I₂ recorded a substantial increase in monetary efficiency, a noteworthy 77.3% increase compared with I₁.

Table 3. Effect of foliar application of urea and irrigation scheduling on the economics of moth bean (pooled of two years, 2020 and 2021).

Treatments	Cost of Production (₹ ha^−1)	Net Return (₹ ha^−1)	B:C ratio	Monetary Efficiency (₹ ha^−1 day^−1)
Urea foliar application (N)
N1	17925	21722 ± 1763.31b	1.21 ± 0.10b	350.36 ± 28.44b
N2	17925	22438 ± 2193.4b	1.25 ± 0.12b	361.91 ± 35.38b
N3	18572	30026 ± 2713.42a	1.61 ± 0.14a	484.30 ± 43.76a
Irrigation scheduling (I)
I1	17674	17062 ± 1739.32b	0.96 ± 0.10b	275.19 ± 28.05b
I2	18374	30249 ± 2119.31a	1.64 ± 0.11a	487.89 ± 34.18a
I3	18374	26876 ± 2176.11a	1.46 ± 0.12a	433.48 ± 35.10a
Years (Y)
2020	17801	24559 ± 2262.32	1.37 ± 0.12	396.12 ± 36.49
2021	18481	24898 ± 1620.92	1.34 ± 0.08	401.59 ± 26.14
Anova
Y	–	0.8624	0.7776	0.8624
N	–	0.0021	0.008	0.0021
I	–	<0.0001	<0.0001	<0.0001
N × I	–	0.1182	0.1307	0.1182
Y × N × I	–	0.0172	0.0143	0.0172

N₁: Foliar spray of urea (2%) at the flowering stage, N₂: Foliar spray of urea (2%) at the pod formation stage, N₃: Foliar spray of urea (2%) at the flowering and pod formation stages, I₁: Vegetative/branching stage, I₂: Vegetative/branching + pod formation stage, I₃: Flowering stage + pod formation stage. LSD post hoc test was applied, and the use of similar lowercase letters within a column signifies that there is no statistically significant difference at the 0.05 level of probability.

3.4. Protein content and protein yield

Both urea foliar spray and irrigation scheduling practices significantly influenced the protein content and productivity, as illustrated in Figure 2. The dual foliar application of urea at the branching + pod formation stage significantly increased protein content (21.7%) and productivity (192.99 kg ha⁻¹). This increase in protein content and productivity was 7.7% and 31.3%, respectively, compared with those of N₁. Irrigation scheduling at the branching and pod formation stages significantly enhanced protein content by 7.4% and productivity by 52.0% compared to single irrigation at the branching stage.

Figure 2. Effect of foliar application of urea and irrigation scheduling on protein content (A) and protein yield (B) pooled of two years (2020 & 2021).

N₁: Foliar spray of urea (2%) at the flowering stage, N₂: Foliar spray of urea (2%) at the pod formation stage, N₃: Foliar spray of urea (2%) at the flowering and pod formation stages, I₁: Vegetative/branching stage, I₂: Vegetative/branching + pod formation stage, I₃: Flowering stage + pod formation stage. LSD post hoc test was applied, and the use of similar lowercase letters within a column signifies that there is no statistically significant difference at the 0.05 level of probability.

3.5. Input use efficiency

3.5.1. Production efficiency

Production efficiency was notably influenced by the foliar application of urea and irrigation scheduling. Among the foliar applications of urea, N₃ resulted in the highest production efficiency with a remarkable output of 14.3 kg ha⁻¹ day⁻¹, outperforming N₁ and N₂. Regarding irrigation management strategies, higher production efficiency was observed with I₂, recording an impressive 14.4 kg ha⁻¹ day⁻¹, which was on par with I₃. Conversely, the lowest production efficiency was observed for I₁ (Table 4).

Table 4. Effect of foliar application of urea and irrigation scheduling on applied irrigation water (IW), physical (PWP_IR+R) and (EWP_IR+R) economic water productivity of moth bean (pooled of two years, 2020 and 2021).

Treatments	Production efficiency (kg ha^−1 day^−1)	Applied irrigation water (IW) (mm)	Physical water productivity (PWPIR+R) (kg m^−3)	Economic water Productivity (EWPIR+R) (₹ m^−3)
Urea foliar application (N)
N1	11.72 ± 0.54b	100	1.34 ± 1.02b	19.67 ± 0.08b
N2	11.92 ± 0.66b	100	1.35 ± 0.08b	19.76 ± 0.92b
N3	14.30 ± 0.81a	100	1.62 ± 0.08a	23.59 ± 0.98a
Irrigation scheduling (I)
I1	10.25 ± 0.51b	60	1.43 ± 0.07	21.10 ± 1.04
I2	14.37 ± 1.07a	120	1.48 ± 0.09	21.73 ± 0.64
I3	13.33 ± 0.65a	120	1.39 ± 0.09	20.19 ± 1.06
Years (Y)
2020	12.78 ± 0.68	100	1.58 ± 0.07a	22.23 ± 0.97a
2021	12.52 ± 0.50	100	1.29 ± 0.04b	19.79 ± 0.67b
Anova
Y	0.6480	–	0.0003	0.0154
N	0.0011	–	0.0044	0.0024
I	<0.0001	–	0.5908	0.4296
N × I	0.1456	–	0.0331	0.1060
Y × N × I	0.0618	–	0.0946	0.0672

Effective rainfall of the cropping period was 105 mm (mean of the two years) N₁: Foliar spray of urea (2%) at the flowering stage, N₂: Foliar spray of urea (2%) at the pod formation stage, N₃: Foliar spray of urea (2%) at the flowering and pod formation stages, I₁: Vegetative/branching stage, I₂: Vegetative/branching + pod formation stage, I₃: Flowering stage + pod formation stage. LSD post hoc test was applied, and the use of similar lowercase letters within a column signifies that there is no statistically significant difference at the 0.05 level of probability.

3.5.2. Physical and economic water productivity

A total of 60 mm of irrigation water was applied in treatment I₁, while treatments I₂ and I₃ received a total of 120 mm. This represents a 50% reduction in irrigation water usage for treatments I₂ and I₃. During the crop period, a total of 105 mm of effective rainfall was recorded (mean data over two years). Physical (PWP_IR+R) and economic water productivity (EWP_IR+R) were significantly influenced by the foliar application of urea. However, irrigation scheduling practices had identical effects on physical and economic water productivity (Table 4). The highest productivity of water, both physical (1.62 kg m⁻³) and economic (23.59 ₹ m⁻³), was observed in N₃. Physical and economic water productivity were higher by 20.9% and 20.3%, respectively, over N₁ on a pooled basis of two years (Table 4). Irrigation practices failed to create significant variations in physical and economic water productivity. However, numerically higher water productivity was observed under the I₂ treatment.

3.6. Nutrient uptake

The N, P, and K uptake (grain, haulm, and total) was significantly influenced by foliar application of urea and irrigation scheduling (Figure 3). The highest N, P and K uptake by grain (24.29, 3.35 and 2.22 kg N, P and K ha⁻¹, respectively), haulm (38.19, 5.16 and 14.12 kg N, P and K ha⁻¹, respectively), and total NPK uptake (62.48, 8.51 and 16.35 kg N, P and K ha⁻¹, respectively) by moth bean was registered under N₃ and it was found at par with N₁ and N₂. In relation to the scheduling of irrigation, the highest N, P and K uptake by grain (30.99, 4.33 and 2.94 kg ha⁻¹, respectively), haulm (47.85, 6.44 and 17.93 kg ha⁻¹, respectively) and total N, P and K uptake (78.84, 10.77 and 20.87 kg ha⁻¹, respectively) were under I₂ being at par with I₃ except N and P uptake by grain. The total N, P, and K uptake by moth bean with N₃ increased by 33.5%, 57.4%, and 39.7%, respectively, over N₁. Moreover, under I₂, total N, P, and K uptake by moth bean was higher by 50.4%, 60.5%, and 54.1%, respectively, than I₁.

Figure 3. Effect of foliar application of urea and irrigation scheduling on N uptake by grain, haulm, and total N uptake (A); P uptake by grain, haulm, and total P uptake (B); and K uptake by grain, haulm, and total K uptake (C) pooled for two years (2020 and 2021).

N₁: Foliar spray of urea (2%) at the flowering stage, N₂: Foliar spray of urea (2%) at the pod formation stage, N₃: Foliar spray of urea (2%) at the flowering and pod formation stages, I₁: Vegetative/branching stage, I₂: Vegetative/branching + pod formation stage, I₃: Flowering stage + pod formation stage. LSD post hoc test was applied, and the use of similar lowercase letters within a column signifies that there is no statistically significant difference at the 0.05 level of probability.

3.7. Available nutrients and organic carbon in soil

The availability of nitrogen (N), phosphorus (P), and potassium (K) was notably influenced by foliar application of urea and irrigation scheduling practices. However, these two factors did not significantly affect the soil organic carbon content (Table 5). The data pooled over two years, 2020 and 2021, revealed that the foliar spray of urea at the flowering and pod formation stage (N₃) recorded a significant increase in available N (99.73 kg ha⁻¹), P (19.25 kg ha⁻¹), and K (213.54 kg ha⁻¹), and the improvement in these parameters was 8.6%, 12.2%, and 11.0%, respectively, compared to N₁. Similarly, irrigation scheduling at I₂ and I₃ had identical effects on available N, P, and K, but significantly higher values of these soil parameters were observed compared to I₁.

Table 5. Effect of foliar application of urea and irrigation scheduling on organic carbon and available soil nutrients of moth bean (pooled of two years, 2020 and 2021).

Treatments	Organic Carbon (%)	Available N (kg ha^−1)	Available P (kg ha^−1)	Available K (kg ha^−1)
Urea foliar application (N)
N1	0.11 ± 0.00	91.8 ± 1.67b	17.16 ± 0.40b	192.26 ± 1.31b
N2	0.12 ± 0.01	97.65 ± 1.11a	17.35 ± 0.22b	194.81 ± 1.72b
N3	0.12 ± 0	99.73 ± 1.72a	19.25 ± 0.33a	213.54 ± 0.94a
Irrigation scheduling (I)
I1	0.11 ± 0.01	90.5 ± 1.59b	17.07 ± 0.30b	196.46 ± 2.80b
I2	0.12 ± 0.00	99.54 ± 1.28a	18.07 ± 0.36a	201.59 ± 2.39a
I3	0.12 ± 0.00	99.14 ± 1.31a	18.63 ± 0.43a	202.57 ± 2.57a
Years (Y)
2020	0.11 ± 0.00	95.75 ± 1.47	17.76 ± 0.38	199.08 ± 2.00
2021	0.12 ± 0.00	97.04 ± 1.31	18.08 ± 0.24	201.33 ± 2.29
Anova
Y	0.0539	0.2441	0.1714	0.0612
N	0.2481	<0.0001	<0.0001	<0.0001
I	0.5093	<0.0001	<0.0001	0.0003
N × I	0.1105	0.0021	0.0006	0.0364
Y × N × I	0.5223	0.8472	0.0616	0.1299

N₁: Foliar spray of urea (2%) at the flowering stage, N₂: Foliar spray of urea (2%) at the pod formation stage, N₃: Foliar spray of urea (2%) at the flowering and pod formation stages, I₁: Vegetative/branching stage, I₂: Vegetative/branching + pod formation stage, I₃: Flowering stage + pod formation stage. LSD post hoc test was applied, and the use of similar lowercase letters within a column signifies that there is no statistically significant difference at the 0.05 level of probability.

However, the year had no significant effect on available N, P, and K, but the interaction between foliar application of urea and irrigation scheduling (N × I) was significant, highlighting that the combined effects of these factors can further influence available N, P, and K content. Conversely, the three-way interaction (Y × N × I) did not significantly affect the availability of these nutrients in soil.

3.7. Correlation studies

To investigate the associations between different parameters in moth bean, correlation analysis was performed, and the resulting estimates are displayed in Table 6. The Pearson’s correlation matrix elucidates significant associations among the variables.

Table 6. Correlation coefficients among various growth, yield, and water productivity parameters of the moth bean crop.

Variables	Dry matter accumulation	No. of branches plant^−1	No. of nodules plant^−1	Nodule weight plant^−1	Grain yield	Biological yield	Physical water productivity	Economic water Productivity
Dry matter accumulation	1	0.15	0.25	0.48***	0.22	0.24	0.19	0.15
No. of branches plant^−1		1	0.2	0.42**	0.41**	0.34*	0.08	0.15
No. of nodules plant^−1			1	0.26	0.2	0.17	0	0
Nodule weight plant^−1				1	0.61***	0.59***	0.38**	0.38**
Grain yield					1	0.96***	0.73***	0.79***
Biological yield						1	0.81***	0.80***
Physical water productivity							1	0.96***
Economic water Productivity								1

Dry matter accumulation exhibits a moderate positive correlation with nodule weight plant⁻¹ (r = 0.48, p < 0.001), while branches plant⁻¹ demonstrates comparable correlations with nodule weight plant⁻ (r = 0.42, p < 0.01) and grain yield (r = 0.41, p < 0.01). nodule weight plant⁻¹ displays strong positive correlations with grain yield (r = 0.61, p < 0.001), biological yield (r = 0.59, p < 0.001), and moderate correlations with physical water productivity (r = 0.38, p < 0.01) and economic water Productivity (r = 0.38, p < 0.01). Grain yield, biological yield, physical water Productivity, and economic water Productivity are highly intercorrelated, with very strong positive correlations ranging from r = 0.73 to r = 0.96 (p < 0.001), indicating that these yield and biomass measures are closely associated.

4. Discussion

The moth bean is a short-duration leguminous crop that is predominantly cultivated in arid regions with marginal soil conditions. Throughout its growth stages, the crop encounters stresses associated with nutrient and moisture availability. Consequently, judicious input management is imperative for attaining satisfactory yields under arid environments (Singh et al., 2015). A significant reduction in root activity during the reproductive phase is identified as one of the contributing factors to lower productivity in moth bean under arid conditions. This phenomenon leads to the remobilization of nutrients from the leaves and pods to the developing grains, thereby depriving the leaves of adequate nutrition for various metabolic processes and stress responses. The situation is further exacerbated by the lack of precipitation in the region. Nutrient deficiency eventually manifests as leaf yellowing, leading to diminished photosynthetic capacity and subsequent reductions in grain yield (Panwar et al., 2018). Therefore, to sustain moth bean grain yield in arid regions, the implementation of foliar urea sprays and optimized irrigation scheduling is deemed essential.

The growth parameters of moth bean, viz. dry matter accumulation plant⁻¹, branches plant⁻¹, and nodule weight plant⁻¹, increased with N₃ owing to an adequate supply of nitrogen as a basal application and spraying of urea twice at the flowering and pod formation stages. At the reproductive stage, the nodules responsible for nitrogen fixation begin to degrade, leading to a decrease in nitrogen fixation. However, the plant’s demand for nitrogen increases during the seed development phase. According to Da-Silva et al. (1993), the application of nitrogen at later stages of crop growth can enhance the activity and biomass of existing nodules. This could potentially explain the higher nodule weight observed when urea was applied as a foliar spray during the flowering and pod formation stages. Growth parameter enhancement can be attributed to the supplementary supply of nitrogen via foliar application, which could have elevated nutrient absorption and movement within the plant (Niu et al., 2021). The application of foliar spray is an effective method to supplement and improve the nutritional status of plants, as the absorption of nutrients through leaves is noticeably faster than through the roots (Niu et al., 2021). Drought stress leads to a significant decrease in leaf chlorophyll content, which negatively affects the photosynthetic efficiency of plants, decreases dry matter accumulation, and ultimately results in low grain yield (Wang et al., 2017). In this study, we found that there was a substantial increase (p < 0.05) in plant biomass per plant, number of branches per plant, nodule weight per plant, number of pods per plant, biomass, and grain yield when two foliar applications of urea were used instead of a single application. These findings are in close agreement with those reported by Sanjida et al. (2023) in mung bean crop. The application of urea to the leaves may have resulted in increased chlorophyll content, which in turn allows for more photosynthesis, particularly under stressful conditions (Arabzadeh, 2013).

Similarly, N₃ produced significantly higher grain and biological yields than N₂ and N₁. The application of nitrogen as a basal and urea spray (2%) twice during the flowering and pod formation stages resulted in increased grain yield, potentially because of the high leaf penetration rate of urea, which is quickly absorbed and hydrolyzed by most plants in the cytosol (Witte et al., 2002). The application of urea to the leaves during the flowering and pod formation stages could have enhanced the nitrogen levels in photosynthesizing leaves and revitalized photosynthesis, ultimately leading to a higher yield (Singh et al., 2022).

Drought events are common and frequent in arid regions and the monsoon season has a small number of rainy days (Majumdar et al., 2022). Therefore, crop water demand was supplemented with irrigation water. In the present study, crops suffered from moisture stress at the branching and pod formation stages in the first year; therefore, irrigation scheduling treatment I₂ at par with I₃ significantly improved growth parameters, viz. accumulation plant⁻¹, branch plant⁻¹, number of nodules plant⁻¹ and nodule weight plant⁻¹. Sufficient moisture availability during critical growth periods can be the reason for improved growth under two irrigations during the flowering and pod formation stages (Singh, 2021). Irrigation maintains cellular turgor, boosts cell division/expansion, enhances metabolic processes like photosynthesis, and facilitates nutrient translocation from leaves. These factors arising from ample moisture availability, especially during critical growth stages, collectively promote vigorous vegetative growth, taller plants, and improved yield attributes (Halder et al., 2021; Sosiawan et al., 2021).

Moreover, the yield in terms of grain yield and biological yield of moth bean was significantly influenced by irrigation scheduling in this study. Irrigation scheduling treatment I₂, at par with I₃, resulted in significantly higher grain and biological yields. Moisture availability during critical crop growth stages results in better growth and development, ultimately resulting in better grain and biological yields. The yield of moth bean was slightly higher in the first year than in the second year, although the crop received lower rainfall in the first year. These contradictory results were recorded because of untimely rain during the maturity stage, which caused a lower harvest (Maity et al., 2023).

The dual application of foliar urea spray and irrigation slightly increased the production cost of moth bean. Although the increase in grain and biological yields N₃ and I₂ contributed to higher net returns, B:C ratios, and monetary efficiency compared to other treatments. In chickpea, a 2% urea spray at pod initiation significantly increased gross returns, net returns, and benefit-cost ratio over control (Singh et al., 2022). Similarly, in mung bean, a 2% urea spray at flowering improved these economic parameters compared to unsprayed control (Muthal et al., 2016). The I₂ irrigation treatment recorded significantly higher net returns and benefit-cost ratio. The results of this study align with the findings of Thenua et al. (2010), who reported increased net returns when irrigation was applied during the flowering and pod-filling stages in a chickpea-fodder sorghum cropping system.

Furthermore, higher protein content and protein yield were registered under N_3. The increased availability of nitrogen during the seed-filling stage in pulses facilitated a higher seed protein content, and the enhanced seed yield subsequently translated into a higher protein yield (Venkatesh & Basu, 2011). The foliar application of nitrogen during the reproductive stage might have enhanced the nitrogen content in plants, which could have led to an increased photosynthesis rate. Consequently, this facilitated greater translocation of nitrogen to the grains, resulting in higher protein content in the grains (Singh et al., 2022). Among irrigation schedules, I₂ registered a higher protein content and protein yield. The higher protein content under I₂ might be attributed to increased nitrogen availability by N-fixation, which is generally highly correlated with moisture availability, leading to increased protein content with increased moisture supply (Dhima et al., 2015).

Higher grain yield was recorded with the two foliar spray applications of urea (N₃) and irrigation at branching + pod formation stage (I₂), leading to greater production efficiencies. These treatments improve production efficiency by enhancing plant growth, improving yield components, and increasing overall yield compared to other treatments. Similar findings of increased production efficiency and seed yield were reported in mung bean by Bahadari et al. (2020) and in soybean by Dass et al. (2022).

The application of nitrogen as a foliar spray in the form of urea at foliar spray of urea (2%) at the flowering and pod formation stages (N₃) exhibited the highest physical and economic water productivity when compared to the N₁ and N₂ treatments. The relatively higher values of physical water productivity (PWP_IR+P) and economic water productivity (EWP_IR+P) observed under the N₃ treatment indicate the beneficial effects of nitrogen supplementation through urea foliar spray, leading to enhanced plant biomass production (grain + straw) and increased gross returns from moth bean cultivation, respectively. These findings corroborate the results reported by Gupta et al. (2020) in their study on chickpea crops, where similar effects were observed.

The higher numerical values of PWP_IR+P and EWP_IR+P under I₂ could be attributed to the proportional increase in biomass yield resulting from the plant’s efficient utilization of the applied water and rainfall for productive purposes (Table 4). Conversely, the minimum PWP_IR+P and EWP_IR+P observed under I₁ might be a consequence of reduced biomass production under water stress conditions during critical growth stages (Sarkar et al., 2016).

The application of urea through foliar methods and the implementation of irrigation scheduling practices has a significant impact on the uptake of nitrogen, phosphorus, and potassium (NPK) by crops. The N₃ treatment resulted in the highest NPK uptake by both the grain and haulm, as well as the highest total NPK uptake by the moth bean. This may be due to the consistent supply of nitrogen (N) to the crops during their entire growth period, which is a result of applying basal N and spraying 2% urea at the flowering and pod formation stages (Deshmukh, 2012; Venkatesh & Basu, 2011). Further, I₂ registered the highest NPK uptake by grain, haulm, and total uptake by moth bean. The phenomenon of nutrient uptake is the consequence of the combined influence of nutrient content and seed yield. It was observed that irrigation induced greater nutrient uptake during the stages of pod formation and flowering. The higher nutrient uptake with irrigation at critical stages of the crop was also reported in chickpea (Singh et al., 2017). Similarly, available N, P, and K in soil, and organic carbon were with N₃, whereas among irrigation schedules, I₂ gave the highest value of available N, P, and K in soil, and organic carbon after experimentation. This could be attributed to the treatment effectively fulfilling the nitrogen needs of crops via enhanced nitrogen fixation and supply via basal dose and urea application while causing comparatively less nitrogen loss from the soil compared to alternative approaches (Gupta et al., 2011). These findings suggest that the soil nitrogen content can be sustained at an optimal level if the crops are given basal nitrogen and urea spray with sufficient moisture in the soil.

Conclusion

Moth bean production in the western arid regions of India faces significant constraints due to suboptimal agricultural practices and adverse environmental factors, including water scarcity, temperature fluctuations, and erratic precipitation patterns. This study addressed the critical need to mitigate the deleterious effects of early-season drought stress and enhance moth bean productivity, profitability, and protein availability. The novel integrated approach involving dual foliar spray of 2% urea during the flowering and pod formation stages, in conjunction with irrigation scheduling at the branching and pod formation stages, resulted in significant improvements in growth parameters, grain yield, biological yield, protein content, nutrient uptake, water productivity, and economic returns. Notably, this strategy demonstrated superior resource use efficiency, thereby enhancing the economic and nutritional security of smallholder moth bean farmers operating in water-scarce arid environments.

Authors’ contribution

Conceptualization & Methodology: [R.L.J.; S.K., N.K.], Formal analysis and investigation: [R.L; R.B., L.K.R, M.H.S., N.K], Writing - original draft preparation: [R.L; R.B., S.A., R.R.C; L.K.R]; Writing - review and editing: [M.P; M.H.S., S.A., S.K; A.K; R.K.J].

Acknowledgement

The authors express their sincere thanks to the Director, ICAR-IIPR, Kanpur, for guidance as well as for providing all available help rendered during the study. The authors sincerely acknowledge the Researchers Supporting Project number (RSP2024R347), King Saud University, Riyadh, Saudi Arabia.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data for this study are available from the corresponding author (Lalit Kumar Rolaniya) upon reasonable request.

Additional information

Funding

Authors are highly gratefully to ICAR-Indian Institute of Pulses Research, Kanpur, India for financial support for conducting the experiment. APC was supported by the Researchers Supporting Project number (RSP2024R347), King Saud University, Riyadh, Saudi Arabia.

Notes on contributors

Ram Lal Jat

Ram Lal Jat, a Scientist at the ICAR-Indian Institute of Pulses Research, Kanpur, India, is currently posted at the Regional Research Centre in Bikaner, India. He obtained his PhD in Agronomy. His research experience encompasses conservation agriculture, water management, and nutrient management in diverse ecologies. Presently, he is working on cropping system-based nutrient and irrigation management aspects for arid regions.

Lalit Kumar Rolaniya

Lalit Kumar Rolaniya, a Scientist at the ICAR-Indian Institute of Pulses Research, Kanpur, India, is currently posted at the Regional Research Centre in Bikaner, India. He obtained his PhD in Agronomy and is actively engaged in research on resource conservation technologies in arid legume-based cropping systems and integrated nutrient management. His research primarily focuses on developing sustainable agricultural practices to optimize resource use efficiency and enhance crop productivity in arid zones.

Narendra Kumar

Narendra Kumar is a Principal Scientist and presently the Head of the Division of Crop Production at ICAR-Indian Institute of Pulses Research, Kanpur, India. He holds a PhD and specializes in Cropping Systems, Conservation Agriculture, and Weed Management. His research focuses on developing sustainable agricultural practices and managing weeds to enhance pulse production.

Raja Ram Choudhary

Raja Ram Choudhary is a Scientist at ICAR-Directorate of Groundnut Research, Junagarh, India, and is presently posted at the Regional Research Station in Bikaner, India. He holds a PhD and specializes in resource conservation technologies and nutrient management in diverse agroecologies. He has extensively worked on mineral nutrition in legumes, with a focus on developing sustainable and efficient nutrient management strategies specifically for groundnut cultivation.

Monika Punia

Monika Punia is a Scientist at ICAR-Indian Institute of Pulses Research, Kanpur, India, and is currently posted at the Regional Research Centre in Bikaner, India. She holds a PhD in Genetics and Plant Breeding. She is presently working on breeding for abiotic and biotic stress resistance in arid legumes, specifically focusing on mothbean.

Sudheer Kumar

Sudheer Kumar is a Principal Scientist and Head of the ICAR-Indian Institute of Pulses Research, Regional Research Centre, Bikaner, India. He holds a PhD in Plant Pathology and specializes in integrated disease management in wheat and arid legumes. His research focuses on developing effective and sustainable strategies to manage diseases affecting legume crops in arid regions.

Arun Kumar

Arun Kumar is an Assistant Professor of Agronomy at the Livestock Research Station, Rajasthan University of Veterinary and Animal Sciences, Bikaner, India. He holds a PhD in Agronomy. His research interests encompass conservation agriculture, climate change, sustainable agriculture, cropping systems, and fodder production.

Rajendra Kumar Jakhar

Rajendra Kumar Jakhar is an Assistant Professor of Soil Science at the College of Agriculture, Swami Keshwanand Rajasthan Agricultural University, Bikaner, India. He holds a PhD and specializes in soil fertility, salinity, and sodicity. His research focuses on understanding the complex dynamics of soil fertility and the challenges posed by salinity and sodicity in arid regions.

Rajan Bhatt

Rajan Bhatt is an Associate Professor at the Punjab Agricultural University-Regional Research Station, Kapurthala, Punjab, India. He holds a PhD in Soil Science. His expertise lies in water resources management, irrigation and drainage, protected cultivation, and the use of non-conventional energy resources in irrigation. His research focuses on developing sustainable and efficient water management strategies, optimizing irrigation systems, and promoting the adoption of protected cultivation techniques.

Saud Alamri

Saud Alamri is an Associate Professor at the Department of Botany and Microbiology, College of Science, at King Saud University in Riyadh, Saudi Arabia. He holds a PhD in Plant Biology. His expertise lies in stress physiology and ecophysiology. His research focuses on understanding the physiological and ecological responses of plants to various environmental stresses, such as drought, salinity, and extreme temperatures.

Manzer H. Siddiqui

Manzer H. Siddiqui is a Professor in the Department of Botany and Microbiology, College of Science, at King Saud University in Riyadh, Saudi Arabia. His research focuses on crop production, with a special emphasis on the management strategies of different fertilizers, plant growth regulators, and signaling molecules, such as nitric oxide, hydrogen sulfide, and reactive oxygen species (ROS), under various environmental conditions.