The study area is located within the Faculty of Forestry in Benhama, Ganderbal, Sher-e-Kashmir University of Agricultural Science and Technology of Kashmir (J&K), situated at approximately 34.2794° N latitude and 74.7717° E longitude. It is positioned at an altitude of 1790 meters (5872 feet) above mean sea level. The site lies in a mid- to high-altitude temperate zone, characterized by four distinct seasons. Winters (December–February) are long and severe, with temperatures commonly falling below – 4°C, frequent frost events, and substantial snowfall. Spring (March–May) remains cold and wet. Summers (June–August) are mild, with maximum temperatures reaching up to ~34°C, while autumn (September– November) is cool and marked by a rapid decline in temperature. The region receives an annual precipitation of approximately 1327 mm, of which a major proportion occurs as winter snowfall,

supplemented by spring rainfall distributed over nearly 70 precipitation days per year. The combination of low winter temperatures, moderate summer heat, and high winter precipitation creates a typical Western Himalayan temperate climate, making it suitable for fruit-based agroforestry research.

Layout of the Experimental Field

The experimental details and methodologies adopted in the present study are described as follows. The experiment was conducted under a horti-agricultural agroforestry system comprising both tree and crop components. The tree component consisted of apricot (Prunus armeniaca L.) and cherry (Prunus avium L.), while the agricultural intercrops included garlic (Allium sativum L.) and onion (Allium cepa L.). The apricot and cherry trees were three years old at the time of experimentation and were planted at a spacing of 3 m × 3 m, with rows oriented in the east–west direction to ensure uniform light distribution. The intercrops, garlic and onion, were grown between tree rows at a spacing of 30 cm × 10 cm.

Garlic Onion Apricot Cherry

The experiment comprised a total of ten treatments, which were laid out in a Randomized Block Design (RBD) with three replications. Each replication consisted of four plants per treatment, resulting in uniform experimental units across all treatments. This design was adopted to minimize experimental error and to facilitate reliable comparison of treatments under the agroforestry system.

The experimental field was ploughed, harrowed for smoothness, and subsequently planked. Manual removal of stones, pebbles, and residual debris was also carried out. In total, ten treatments viz., only Apricot (T1), only Cherry (T2), only Garlic (T3), only Onion (T4), Apricot + Garlic (T5), Apricot + Onion (T6), Apricot + Garlic + Onion (T7), Cherry + Garlic (T8), Cherry + Onion (T9) and Cherry + Garlic + Onion (T10) were employed. The plots were prepared as per the treatments to accommodate the vegetable crops (garlic and onion) during the rabi season.

Weeding was carried out promptly to keep the beds free of unwanted plants. Hoeing and irrigation were applied as needed, based on the crop's requirements. Harvesting of the vegetable crops (garlic and onion) was done in the month of June and July, respectively. For estimation of growth and yield parameters of vegetable crops (garlic and onion) and fruit trees (apricot and cherry), randomized block design were applied. The trees were spaced 3 meters apart in both directions (3m×3m), while the intercrops were planted with a spacing of 30 centimetres between rows and 10 centimetres between plants (30 cm× 10 cm). The details of treatments are presented in Table 1.

To assess crop growth parameters of (garlic and onion) such as plant height, bulb diameter, weight per bulb, weight per 100 cloves, and the number of cloves per bulb, ten plants were randomly selected from each plot at maturity for observation. The total biomass of both crops (garlic and onion) was evaluated by uprooting plants from each replication at the harvesting stage. The plants were separated into different parts, including bulbs (root) and aboveground portions, which were then weighed individually to determine their fresh weight. These samples were initially sun- dried for 4 to 5 days, followed by oven-drying at 60°C until a constant weight was achieved. The dry weight of the plant samples was recorded in grams and subsequently calculated in kilograms per hectare (kg ha⁻¹).

For estimating growth parameters of experimental trees viz., height (m), collar diameter (cm) were measured using a measuring tape (Stanley Model 33- 425). Five trees were randomly selected from each from each treatment for this purpose. The crown spread was determined using measuring tape on north to south and east to west directions. It was then calculated using the formula: (CS = D1 + D2/2).

Where, CS- Crown Spread, D1 – Crown diameter NS direction and D2- Crown diameter EW direction.

Table- 1 Details of treatment combinations

The leaf area of fully expanded leaves was estimated using a pre-calibrated portable leaf area meter. Each leaf was positioned under the leaf area meter's arm and digitally scanned to determine its area. Sixteen leaves per replication were chosen randomly for this assessment using a portable leaf area meter (CI-202 Portable Laser Leaf Area Meter). The fruit colour of apricot and cherry was determined using a colour chart through regular field visits. Fruit maturity was recorded as the period from the initiation of fruiting to the stage when the fruit reached full maturity, based on colour and size. At physiological maturity, all marketable fruits from each sample tree were harvested manually. The total number of fruits was counted, and their fresh weight was recorded using a calibrated digital weighing balance (accuracy ±1 g). Fruit yield was first expressed as kg tree⁻¹ and subsequently converted to t ha⁻¹ using the tree population per hectare based on the experimental spacing. The fruit length was measured from the base to the top using a measuring scale, and the diameter of fully mature fruits was measured in centimetres at the centre using a digital Vernier calliper (Aerospace Digital Vernier Caliper, 150 mm, accuracy

±0.01 mm,with both measurements taken from five randomly selected trees and five randomly selected fruits. The stone yield was recorded from fruits collected at their firm ripe stage, the stones were removed, weighed, and expressed in t ha⁻¹.

The cost of cultivation of vegetable crops (garlic and

onion) as well as maintenance of fruit trees (apricot and cherry) and harvest of its produce was worked out on the basis of net cropped area and number of tree ha-1 (Table-2). The requirements of labour and mechanical power for various activities like ploughing, harrowing, weeding, irrigation and harvesting were assessed per hectare according to the rates at the experimental farm. Costs for inputs like seedling and weeding were also calculated. The yield of agricultural crops and fruit trees was converted to gross returns using prevailing local market prices. Net returns were determined by subtracting the total cost from the gross returns. The data obtained was subjected to statistical analysis using a Randomized Block Design of experimentation as per the procedure suggested by Gomez and Gomez (1984). Data analysis was performed using R software.

In the present study the maximum value of sprouting time (14 days) were recorded in T5 (Apricot + Garlic), T7 (Apricot + Garlic + Onion), T8 (Cherry + Garlic) and T10 (Cherry + Garlic + Onion), whereas the minimum sprouting time (11 days) were recorded in T3 (Only Garlic). The possible explanation for this observation could be linked to the moisture content within the agroforestry system, creating cooler soil conditions compared to sole cropping. This alteration in moisture and consequent temperature variance might significantly impact the growth patterns and timing of sprouting in the intercropped vegetables, such as garlic, potentially elongating the duration required for complete sprouting. The results are similar with the findings of Yadav (2003). Plant height variations were also noted with T8 (Cherry + Garlic) exhibited the maximum height. The possible reason for this is when crops are grown in proximity to fruit trees, they tend to

become much taller and allocate most of their resources to vertical growth rather than lateral growth. The similar findings were reported by (Sayed et al., 2009). The information depicted in the table indicated that the maximum total biomass was recorded in T3 (Only Garlic). The data in the table showed that the total biomass values were higher in monoculture compared to agroforestry systems. This could be attributed to continuous and sufficient sunlight without obstruction, along with no competition between trees and crops for light, nutrients, or moisture in open conditions, aiding in the synthesis of food materials has also been documented by (Sayed et al., 2009). The other parameters such as diameter of bulb, weight per bulb, weight per 100 cloves, number of cloves per bulb were recorded maximum in T3 (Only Garlic) (Table-4). The reason for less growth performance of garlic in intercropping is due to high root competition between the crops and trees in the upper soil layer, potentially leading to a substantial decline in crop yield. This reduction is also influenced by decreased light interception and stronger below- ground competition in tree–crop interfaces, which are well-known constraints in vegetable production under partial shade. The reduced growth performance observed in intercropping systems aligns with prior research highlighting high root competition and shading as significant factors contributing to diminished crop yields (Patil, 2010).

In the present findings from the research revealed that the growth and yield parameters of onion were significantly affected by different treatments under apricot and cherry-based agroforestry system. Table-

5. The data revealed that highest value of plant height was recorded in T9 (Cherry +Onion). This increase in height can be attributed to altered light availability and microclimatic conditions created by the partial shading of fruit trees, which may induce vertical growth as an adaptive response. Consequently, this

proximity could lead to an increase in overall plant height while potentially impeding the proper development of onion bulbs (Yadav 2003).

Similarly, total biomass, diameter of bulb, weight per bulb, were recorded highest in T4 (Only Onion). The maximum value for growth and yield parameters were noted in the open (monoculture) system compared to an agroforestry setup. The possible reason for this is increased accessibility of light, area, water and nutrients in a singular cropping approach compared to the intercropped field. In sole cropping onions have access to full array of nutrients, water and sunlight without having to share them with other crops. This allows them to develop larger diameters, heights and biomass as they allocate more resources to their growth. In mixed cropping, onions often have to compete for essential resources, resulting in reduced growth and yield (Ferdous et al., 2022). These findings clearly demonstrate how reduced light interception and intensified root interactions under tree canopies restrict bulb development in onions.

The economic assessment of various cropping systems showed higher returns from agroforestry system rather than sole cropping (Table-8) indicated that the cost of cultivation from intercrops were found maximum in T4 (Only Onion). However, for fruit trees the maximum cost of cultivation was incurred in T2 (Only Cherry), T8 (Cherry + Garlic), T9 (Cherry

+ Onion) and T10 (Cherry + Garlic + Onion). Sole cropping

requires higher inputs like fertilizers, water, and labour, while agroforestry reduces costs through better resource use, nutrient cycling, and natural pest control (Singh et al., 2022).

The gross and net returns from intercrops were obtained minimum when intercrops were cultivated in conjunction with fruit trees as opposed to sole cropping. The maximum gross return and net return from intercrops was found to be in T3 (Only Garlic) Sole cropping often yields higher returns due to focused management and efficient resource use, while agroforestry may face reduced intercrop yields due to competition and complex management (Singh et al., 2022). However, the gross and net returns from fruit trees were obtained maximum when intercrops were cultivated in conjunction with fruit trees. The maximum gross return and net return from fruit trees was calculated in T7 (Apricot + Garlic + Onion) The possible reason for this could be the interplay between fruit trees and intercrops in agroforestry enhances overall productivity, mitigates risks and reduces input costs. This dynamic interaction results in higher gross and net returns as observed in T7 (Apricot + Garlic + Onion) surpassing the relatively limited productivity of sole cropping, as seen in T2 (Only Cherry) (Dutt and Thakur 2020).

The total net return was maximized when intercrops were grown in association with fruit trees rather than sole cropping. The maximum total net return was obtained in T7 (Apricot + Garlic + Onion). The total net return was

Table 5: Average values for the growth and yield parameters of onion under apricot-cherry based agroforestry system

significantly elevated in agroforestry systems compared to the sole cropping of Garlic and Onion. The increased net returns in agroforestry interventions stem from additional income derived from fruit trees, an advantage absent in sole cropping (Dutt and Thakur

2020). The study indicates that cultivating Garlic and Onion alongside Apricot and Cherry trees ensures consistent income through agroforestry.

Analysis of the data present in Table-8 unveiled that highest benefit-cost ratio among treatments was noticed when intercrops were cultivated alongside fruit trees rather than in sole cropping. The highest benefit-cost ratio in T7 (Apricot + Garlic + Onion). Agroforestry system tend to benefit from diversified income sources, reduced input costs and enhanced ecological resilience, contributing to higher overall returns relative to the investment made compared to the sole cropping (Bhat et al. 2019; Singh et al., 2022). These economic gains also reflect ecological processes such as nutrient recycling, moderated microclimates, and improved soil moisture retention, all of which collectively enhance long-term system sustainability and profitability.

Table 6: Relative economics of different treatments