Enhancing Farm Income through Boundary Plantation of Poplar (Populus deltoides): An Economic Analysis

Abstract

Poplar is popular among farmers and planted widely in the form of block and boundary systems. The preferences of farmers are shifting much more towards bund plantations due to their smaller yield reductions and can take up kharif and rabi crops till rotation. As for boundary plantations, farmers tend to grow trees in any direction without concern for yield reduction or profitability. Against this background, an experiment was designed by planting poplar at 2 m intervals in East–West (E–W) and North–South (N–S) directions during 2008 to determine the production potential and economic viability of boundary plantations and their effect on sorghum (Sorghum bicolor) and wheat (Triticum aestivum) crop rotations till harvesting of the trees. The experiment comprised three variables: stand age (years); four aspects (northern and southern E–W rows, eastern and western N–S rows; these four aspects are considered by dividing the tree lines); and six distances from tree the lines (0–3, 3–6, 6–9, 9–12, 12–15, 15–18 m and a control). A split-split plot design with three replicates was used. A significant reduction of fodder biomass of sorghum and wheat yield was observed up to 9 m distant from the tree line: the reduction was 10 to 60% for the kharif season and 7.2 to 29.5% for rabi crops from the second year to eight years after planting, respectively. Interestingly, the poplar boundary plantation had a favorable microclimatic effect from 9 to 15 m distance from the tree line, which increased crop yields compared with the control. The total dry wood production of poplar in the E–W direction (166.99 mg ha⁻¹) was almost two times more than production for the N–S direction (82.62 mg ha⁻¹) at 8 years of rotation. The economic analysis of this study concluded that an E–W boundary plantation of poplars exhibited the maximum net returns of INR 549,367 ha⁻¹, a net present value of INR 222,951 ha⁻¹, a BC ratio of 1:1.65, an IRR of 85% and an LEV of INR 1,220,337 ha⁻¹. Therefore, it is concluded that the intercropping of a sorghum-wheat crop rotation in E–W boundary plantations was more beneficial for enhancing farm income over traditional agriculture in north India.

1. Introduction

In India, a revolution in intensive agriculture through modern agricultural technologies has changed the scenario from millions of empty food bowls to a million tonnes of food in godowns, and it has been one of most successful strategies in the fight against hunger. The Indo-gangetic region (IGR), which is one of the most fertile tracts of Ganga popularly known as “food basket” of India and comprises Punjab, Haryana, western Uttar Pradesh and some parts of Bihar, emerged as a savior for an ailing food scarce nation. The IGR produces about 50% of the total food grains, which satisfy the demand of 40% of the population of the country [1,2]. In the region, the rice (Oryza sativa)-wheat (Triticum aestivum) cropping system (RWCS) is one of the predominant traditional cropping systems spread over 53% of the total area [3]. On the flip side, the revolution has caused many environmental concerns and is considered the killer of the nature’s gift: soil fertility. This advancement in traditional agriculture during last five decades has created several negative consequences such as land fertility loss through erosion, nutrient depletion and water source contamination [4,5]. Intensive agricultural practices are one of the major contributors to greenhouse gas emissions, which include carbon dioxide (CO₂), methane (MH₄) and nitrous oxide (N₂O) [6]. In addition, a rising population along with degradation of resources, poverty and food and nutritional insecurity make India more vulnerable to the impacts of climate change. Smallholder farmers are largely affected by extreme climate events as they are less able to cope. In India, the total area of operational holdings decreased by up to 1.15 hectares as per the records of the Agriculture Census (2015–2016). About 85 per cent of the total holdings fall into the marginal and small farm category consisting of less than 2-hectare land holdings and operate on 44 percent of land under cultivation. These figures on land holdings indicate that the number of small and marginal farmers is increasing in the era of climate change. Their coping ability and vulnerability impact food security and require urgent attention. In such situations, diversification of existing cropping systems though agroforestry is becoming a prime solution to address food security and sustainability issues in the IGR.

Trees in agricultural landscapes provide openings to a diversified set of agricultural production systems that contribute various spillover benefits by improving the coping ability of smallholder farmers towards extreme climatic events [7] and also fulfilling the ever increasing demands of wood-based industries [8,9]. Agroforestry is widely practiced by more than 1.2 billion people throughout world due to its multiple benefits [10,11]. The role of trees in securing livelihoods in the face of climate change is more focused due to their ability to withstand extreme weather events and modify the local microclimate to support improved production of agricultural crops. In relation to this, the potential carbon sequestration through agroforestry is well explained by various authors [12,13,14,15,16]. As per Zomer et al. [11], 43% of the world agricultural area has 10% tree cover, with trees contributing >75% of an estimated 45.3 Pg of carbon on agricultural landscapes globally. Agroforestry systems in India help to offset 142.34 million tons CO₂ equivalent annually (about one-third greenhouse gas emissions from the agriculture sector) from 15.31 million hectares [12]. Therefore, tree-based systems create the opportunity to adapt and to mitigate the adverse impacts of climate change in agricultural landscapes [17,18,19] as well as increase agricultural yields and timber production [20]. The trees in agricultural landscapes also reduce the vulnerability to extreme events by ameliorating microclimatic conditions and improving soil health [21]. Irrespective of the multifarious tangible and intangible benefits of agroforestry, farmers still have a certain level of apprehension about including trees on their farms due to potential crop yield reductions as well as trees being a hindrance to the movement of farm equipment [22].

As earlier discussed, the landholdings of farmers is also an important notion in the adoption of agroforestry system. Farmers are purposely plant various tree species on farm boundaries to reduce competition with arable crops and also provide ecosystem services, such as microclimate amelioration, soil improvement and reductions in wind velocity and evapotranspiration. Retention of trees on farm boundaries is one of the most adopted traditional tree planting practices in India. After independence, the overuse of forest resources increased degradation, reduced forest areas, and further increased wood scarcity for industrial use. To tackle this, several social forestry programs were promoted by government departments to increase tree cover, among which tree plantations on farm boundaries was the most popular as farmers preferred to plant fast growing tree species around their homesteads, along field boundaries and irrigation channels and also within the fields. It became a very common practice in rice and wheat cropping systems in the IGP region. Various agroforestry tree species, such as Eucalyptus, Melia, Bamboo, Dalbergia and Poplar etc., are commonly planted on farm boundaries. Among these tree species, poplar is the widely preferred tree due to its short rotation, high growth rate, leafless state in winter which permits intercropping, and market acceptability. These tailor-made characteristics have allowed it to be adopted as an alternative to the traditional wheat-paddy crop rotation in the IGR of India [9,15,20,23]. Zomer et al. [10] reported that bund and boundary plantings have been adopted extensively due to the assured income they provide, reduced crop loss and very low labor cost. Rizvi et al. [24] and Chauhan et al. [23] observed the higher diameter growth and biomass of trees grown as a boundary compared with block planted trees, even though trees interfere with critical growth resources and directly impact crop yields. The orientation of boundary plantations creates unique opportunities by modifying shelter and shade conditions in agriculture fields. These include plant height, the planting density, orientation, modified light conditions, crop yields and spacing of the tree strips, and the roughness of the terrain [25]. Generally, boundary planting of trees is occurs in any direction (East–West and North–South direction) depending on the availability of land without considering the above-mentioned parameters. Several researchers have studied the effect of boundary planting on arable crop yield in irrigated as well as rainfed regions of India. Studies carried out by various researchers observed that a significant yield reduction of more than 70% was observed near the tree base (0–3) and about a 10–35% reduction up to 9 m away from the tree [10,22,23,25]. The microclimate modification of bund plantations positively enhances the yield in wheat crops grown with poplar boundary plantations in Punjab [26,27]. Kidanu et al. [28] rightly mentioned that the tree shade effect, reduced wind velocity, age of the tree, field aspects and interaction due to the boundary plantation are considered crucial parameters for extra yield advantage. Studies by Chhavi et al. [29] critically pointed out that the orientation and spacing of trees are the key factors to optimize the production of arable crops in boundary plantations.

Recently, small and marginal land holdings of farmers are dominantly adopting boundary plantation in the IGR. When poplar is planted on the field boundaries, kharif crops have been harvested until the rotation, whereas as in case of block plantations, it is possible up to beyond three years [9,30]. However, there is a large concern among the farmers over the planting direction of boundary rows as it affects the performance of agricultural crops significantly [26]. The majority of studies in bund planting have been carried out either for two years or, at most, with trees up to four years of age. In addition, crop growth and yield reduction were prominent features of the studies in India as well as around the world. There are scarce efforts to quantify the economic performance of the boundary planation of poplar or other fast-growing trees in India [31,32]. It has been critically observed that most of the scientific studies on the economic analysis of tree-based systems do not present a realistic picture of feasibility or profitability because they were carried out either by extension survey questionnaires or over a two year period as a secondary investigation in studies of a package of crop growing practices [32,33,34]. Therefore, a study was planned over the complete cycle of poplar as a boundary plantation (from planting to harvesting of trees over a period of 8 years) intercropped with a sorghum–wheat crop rotation to investigate crop performance and tree age, the effects of the orientation of tree lines and the economic viability of the system. We have formulated a hypothesis that tree age and tree line direction/orientation influence crop performance and tree biomass and that adoption of boundary plantations by small landholding farmers results in increased returns over existing cropping practices. Thus, our main focus was to determine the economic feasibility of boundary plantations of poplars in a field experiment from planting to harvesting.

2. Materials and Methods

2.1. Field Description

The research work was carried out at Chaudhary Charan Singh Haryana Agricultural University, Hisar, Haryana (India) located at 29°10′ N latitude and 75°43′ E longitude and at an elevation of 215 m above mean sea level. The climate of the site is semi-arid and subtropical-monsoonal. The average annual rainfall is recorded as 350–400 mm, of which 70–80% occurs between July and September. During the summer months, the temperature ranges from 40 to 45 °C in May and June, whereas December and January are the coldest. The soil type is sandy-loam with medium levels of organic carbon, available nitrogen, phosphorus and potassium. The mean yearly data for meteorological parameters during the eight-year rotation is presented for understanding the conditions the of experimental site (See Supplementary Materials).

2.2. Experimental Details: Populus Deltoides

Entire transplants of G-3 clone poplars were planted in two row directions, i.e., east–west (E–W) and north–south (N–S), with trees separated by 2 m and resulting in a constant tree density of 200 tree ha⁻¹ (Figure 1). The present experiment was carried out in the period 2008 to 2016, and the trees were harvested after 8-years of planting. The row of poplars was established during February by digging out 3 m deep pits using a tractor mounted augur and filled with 3:1 potting mixture of (soil: FYM). The one-year-old entire transplant poplar clones were then planted in the pit. The standard practices for raising poplar were followed.

2.3. Crop Sampling

The row of poplar trees were planted in the most commonly adopted directions, i.e., north–south and east–west directions. Furthermore, the directions (east–west and north–south) were considered as partition between single fields into two aspects. The north–south tree lines divide farmlands into an eastern–western aspects, and the east–west oriented tree lines divide farmlands into a northern–southern aspects with respect to the tree lines (Figure 1). Intercropping of sorghum (Sorghum bicolour) during kharif (July–October) and wheat (Triticum aestivum) during the winter season (November–April) was conducted from the second year after poplar planting until the trees were harvested. A control sorghum–wheat crop rotation was maintained alongside for comparison. The standard package of practices designed by CCS Haryana Agricultural University, Hisar, Haryana (India) was followed to cultivate the annual crops. At crop maturity every cropping season, quadrat based samples of 1 m² were harvested at six distances (0–3 m, 3–6 m, 6–9 m, 9–12 m, 12–15m and 15–18 m) from the tree lines on four aspects in three replicates. For comparison, quadrat samples were also harvested from the control sole cropping field. The green fodder biomass of sorghum and wheat grain yield was extrapolated to a hectare basis and expressed in t ha⁻¹. Figure 1 provides the actual planting site of the poplar rows and illustrates the four aspects with crop observations taken from different distances (0 to 15 m) from the tree line.

2.4. Tree Sampling

The tree height and girth were randomly recorded every year in the month of February until harvest. Randomly selected trees were destructively harvested at rotation age (8 years after planting) from the E–W and N–W rows of poplars. After harvesting, the trees were separated into components for fresh biomass measurements and representative samples were taken to measure dry weights. Fresh component-wise samples were dried to constant weight at 60 °C and weighed for biomass components (leaf, branch, bole, and root) to calculate total component fresh and dry biomass (t ha⁻¹) following standard methodology [13]. The tree height was measured using a ravi altimeter, and girth at breast height (GBH) and diameter at breast height (DBH) were measured using a measuring tape. These girths of trees were used to calculate the revenue on a per tree basis by using the Haryana Forest Development Corporation’s 2015 price list for poplar (https://hfdc.gov.in/, accessed on 15 December 2018).

2.5. Economic Analysis of Boundary Plantations

In the economic analysis, the E–W and N–S boundary plantations were systematically compared with the sorghum–wheat crop rotation over a period of eight years (from planting to till harvesting). A cost-benefit analysis was performed to understand the viability of the agroforestry systems over traditional cropping on a financial basis. Different components of the systems were analyzed as described in the following sections:

• Establishment Cost (A): The cost of establishment of species included land preparation, poplar ETPs, transportation, planting and plant protection and transplanting and plant protection during the establishment phase.
• Operational Cost (B): The costs of general maintenance of the trees and crops, such as watering, fertilizers and manure applications, planting materials of crops, hoeing and weeding, and other miscellaneous components etc. A 9% interest rate on working capital (establishment cost + operational cost) was assumed in the analysis.

Another two costs, management cost (10%) and risk cost (10%) were also considered in the analysis. The annual existing rental value of land was added for the financial analysis. The management cost includes the intellectual cost of managing the systems such as a farm. The values of the 10% risk and management costs were based on the assumption that a farmer expects a minimum return of 10% per annum, which is slightly above the prime lending rates of the national banks. The risk cost is meant to cover the risk expected to be faced by farmers or systems. In the case of risk cost, insurance companies charge a premium of 3 to 10% in case of any exigency due to weather or natural calamity (https://pmfby.gov.in/pdf/NAIS_SCHEME.pdf, accessed on 2 June 2022 ). The cost-benefit parameters used for comparison of systems were net returns, net present value (NPV) at a 12% discount rate, internal rate of returns (IRR) and benefit/cost ratio (BCR). The costs incurred and income generated from the intercrop and poplar trees were calculated.

Net Present value: NPV was estimated as below:

$$\mathrm{Net}\mathrm{Present}\mathrm{Value}={\displaystyle \sum }_{i=1}^n\frac{\left(Bi-Ci\right)}{\left(1+r\right)t^2}$$

(1)

where B represents benefits in the year t, C the costs in year t, r the selected discount rate and n the number of years

Benefits cost ratio (BCR): BCR can be expressed as follows:

$$\mathrm{BCR}={\displaystyle \sum }_{i=1}^n\frac{Bi}{{\left(1+r\right)}^2}/\frac{Ci}{{\left(1+r\right)}^2}$$

(2)

Internal rate of return (IRR): This states the rate of discounting, which equates the present value of a stream of net benefits with the initial investment outlay, or more simply, the rate at which the net present value of cash flow is zero.

Land expectation value (LEV): The estimation is based on the assumption that the land is the property of the given enterprise with the same management in perpetuity [35]. This was calculated using the Faustmann model that combines annual revenue flow from intercropping and poplar trees:

$$\mathrm{LEV} \left(\frac{Rs}{ha}\right)=\frac{\mathrm{NPV} {\left(1+r\right)}^t}{{\left(1+r\right)}^t-1}$$

(3)

where NPV is the net present value, r is the interest (discount) rate, t is the time period.

Land equivalent ratio (LER): LER was used to quantify the land use efficiency and productivity of intercropping, mixed cropping and agroforestry systems [36]. LER was calculated using three different methods: on the basis of crop equivalent yield (wheat) of commodities; on a biomass/yield basis; and on a monetary basis (NPV dependent), as per the formula of Chavan et al. [9]. It is the ratio of relative yield of the intercropped crop and tree in boundary planting to the yield of same tree and crop in sole plantings for a similar period. It is calculated as follows:

LER = [Y_pc/Y_p] + [Y_cp/Y_c]

(4)

where Y_pc and Y_cp are the yields of the poplar and crop species as mixtures, respectively, and Y_p and Y_c are the yields of poplar and crop species in a monoculture, respectively.

It can be concluded that if LER = 1, intercropping has no advantage over monocropping. If LER < 1 it can be concluded that competition causes yield loss and if LER > 1, it is concluded there is a higher yield of both components on same piece of land compared with a monoculture.

2.6. Statistical Analysis

The F-test was used to statistically evaluate the data collected throughout the study. The significant differences across treatments were examined using LSD (least significant difference) at a 5% level of significance. An analysis of the data was then carried out using the ANOVA [37]. The experiment comprised three factors: stand age (years); four aspects (E–W northern and southern rows; N–S eastern and western rows; these four aspects were considered by dividing the tree lines); and seven distances from the tree lines (0–3 m, 3–6 m, 6–9 m, 9–12 m, 12–15 m, 15–18 m and a control). A split-split plot design with three replicates for the sorghum and wheat crops was used.

3. Results and Discussion

3.1. Growth Performance of Poplar Boundary Planting

Tree growth is a function of age, spacing, aspect, orientation and site quality. Tree growth data revealed that with the advancement of age, there was a gradual increase in the height and DBH in the E–W and N–S boundary plantations (Figure 2). The growth parameters (both height and DBH) of eucalypts followed an increasing trend with the advancement of age under different planting geometries. The comparative performance of the E–W and N–S boundary plantations of poplars in terms of height (m), diameter at breast height (cm), component wise dry biomass (kg tree⁻¹) and total biomass (mg ha⁻¹) are shown in

Table 1. Height, DBH and dry biomass of Populus deltoides boundary plantings after harvesting (8 years of rotation).

Row Direction	Tree Height (m)	DBH (cm)	Aboveground Biomass (kg tree−1)				BGB (kg tree−1)	Total Tree Biomass (kg tree−1)	Total Dry Biomass (Mg ha−1)
			Stem	Branch	Leaves	Total
E–W	22.15 ± 1.39	36.22 ± 0.22	546.03 ± 20.76	93.47 ± 18.86	35.87 ± 5.98	675.36 ± 70.14	154.53 ± 35.28	829.90 ± 62.39	83.49
N–S	16.8 ± 0.61	27.55 ± 0.20	274.67 ± 39.75	57.82 ± 11.60	17.03 ± 3.40	349.51 ± 47.34	67.28 ± 14.81	416.79 ± 56.98	41.31

Least significant difference at p = 0.05.

. The mean height and DBH of the E–W boundary planting and N–S boundary planting were recorded as 22.15 ± 1.39 m, 36.22 ± 0.22 cm, 16.8 ± 0.61 m, and 27.55 ± 0.20 cm, respectively. The study found that the growth of the E–W row planting was far greater (height: 24.15% and DBH: 33.33%) than that of the N-S row planting of poplars. At the rotation age, the average dry biomass of the E–W plantings (829.90 kg tree⁻¹) produced two times more biomass than the N–S row plantings of poplars (413.10 kg tree⁻¹). The dry weight of stem was also higher for the E–W boundary plantings (546.03 kg tree⁻¹) compared with the N–S boundary plantings (274.67 kg tree⁻¹). However, the total biomass production was higher in the E–W boundary plantings (83.49 mg ha⁻¹ at 100 tree ha⁻¹) than in the N–S boundary planting method (41.31 mg ha⁻¹). The present performance of the poplar boundary is higher than that measured in earlier work of [24,38,39,40]. The study of Rizvi et al. [24] observed that poplar boundaries in the Saharnapur district of Uttar Pradesh and the Yamunanagar district of Haryana produced (over seven rotations) 49.41 and 45.91 t ha⁻¹ of aboveground timber biomass, respectively. The findings of Chauhan et al. [38] support the present study, in which a 6-year-old poplar boundary plantation (height: 22.12 m and DBH 24.23 cm) was estimated to produce 46.153 t ha⁻¹ at a density of 200 tree ha⁻¹. The dry biomass of boundary planted trees is higher than for block planted trees on a per tree basis [41]. Therefore, it is concluded that the orientation of the E–W row direction provides ample sunlight, resulting in a higher photosynthetic rate.

3.2. Yield Performance of Agricultural Commodity

The present study found that stand age (years), four field aspects, and six distances from the tree line and interactions between these factors significantly influenced sorghum as well as wheat yield at the tree-crop interface (

Table 2. Green biomass of Sorghum (t ha⁻¹) under boundary plantation of Populus deltoides.

Aspect	Distance from Tree Line	Green Biomass of Sorghum (t ha−1)
		2	3	4	5	6	7	8	Average
East	0–3	35.00	17.80	19.37	19.08	7.00	7.78	7.53	16.22
	3–6	35.63	30.73	24.27	23.19	13.87	7.03	8.88	20.51
	6–9	35.77	36.77	30.03	27.87	15.44	19.27	17.28	26.06
	9–12	36.90	43.13	33.23	31.07	24.83	27.17	26.14	31.78
	12–15	40.00	42.90	35.27	35.14	27.82	31.17	30.38	34.67
	15–18	39.30	43.03	36.37	34.60	27.47	31.08	29.49	34.48
West	0–3	34.50	18.50	20.33	15.17	6.71	7.40	8.88	15.93
	3–6	35.05	28.87	23.60	23.43	13.52	8.53	7.38	20.05
	6–9	35.37	34.47	31.68	32.47	15.23	18.30	18.28	26.54
	9–12	36.50	43.03	32.02	33.80	24.62	22.82	25.38	31.17
	12–15	38.08	43.10	36.62	33.93	24.76	27.80	25.28	32.80
	15–18	39.83	43.00	33.45	33.87	24.62	30.50	26.28	33.08
North	0–3	38.95	20.17	14.97	7.27	5.73	3.77	5.36	13.75
	3–6	40.18	26.53	20.00	10.00	14.06	10.47	11.37	18.94
	6–9	41.58	36.57	31.97	17.30	20.51	14.80	19.18	25.99
	9–12	41.68	37.90	33.80	28.70	34.49	23.50	29.51	32.80
	12–15	42.88	39.50	36.13	34.00	35.24	28.30	31.58	35.38
	15–18	42.48	40.07	36.80	32.87	35.05	27.13	30.38	34.97
South	0–3	39.46	20.87	18.13	19.57	7.10	8.34	7.68	17.31
	3–6	40.98	31.87	24.97	16.20	16.27	15.73	14.13	22.88
	6–9	42.08	36.27	33.57	24.90	22.17	18.45	24.78	28.89
	9–12	42.68	42.27	34.50	30.60	35.57	26.80	32.48	34.99
	12–15	43.88	41.83	35.97	35.20	35.30	29.10	32.78	36.29
	15–18	43.88	40.87	33.77	35.30	35.47	29.70	33.28	36.04
Control		42.45	42.10	36.66	35.00	35.00	30.53	31.48	36.17
Year (Factor A)		0.204		Distance (Factor C)			0.148
Aspect (factor B)		0.153		Interaction A × C			0.391
Interaction A × B		0.404		Interaction B × C			0.295
Interaction A × B × C		0.782

Least significant difference at p = 0.05.

and

Table 3. Grain yield of wheat (t ha⁻¹) under a boundary plantation of Populus deltoides.

Aspect	Distance from Tree Line	Grain Yield of Wheat (t ha−1)
		2 year	3 year	4 year	5 year	6 year	7 year	8 year	Average
East	00–03m	3.59	2.84	3.22	2.55	2.70	2.40	1.72	2.72
	03–06m	3.74	3.59	3.55	2.73	3.02	2.90	2.18	3.10
	06–09m	3.80	3.62	3.63	2.76	3.14	3.12	2.73	3.26
	09–12m	3.85	3.84	3.74	2.90	3.47	3.28	3.06	3.45
	12–15m	3.82	3.82	3.78	3.10	3.59	3.48	3.43	3.57
	15–18m	3.80	3.95	3.77	2.76	3.45	3.35	3.52	3.51
West	00–03m	3.56	2.77	3.33	2.63	2.70	2.48	1.57	2.72
	03–06m	3.78	3.54	3.65	2.77	3.25	3.13	1.75	3.12
	06–09m	3.91	3.51	3.65	2.77	3.62	3.30	2.24	3.29
	09–12m	3.88	3.84	3.59	2.94	3.64	3.48	2.73	3.44
	12–15m	3.91	3.93	3.80	2.99	3.70	3.54	3.10	3.57
	15–18m	3.90	4.03	3.58	2.96	3.65	3.53	3.20	3.55
North	00–03m	3.50	2.69	1.84	2.70	1.72	2.50	1.99	2.42
	03–06m	3.70	3.22	2.11	3.35	2.45	3.42	2.90	3.02
	06–09m	3.70	3.45	2.74	3.80	2.50	3.82	3.04	3.29
	09–12m	3.90	3.65	3.64	3.86	2.53	3.69	3.40	3.52
	12–15m	4.00	3.80	3.66	3.92	2.46	3.90	3.41	3.59
	15–18m	3.90	3.89	3.79	4.02	3.43	3.79	3.87	3.81
South	00–03m	3.61	2.80	1.91	2.99	2.12	2.74	2.28	2.64
	03–06m	3.86	3.49	2.23	3.49	2.64	3.72	3.32	3.25
	06–09m	3.94	3.61	2.70	3.58	3.05	3.72	3.54	3.45
	09–12m	4.05	3.70	3.57	3.84	3.55	3.74	3.40	3.69
	12–15m	4.19	3.98	3.63	3.90	3.63	3.99	3.64	3.85
	15–18m	3.92	3.96	3.77	4.06	3.31	3.98	3.91	3.84
Control		4.05	4.04	3.57	3.49	3.46	3.6	3.44	3.66
Year (A)		0.016		Distance (C)				0.013
Aspect (B)		0.015		Interaction (A × C)				0.034
Interaction (A × B)		0.039		Interaction (B × C)				0.026
Interaction (A × B × C)		0.068

Least significant difference at p = 0.05.

). A significant interaction between stand age and distance from the tree line indicated that the competitive ability of poplar boundaries, as measured in terms of crop yield losses at the tree crop interface, increased with stand age. The green fodder biomass production of sorghum and wheat grain was found to be statistically significant for both directions of poplar boundary plantations, i.e., the E–W and N–S rows. The performance of sorghum and wheat crops was strongly influenced by the distance from tree lines and the age of the poplar trees. The average green sorghum fodder biomass was 28.55, 27.963, 28.28 and 30.36 t ha⁻¹ in the eastern, western, northern and southern aspects of both the boundary plantations throughout the rotation, respectively, whereas the average biomass of sorghum in the control plot was also recorded to be 36.17 t ha⁻¹. The southern aspect of the E–W row direction produced 6% more sorghum biomass than the other aspects. A similar trend was also observed in the case of wheat grain yields, where the southern aspects produced 4% extra yield over other aspects (Figure 3b). This might be due to significant interaction between distance and aspect that was attributed to small differences in the intensity and duration of shadows cast by the boundary stands, which was obviously higher on east–west facing plots (aspect) than on north–south facing plots (aspect). Arenas-Corraliza et al. [42] provided an interesting observation that appropriate shade conditions have a positive impact on the physiological basis of crops and yield. Kanzler et al. [43] reported a 16% higher grain yield of winter wheat under temperate agroforestry compared with an open field crop. Similarly, researchers [44,45] have reported that ecological intensification through agroforestry increases crop yield through better use of resources.

During the poplar rotation from the 2nd year to the 8th year, the green fodder biomass of sorghum (Figure 3a) and the wheat grain yields (Figure 3b) noticeably reduced from 7.04 to 83.64% and 9.04 to 54.4% at 3 m distance from tree line compared with the sole crop Control. The high competition for soil moisture and light conditions near tree stem reduces the crop yield drastically. Poor crop performance near the tree line at 2–3 m was also reported by [26,46] in a poplar boundary plantation. In both seasons, crop yield of sorghum and wheat at 9 m distance from the tree line was reduced by 41.2% and 19.1%, respectively. The negative effects on crop yields from the presence of trees are due to shading and increased competition for critical resources [22,42]. The reduction in crop yield near the tree lines was due to competition for water, nutrients, and light or unsprayed crop edges which reduce the photosynthetically active radiation (PAR) and rainfall interception in comparison with open conditions [47].

At a 9 to15 m distance from the tree lines, positive results in terms of increased yields of sown crops (Table 3) were observed. Figure 3a,b reveal the variable influence on yield in different directions, which can be attributed micro-site enrichment due to shade and litter fall. In the present study, the yield of wheat increased by 3.5% at 9–15 m distance from tree line during the three- to six-year age period of the trees. The microclimatic effects of poplar boundary plantations such as reduced wind velocity and improved shade conditions favor the higher retention of soil moisture and reduced evapo-transpirational rate leading to more yield than in the control or open conditions. Similar types of findings are also observed by [26,27] for poplar plantations. The study reveals that the southern aspect of the E–W row-direction performs better in terms of crop yield over other aspects of boundary plantations. This might be because the orientation of southern aspects provides better growing conditions such as increased insolation and, therefore, higher photosynthetic activity and micro enrichment conditions favoring improved assimilation of nutrients. The results of this study also indicate that more pronounced yield reductions were observed in kharif crops (up to 83%) than in rabi crops (41%). It is a well-accepted fact that competition for light affects the yield of agricultural crops under agroforestry system more than in sole cropping. Many researchers [48,49] have observed that the yields of rainy season crops is more significantly reduced than those of winter season crops because during rainy season, the heavy shade of poplar trees hinders the interception of light and reduces the yield. However, the leaflessness of poplar trees in the winter season allows for plentiful light to reach the crops and leads to more yield than in the rainy season. Moreover, in agroforestry systems, annual yield reductions of various crops are compensated for in the form of woody biomass, which is well supported by various economic evaluation studies [32,50].

3.3. Land Equivalent Ratio (LER) in Agroforestry

Land sharing of multiple components for higher productivity is more appropriately indicated as land sparing to achieve the goal of efficient utilization of land resources expressed in terms of LER [51]. More precisely LER can be defined as a ratio of the total non-cropped area to the agroforestry area, with similar types of management practices for equal yield [52,53]. Yu et al. [54] also stated that any ratio above one is feasible for intercropping. In agricultural systems, LER is widely used for intercropping experiments to select better performing systems, whereas in agroforestry it is very limited. We have used three approaches to analyze the LER values including biomass basis, crop equivalent yield (wheat yield basis) and discounting /Net present value basis (monetary basis), and these are presented in Figure 4. Further, Terreaux and Chavet [55] mentioned that the monetary-based calculation of LER provides more generalized results than a biomass-based calculation. In this study, the LER of the sorghum-wheat crop rotations under four aspects of poplar row direction was greater than one and ranged from 1.37 to 2.67 for poplar intercropped with a sorghum-wheat crop rotation (Figure 4). The LER of 2.67 means that one hectare of agroforestry farm produces as much crop and tree products as a conventional 2.67 ha farm where trees and crops are separated. In other words, LER values ranging from 1.37 to 2.67, indicate that the agroforestry systems were more productive by 37–167% compared with monocultures. Alternatively, it would require 167% of extra land to produce the yields of agroforestry if crops were grown on separate land as monocrops. Among the four aspects of the boundary plantations, the southern aspect of the E–W boundary plantation recorded the highest LER value in all of the three methods (Figure 4). Concerning the tree row directions, the E–W row of poplars had higher LER values compared with the N–S row direction. The results also suggest that intercropping of agricultural crops with poplar under semi-arid environmental conditions maximizes the use of available resources compared with sole cropping systems. Certainly, agroforestry systems provide a unique opportunity to enhance the LER over sole cropping. This has been also reported in oil-palm agroforestry, Leucaena-alley cropping, poplar, Acacia senegal, and bamboo [51,52,56,57,58]. Studies carried out by Chavan et al. [9] reported the sorghum-berseem cropping pattern resulted in a higher LER ranging from 1.75 to 2.28 in three-spacing geometry of poplar-based agroforestry. A similar field study in Germany of intercropping of wheat and barley with different densities of poplar found higher production with LER ranges from 1.1 to 1.6 compared with the monocultures [56]. Hence, a maximum LER for the poplar-based agroforestry system was reported, which suggests a positive synergistic mutual relationship between trees and crops.

3.4. Financial Analysis

The economic viability of an agricultural system is a critical factor for its adoption and success among the farmers of India. The adoption of certain practices by the farmer occurs if they are more attractive, remunerative and profitable compared with existing practices. In agroforestry, economic studies are carried out as questionnaire surveys or are based on secondary information, but practically, these methods do not provide a realistic picture. [33,34,59]. In the present study, observations were recorded from land preparation, planting, annual crop and tree growth data, land rental values, input costs to market values of the output. Based on this data, the following were calculated: benefit:cost ratio (B:C ratio), internal rate of return (IRR), net present value (NPV), and land expectation value (LEV).

The detailed economic analysis of the four aspects (northern and southern E–W rows, eastern and western N–S rows ) of the poplar boundary plantations intercropped with a sorghum-wheat crop rotation is presented in

Table 4. Details of cultivation costs of Populus deltoides boundary plantation.

Sr. No	Particulars	Annual Expenses (INR ha−1)								Total Value	Percent
		1	2	3	4	5	6	7	8
A	Establishment cost
	Poplar	4500	550	0	0	0	0	0	0	5050	0.86
B	Operational cost
1	Trees	2756	3400	3289	3141	4270	4500	3991	3666	29,013	4.97
2	Sorghum	0	7575	10,215	11,575	10,549	11,885	13,383	17,858	83,039	14.22
3	Wheat	0	15,378	17,008	18,183	19,523	22,540	24,083	25,538	142,250	24.35
4	Miscellaneous cost	250	570	657	830	617	888	1013	1118	5942	1.02
5	Total operational cost	2756	26,353	30,512	32,899	34,342	38,925	41,456	47,061	25,4302	43.53
6	Interest on working capital @ 10%	676	1661	1989	2054	2353	2671	2876	3220	17499	3.00
C	Total variable cost	8182	29,133	33,158	35,783	37,311	42,483	45,344	51,399	282,793	48.44
1	Management cost at 10%	818	2913	3316	3578	3731	4248	4534	5140	28,279	4.84
2	Risk factor at 10%	818	2913	3316	3578	3731	4248	4534	5140	28,279	4.84
3	Rental value of land	12,382	21,882	24,375	34,133	33,818	34,856	35,880	36,000	233,325	39.94
D	Total fixed cost	14,018	27,709	31,007	41,289	41,280	43,353	44,949	46,280	289,884	50.00
F	Marketing/transportation cost	0	1170	1425	1622.5	1800	1727.5	1920	1800	11,465	1.96
G	Total cost of cultivation	22,200	58,012	65,590	78,694	80,391	87,564	92,213	99,479	584,142	100.00

(Establishment cost: land preparation, pre-tillage, digging of pits, FYM, transplanting cost, planting material cost and some protective measures etc.; Operational cost: subsequent yearly operation such as thinning and pruning, weeding, sowing of sorghum and wheat, irrigation, fertilizer applications, harvesting and protective measures etc.) The rate of 1 US dollar was considered to be 65 INR.

and

Table 5. Economic analysis of E–W and N–S boundary plantations (INR ha⁻¹).

Particulars	Boundary Plantation (INR ha–1)						Control (Sole Crop)
	North–South			East–West
	Eastern	Western	Mean	Northern	Southern	Mean
Total cost of cultivation	586,741			586,741			569,655
Returns from the System
Trees	255,000	255,000	255,000	558,000	558,000	558,000	–
Kharif crops (sorghum)	210,134	209,899	210,017	213,136	223,775	218,456	301,930
Rabi crops (wheat)	352,795	365,369	359,082	352,807	361,300	357,054	490,477
Total returns (INR ha–1)	817,929	830,268	824,099	1,123,943	1,143,075	1,133,509	792,407
Net income (INR ha–1)	233,787	246,126	239,957	539,801	558,933	549,367	26,068
NPV12% discounting	93,418	98,903	96,161	217,753	228,149	222,951	17,064
Benefit-cost ratio	1.28	1.30	1.29	1.65	1.68	1.67	1.05
Internal rate of return%	63	65	64	82	88	85	-
Land equivalent value (INR ha–1)	511,320	541,352	526,336	1,191,883	1,248,791	1,220,337	93,402

. During the first year of agroforestry, the total cost of planting was higher compared with the sole agriculture control, and the returns from the various systems were also negative. The returns from agroforestry systems in the first years are negative due to higher initial investment cost [60]. We considered the time value of money at a discount rate of 12% in the economic analysis of different criteria (Table 5). The highest gross returns was obtained from the sorghum-wheat crop rotation under southern farm orientation of the E–W row (INR 1,143,075), followed by the northern aspect (INR 1,123,943). Moreover, the highest returns over a period of 8 years were obtained from the E–W boundary plantation, due to the orientation favoring plentiful light, nutrient and moisture levels.

The net returns from the various aspects of E–W and N–S boundary plantations of poplar ranged from INR 233,787 ha⁻¹ (eastern aspect) to INR 558,933 ha⁻¹ (southern aspect) as presented in Table 5. The net returns from the rotation in the present study are lower compared with those of Singh et al. [33] in Yamunanagar, Haryana where they reported that poplar-based agroforestry provides net returns INR 613,499 for a six-year rotation. This may be because this part of India is considered to have higher soil fertility and plentiful water availability compared with the semi-arid region of Haryana.

Three measures of economic worthiness normally used to compare various land-use systems are NPV, IRR, B:C ratio and LEV (Table 5).

The NPV in the study provides a realistic assessment of the benefits of systems through discounting the future value of present money. The maximum NPV of INR 228,149 and INR 217,753 were obtained from the southern aspect as well as northern aspect of the E–W rows, respectively, of poplar boundary plantations as the higher growth of poplar provided the highest return on trees (Table 5). The E–W and N–S boundary plantations performed significantly better; however, compared with sole cropping of sorghum-wheat crop rotation the NPV was negligible. The NPV values reported in this study are on the higher side than the studies of Karemulla et al. [59], where an 8-year-old boundary plantation of poplars provided a return of INR 101,000 per ha.

The internal rate of return (IRR) assesses the highest interest rate that a system can repay on loans. The highest IRR was calculated for the E–W row direction (88% for the southern and 82% for the northern aspect) of the poplar boundary plantation. In financial analysis, higher IRR rates that the discounting are accepted and provide enumerative returns on the investment. The eastern (63%) and southern (65%) aspects of N–S rows provided a comparatively lower IRR than the E–W rows of poplar boundary plantations (Table 5). In the present study, the IRR did not provide a precise estimate of the benefits of agroforestry spacing. Additionally, the maximum IRR was selected for the adoptability of the agroforestry system due to greater returns on investment. Using an IRR which is too high in the analysis provides a misleading and unrealistic picture. However, the Net present value is considered as more valid than the IRR in a profitability analysis [61].

A benefit-cost ratio is the most accepted and attractive parameter for analysis of agricultural commodities. A higher benefit-cost ratio for the sorghum-wheat cropping system was reported for the southern aspect (1.68) and northern aspect (1.65) of the E–W rows followed by the western aspect (1.30) in the N–S rows of the poplar boundary plantation. Lower values of the benefit-cost ratio were reported for the sole cropping of the sorghum-wheat rotation (1.1) and eastern aspect (1.28) (Table 5). The E–W boundary plantation is a more suitable direction from an efficiency and profitability point of view. A higher benefit-cost ratio (more than 1:2.00) has been reported for poplar bund agroforestry systems in the Indo-gangetic plains of India [33,34,59]. The study of Himshikha et al. [31] calculated NPV (INR 375,000 ha⁻¹), BCR (2.15) and IRR (120%) in poplar boundary plantations with a rice-wheat crop rotation in Uttar Pradesh (India), which is higher than the present study. It was estimated that the NPV was INR 375,000 ha. The BCR was calculated as 2.15:1 and the IRR was estimated to be 120.6% when calculated for six years. It was also calculated that the tree component contributed, on average, one third of the total gross returns in a poplar boundary plantation.

The Land Equivalent Ratio is the value of bare land in perpetual timber production in a tree plantation. There is very little literature on the LEV of agroforestry systems to provide the basis for a comparison. The LEV is adopted in the present study to illustrate the profitability of the agroforestry systems over sole cropping of crops and trees. The results of the study indicate that sorghum-wheat crop rotation in the southern aspect of E–W rows had the higher LEV (INR 1,248,791 ha⁻¹), followed by the northern aspect (INR 1,191,883 ha⁻¹) in the N–S rows of poplar bund plantations (Table 5). All of the agroforestry systems of the study reported higher LEVs compared with sole cropping (INR 93,402 ha⁻¹). Both the boundary plantations of poplar provided an 80% higher LEV compared with other sole cropping systems (crop and tree). Guo et al. [62] reported the highest LEV for rubber-tea intercropping, followed by rubber and tea monoculture in China. Additionally, the study of Bertomeu [63] reported higher profitability for two maize-agroforestry systems over maize monoculture in the Philippines. Recently Chavan et al. [9] compared two crop rotations under a three-planting geometry of poplars in Haryana, India, where sorghum-berseem cropping systems resulted in a higher LEV of INR 2,242,372 ha⁻¹ from 10 × 2 m² spacings.

4. Conclusions

The livelihood security of the farmer is one of the most important aspects of a country’s overall development. In India, around 70% of farmers have an annual per capita income of less than INR 15,000 and about 40 million farmers have only around 500 m² (0.05 ha) of land, which is barely sustainable. The reduced land holdings indicates that the numbers of small and marginal farmers are increasing in the era of climate change, which severely impacts their coping ability, vulnerability and food security. In addition, reduction of yield due to shade under tree-based systems is a barrier to adoption among farmers. Considering the distress of farming community as a national priority, improving farm income through crop diversification with agroforestry is one of the best available solutions. However, higher adoption depends on the attractive economic profitability over existing crop rotations. Therefore, this study provides a notable example that enhances farm income with the integration of tree components and demonstrates economic profitability of boundary plantations. Its wider adoption is vital due to increasing land pressure and the need for diversification of traditional cropping systems. Given this background, boundary planting of poplar in east–west and north–south directions performed better than a sorghum-wheat crop rotation. The overall crop yield reduction of poplar boundary plantation was 41.2% in the kharif season (sorghum) and 19.1% in the rabi season (wheat) throughout the rotation. The study also demonstrated the compensation ability of agroforestry tree species for the crop yield loss, and trees could be an insurance for farmers under extreme situations. Furthermore, economic analysis of the boundary systems indicates that the adoption of a tree-based system would help farmers to enhance total income (BCR: 1.29 from north–south and 1.67 from east–west plantings) in a semi-arid environment where traditional cropping is not economically viable (BCR of 1.05 from sorghum-wheat crop rotation). This extensive study over a period of 8 years recommends that east–west boundary plantations are adopted for better income generation from small land holdings.. This study could act as grassroot level example to farmers, policymakers and various stakeholders to adopt this attractive, profitable and sustainable practice under changing climate scenarios.