Adoption of management practices and impacts on major diseases among mandarin growers in Syangja, Nepal

Abstract

A study was conducted from February 2021 to May 2021 to assess the incidence and severity of major diseases of Mandarin and the management practices adopted by mandarin growers in Syangja, Nepal. Data were collected from a total of 90 mandarin-growing farmers and 25 orchards, comprising 10 from Putalibazar, 8 from Bhirkot, and 7 from Waling municipalities. Descriptive statistics such as percentage, mean, standard deviation, and range, as well as inferential statistics like the chi-square test and independent sample t-test, were employed alongside analytical tools like binary logistic regression to analyze the data. The findings revealed the highest incidences of citrus greening (27%) and foot rot (36%) in Putalibazar Municipality and sooty mold (63.75%) in Bhirkot Municipality, whereas the most pronounced severity of citrus greening and sooty mold was observed in Waling Municipality. Training, pruning, and the use of Bordeaux mixture were the major practices adopted by farmers for the management of citrus greening and sooty mold, respectively, whereas for the management of foot rot, both Bordeaux mixture and cow’s urine were used. A significant mean difference was found in average production per plant, nursery height, and marketed yield between trained and non-trained farmers. Factors such as mandarin cultivated area, farming experience, and access to technical assistance were found to influence management practices, including the application of Bordeaux mixture, the use of Jhol-mol, neem-based pesticides, and insect traps. Besides, the findings also indicate the need for targeted training programs and technical support for growers, emphasizing disease-specific management strategies.

Keywords:

• Bordeaux mixture
• citrus greening
• foot rot
• incidence
• severity
• sooty mold

Reviewing Editor:

• Manuel Tejada, Universidad de Sevilla, Spain

Subjects:

• Agriculture & Environmental Sciences
• Botany
• Biology
• Epidemiology
• Statistics & Probability

1. Introduction

Citrus, belonging to the family Rutaceae, stands as one of the world’s major fruits, cultivated extensively across the globe. In the context of Nepal, citrus holds significant importance as one of the major fruit crops in terms of area coverage, production, and export potential (Kaini, 2019). It is mainly grown in the tropical and subtropical regions of Nepal. Lama et al. (1988) reported the suitability of climatic conditions, especially in mid-hill regions of Nepal with an altitude range of 800 m to 2100 m from east to west of the country, for citrus fruit cultivation. Citrus fruit significantly enhances the household economy in hilly and mountainous districts, contributing approximately 26.84% to the total fresh fruit production in Nepal (MoALD, 2020). It is cultivated in about 60 districts of the country, contributing 3% of total fruit exports by volume (Dahal et al., 2020). The three main citrus species grown commercially in Nepal are mandarin (Citrus reticulata), sweet orange (Citrus sinensis), and lemon (Citrus aurantifolia). Among them, mandarin is the most common citrus fruit grown in the mid-hill region of Nepal, with a comparative advantage of climatic conditions predominantly between the altitude ranges of 1000 and 1500 m above sea level (Asbin et al., 2022). Despite better climatic and soil conditions, citrus yield has subsequently declined in recent years (Kaini, 2019).

According to Subedi and Acharya (2008), the low and stagnant productivity, as well as the decline of citrus in Nepal, can be attributed to various biotic and abiotic factors. Among the constraints contributing to this decline, including the lack of healthy seedlings, insect pests, and poor orchard management practices, citrus greening stands out as a major problem leading to a severe reduction in mandarin production in Nepal (Paudyal, 2016; Roistacher, 1996). Another destructive disease affecting citrus, foot rot, caused by the moisture-loving fungus Phytophthora spp., is responsible for yield losses ranging from 10% to 30% in major citrus-producing countries globally (Choudhary et al., 2021). Additionally, common diseases like powdery mildew and sooty mold also contribute to the decline of citrus, as reported in the Gandaki Province of Nepal (Belbase et al., 2020).

Ichinose et al. (2012) observed that guava intercropping along with citrus resulted in a low incidence of Citrus psylla over two years, thereby reducing the risk of citrus greening.

The productivity of citrus could be enhanced, coupled with reduced chances of greening, through the adoption of proper training and pruning practices (Singh and Kaur, 2019). An experiment conducted in Guangzhou, China, aimed at assessing the efficacy of petroleum spray oil against citrus psylla revealed that as oil concentrates increased from 0.25% to 1%, there was a significant decrease in psylla populations (Taylor et al., 2010). Furthermore, the incidence of citrus fruit greening saw a considerable reduction through trunk injections of tetracyclines into severely affected trees (Vuuren, 2010).

In a field trial focusing on foot rot management, treatments such as metalaxyl M paste, metalaxyl M soil application, and Fosetyl Al spray in mid-February, March, and August demonstrated significant effectiveness, resulting in notable outcomes like maximum lesion size recovery (88.9%), fruit yield (58.5 kg/plant), and canopy volume (16.9 m³) (Singh et al., 2015). Additionally, Trichoderma harzianum soil application, combined with Bordeaux paste and copper oxychloride spray, led to a 54.7% lesion recovery, while garlic bulb extract paste and spray achieved a 47.4% recovery. Fosetyl-Al was also identified as an effective treatment for foot rot management in a previous study (Davino et al., 1990).

Citrus canker can be effectively managed by spraying streptomycin sulfate at concentrations ranging from 100 to 1000 ppm. The application of Bordeaux paste and Bordeaux mixture (4:4:50) on parts affected by gummosis and foot rot has shown high effectiveness in reducing disease incidence (Ahlawat & Pant, 2003). Managing soil-borne pathogens requires the crucial use of disease-free plant material, implementing quarantine and sanitary measures wherever possible to prevent disease introduction (Naqvi, 2006). Additionally, disease reduction and increased mandarin yield have been evident through timely irrigation along with micronutrient spray (Abbas & Fares, 2009).

Despite the availability of improved varieties, advanced packages of practices, and scientific technology, a substantial gap exists between the yields of mandarin orchards recorded at the research farm and their production in farmers’ fields. This survey research aims to investigate the incidence and severity of major diseases as well as the management practices adopted by mandarin growers in Syangja, Nepal. The identification of biological, technical, and socioeconomic constraints affecting decisions regarding the adoption of appropriate management practices in mandarin orchards, coupled with an assessment of disease management practices, will help distinguish between current practices and the ideal ones to be followed. Furthermore, the findings are expected to serve as a foundation for enhancing existing management practices in mandarin orchards, thereby increasing production efficiency in the study area and in similar contexts.

2. Materials and methods

2.1. Study site and selection of study area

The study was conducted in mandarin-growing areas of Syangja district, specifically in Putalibazar municipality, Bhirkot municipality, and Waling municipality. The research covered 3–5 wards in each municipality. These areas were chosen due to their location within the command area of the mandarin super-zone and their significance as major sites for mandarin cultivation (Figure 1).

Figure 1. Map of the study site.

2.2. Sample size and sampling technique

The mandarin-growing farmers interviewed were selected from the list of registered mandarin farmers at the Agriculture Knowledge Center (AKC) in Syangja. These three municipalities under study had a total of 109 registered mandarin farmers. Raosoft Software was used to determine the representative sample size. With a minimum recommended size at a 5% margin of error and a 95% confidence level, the sample size was found to be 86. For convenience, 90 farmers were selected for the study, with 30 from each municipality for data collection about adopted management practices. Simple random sampling was used to select the respondent farmer from the respective list of farmers belonging to a specific municipality among the three municipalities.

Additionally, 25 orchards (10 from Putalibazar, 8 from Bhirkot, and 7 from Waling) were chosen for incidence and severity assessment as representatives of these municipalities. The orchards generally varied in size based on the varieties and cultivars planted. The choice of assessing 10 trees was specific to foot rot and aimed at observing the collar region. However, for sooty mold and citrus greening, five suspected leaves from each of the 10 selected trees per orchard were examined for both diseases. In the study areas, orchards typically comprised 20–25 mandarin plants per ropani.

Therefore, for each disease assessment, 10 plants were considered, resulting in a total of 50 suspected leaves per orchard, 5 per plant, for citrus greening and sooty mold. These trees were sampled by creating two diagonal transects across the orchard in the form of an “X” (5 plants in each diagonal) at each orchard.

2.3. Research design for the incidence and severity of diseases

2.3.1. Procedure for the iodine test

Citrus huanglongbing (HLB) suspected leaves were collected in a paper envelope from mandarin trees. The collected leaves were tested using the scratch test with a formulation of iodine solution at 1.3% (50 mM), similar to some commercially produced laboratory iodine solutions. A small piece of abrasive sandpaper was used to scratch the upper surface of an infected leaf. The tissue scrapings were then gently washed off the abrasive paper in distilled water by carefully rubbing the polythene bag by hand. Subsequently, a drop (about 30–50 μl) of iodine solution (1.3%) was added, and the mixture was left for 2–3 minutes. Healthy controls, using healthy leaves, were subjected to similar testing. The background color of the control test for each type of paper was also observed for confirmation.

As the iodine test is not necessarily a confirmatory method for citrus greening and visual symptoms are always dubious in providing certainty in assessing the other two diseases, the samples collected from specific suspected plant parts were subjected to laboratory analysis for the confirmation of pathogens. Microscopic examination, along with bacterial colony evaluation, was conducted for citrus greening, and mycelial culture evaluation was performed for sooty mold and foot rot, followed by final confirmation through molecular analysis using the PCR technique.

2.3.2. Assessment of disease incidence

The tree density at each farm was maintained at 20–25 mandarin plants per ropani, equivalent to around 200–250 plants per 10 ropani. To assess disease incidence, ten productive trees were systematically selected within each orchard at every location as representative of the orchards under study. A scratch test was conducted to determine the incidence of citrus greening, while visual symptoms were observed for sooty mold and foot rot. $$\mathit{\text{Disease\hspace{0.33em}incidence\hspace{0.33em}}}=\frac{\mathit{\text{Total no}}.\text{\hspace{0.33em}of\hspace{0.33em}infected\hspace{0.33em}plants}}{\mathit{\text{Total\hspace{0.33em}no}}.\text{\hspace{0.33em}of\hspace{0.33em}observed\hspace{0.33em}plants}}\times 100$$

2.3.3. Assessment of disease severity

The severity of diseases in mandarin plants was assessed using a scoring system outlined by Masood et al. (2010), as depicted in Table 1. For sooty mold and citrus greening, assessment relied on suspected leaves for determining severity, while for foot rot, the collar region of suspected plants was observed and scoring was conducted.

Table 1. Scale for the assessment of damage caused by disease in Mandarin.

Score	Disease Severity
0	No disease symptoms
1	25% of the leaf and collar area affected
2	26–50% of the leaf and collar area affected
3	51–75% of the leaf and collar area affected
4	76–100% affected, including dead trees

Based on the scores obtained, disease severity was calculated using the following formula: $$\mathit{\text{Disease\hspace{0.33em}index}}=\frac{\text{Sum\hspace{0.33em}of\hspace{0.33em}all\hspace{0.33em}scores}}{\text{Total \hspace{0.33em}no}.\text{\hspace{0.33em}of\hspace{0.33em}plants\hspace{0.33em}assessed\hspace{0.33em}}\times \text{\hspace{0.33em}Maximum \hspace{0.33em}score}}$$

2.4. Survey design and data collection techniques

2.4.1. Preliminary field visit

During the preliminary field visit, essential background information about the study area was acquired. This information was used in formulating the interview schedule and devising a sampling framework.

2.4.2. Pre-testing of the questionnaire

The questionnaire was pre-tested before the field survey to assess the reliability and validity of the interview schedule through interviews with five key farmers. In response to the feedback from the respondents, necessary changes were made to the questionnaire.

2.4.3. Field survey

Mandarin growers at the study site responded to a series of open-ended and closed-ended questionnaires, facilitating the collection of valuable data on disease management practices. The data collected encompassed both qualitative and quantitative variables from various sources.

2.4.4. Focus group discussion (FGD)

After the field survey, a focus group discussion (FGD) was conducted using checklists to validate the collected data. Participants in the FGD included mandarin growers from diverse ethnic groups and both genders. The growers were brought together for a discussion to elicit information on various disease management practices adopted by them.

2.4.5. Key informant interview (KII)

A series of questions were posed to key informants, including progressive farmers, representatives of farmer groups and cooperatives, super zone and AKC officers, as well as NGO and INGO officers. The inquiries aimed to gather insights into the current state of disease management practices adopted in Syangja district.

2.5. Methods and techniques of data analysis

The data collected from the survey were coded, tabulated, and analyzed using Microsoft Excel and the Statistical Package for Social Science (SPSS). Descriptive statistics such as frequency and percentage were calculated to determine the distribution of the study variables. The chi-square test and correlation analyses were used to test the significant differences between the variables under investigation. The disease incidence percentage was calculated, and preferential ranking was also carried out.

2.5.1. Descriptive statistics

Descriptive statistics, including frequency, percentage, mean, standard deviation, and range, were employed to analyze socio-economic factors affecting the adoption of disease management, such as age, gender, education level, and the active members of the family. Active members refer to family members fully dedicated to mandarin cultivation, committing their entire productive time of the day to this activity. The numerical statistics of these active members are presented in Table 2.

Table 2. Binary logistic regression analysis of dependent and independent variables.

Variables	Odds ratios
	Application of Bordeaux paste	Use of Jhol-mol	Use of neem based pesticides	Use of traps for insects
Active members of the family	1.461**	1.346*	1.348**	1.074
Farming experience	1.805***	1.557***	1.052	1.095
Mandarin cultivated area	0.996	1.021	1.090*	1.178***
Access to technical assistance	3.012*	2.375	2.884**	5.682**

Note: *, **, and *** represent levels of significance at the 10%, 5%, and 1% levels, respectively.

2.5.2. Chi-square test or test of independence

To investigate the independence or association between two variables, the chi-square test was applied and tested at significance levels of 0.05 and 0.01 for different degrees of freedom. The formula used for this analysis is as follows: $$X^2=\sum \frac{{\left(O_{\mathit{\text{ij}}}-E_{\mathit{\text{ij}}}\right)}^2}{E_{\mathit{\text{ij}}}}$$

Where χ² = Chi-square

${ O}_{\mathit{\text{ij}}}$ = observed frequency of each ij^th term

$E_{\mathit{\text{ij}}}$= expected frequency of ij^th term

i = 1, 2, 3,…,r.

j = 1, 2, 3,…,k.

The degrees of freedom (df) for the chi-square test were calculated as (c − 1)(r − 1), where c is the number of columns and r is the number of rows.

2.5.3. Ranking of constraints and problems by scaling technique

Various problems faced by Mandarin growers during the production and marketing of fruits were presented on a five-point scale with severity levels categorized as most severe, severe, moderate, mild, and most mild, corresponding to scale values of 1, 0.8, 0.6, 0.4, and 0.2, respectively. These constraints were assessed through group discussions and other participatory approaches and ranked using indexing, computed with the following formula (Pandey et al., 2023): $$\mathrm{\text{Iimp}}=\sum \frac{\left(\mathit{\text{Sifi}}\right)}{N}$$

Here, I_imp represents the index of importance, S_i stands for the scale value, f_i denotes the frequency of respondents, and N indicates the total number of respondents.

2.5.4. Binary logistic regression analysis

Binary logistic regression was employed to analyze the influence of factors such as the presence of active family members, years of experience, cultivated mandarin area, and access to technical assistance on the adoption of disease management practices for diseases and pests. Table 3 presents a descriptive overview of the binary logistic regression model, detailing the dependent variables (outcomes) and the independent variables (predictors) considered in this study.

Table 3. Description of the model used in binary logistic regression.

Dependent variables (Outcomes)	Independent variables (Predictors)
Application of Bordeaux mixture	An active member of the family
Use of Jhol-mol	Farming experience
Use of neem-based pesticides	Mandarin-cultivated area
Use of traps for insects	Access to technical assistance

3. Results and discussions

3.1. Socio-demographic characteristics of respondents

Table 4 depicts the socio-demographic characteristics of household heads (respondents). The average age of respondents was 53.33 years, with a standard deviation of 13.51. The average family size was 5.92. The majority of respondents (75.6%) were male, and the main source of income for the majority (82.2%) was agriculture. The average cultivated mandarin area among the interviewed respondents was 9.43 ropani, with a standard deviation of 5.75.

Table 4. Socio-demographic characteristics of mandarin-growing farmers in the study area.

Variables	Mean	Standard Deviation
Age (years)	53.33	13.51
Family Size	5.92	2.51
Gender (male = 1, female = 0)	0.76	0.43
Source of Income (Agriculture = 1, otherwise = 0)	0.82	0.38
Mandarin Orchard Size (Ropani)	9.43	5.75

Figure 2 shows that the majority of the respondents in the study area were Brahmin (68.9%), followed by Janajati (15.6%), Chhetri (12.2%), and Dalits (3.3%). Similarly, Figure 3 presents the education level of respondents involved in mandarin farming. The highest number of respondents acquired secondary level education (26.70%), followed by illiterate (24.40%), higher secondary (24.40%), lower secondary (13.30%), bachelors and above (6.70%), and primary (4.40%).

Figure 2. Ethnicity of Mandarin-growing respondents in the study area.

Figure 3. Education level of the Mandarin-growing respondents in the study area of Syangja, 2021.

3.2. Incidence and severity of diseases in different municipalities

3.2.1. Incidence of major diseases

The incidence of citrus greening was recorded as the highest (27%) in Putalibazar, followed by Bhirkot (22.5%) and Waling (17.14%) municipalities, as shown in Figure 4. Similarly, the incidence of sooty mold was highest in Bhirkot municipality (63.75%), followed by Waling municipality (61.43%), and Putalibazar municipality (59%). Furthermore, the incidence of foot rot was highest in Putalibazar municipality (36%), followed by Bhirkot municipality (32.5%) and Waling municipality (27.14%). The variation in incidence across different areas could be attributed to factors such as initial inoculum levels, as suggested by Gottwald (1989), or differences in the management practices adopted by farmers (Rasowo et al., 2019).

Figure 4. Disease incidence in different orchards in the study area of Syangja, 2021.

3.2.2. Severity of major diseases

The study findings revealed that the severity of citrus greening was higher in Waling (0.15), followed by Putalibazar (0.13), and Bhirkot municipalities (0.12), as illustrated in Figure 5. Similarly, the severity of sooty mold was higher in Waling (0.36), followed by Bhirkot (0.32), and Putalibazar municipalities (0.31). Moreover, the severity of foot rot was more pronounced in Bhirkot (0.19), followed by Waling (0.18) and Putalibazar municipalities (0.13). This observed variation in severity could be attributed to differences in the management practices adopted by farmers, as highlighted by Rasowo et al. (2019). The elevated incidence and severity of diseases in specific areas may also be influenced by the prevailing climatic conditions, as suggested by MacNeill (1980). Furthermore, the heightened severity in a particular region might be correlated with the age of orchards, as proposed by Singh et al. (2015).

Figure 5. Disease severity in different orchards in the study area of Syangja, 2021.

3.2.3. Adoption of orchard management practices

In the study area, the majority of farmers (90%) were engaged in training and pruning activities as orchard management practices, while 10% did not perform such practices. Significantly, training and pruning were predominantly carried out in December and January, post-harvest, during the dormant period. Regarding chemical applications, 83.3% of the farmers utilized Bordeaux mixture and paste, while the remaining 16.7% lacked access to such chemicals, limiting their usage. Additionally, 65.3% of the farmers conducted soil tests, while 34.7% refrained, citing the absence of soil testing programs in their localities as the reason. Furthermore, over half of the orchards lacked access to irrigation facilities.

Similarly, most of the mandarin orchards (90%) in the study area were established without considering the recommended spacing between mandarin trees, as indicated in Table 5. The majority of respondents engaged in intercultural operations such as weeding (94.44%), mulching (71.11%), and intercropping (63.33%). Grass from weeding and tree leaves were the primary materials used for mulching, as they were readily available in surplus in the village and could later be incorporated as manure in standing fields. Among respondents practicing intercropping, the majority planted maize. Only a minority (27.3%) of farmers used micronutrients in their orchards, while 72.7% did not. Farmers using micronutrients applied a mixture of Zn micronutrient (V-tamin) with Rogor (Dimethoate 30% EC) and a sticker (glue-like) at the rate of 1 ml of V-tamin and 1 ml of Rogor per liter of water.

Table 5. Adoption of various orchard management practices by mandarin growers in the study area.

S.N	Management Practices	Frequency of Respondents
		Yes	No
1.	Training Pruning	81 (90)	9 (10)
2.	Use of Bordeaux mixture and paste	75 (83.33)	15 (16.67)
3.	Soil Testing	59 (65.56)	31 (34.44)
4.	Intercultural Operations
4.1	Spacing	9 (10)	81 (90)
4.2	Irrigation	43 (47.8)	47 (52.2)
4.3	Weeding	85 (94.44)	5 (5.56)
4.4	Mulching	64 (71.11)	26 (28.89)
4.5	Intercropping	57 (63.33)	33 (36.67)
5.	Micronutrient Application	26 (28.89)	64 (71.11)
6.	Insect Control	35 (38.89)	55 (61.11)

Figures in parentheses indicate percents.

The majority of farmers (61.11%) did not adopt any insect control measures, followed by 27.78% who adopted both mechanical and chemical control and 11.11% who adopted only mechanical control. The main chemicals used by farmers for insect control in the study area included pheromone traps, Rogor, Cypermethrin, Serbo oil, and protein baits.

3.3. Description regarding the adoption of disease management practices

3.3.1. Appearance of diseases

Three major diseases were taken into consideration: citrus greening, sooty mold, and foot rot. The study reveals that for sooty mold, 66.7% of the respondents reported it appearing in their orchard 3–9 years ago, 20% reported it appearing more than 9 years ago, and 13.33% reported it appearing less than 3 years ago. Similarly, for citrus greening (or greening-like symptoms), 58.89% reported it appearing in their orchard less than 3 years ago, followed by 30% reporting it appearing 3–9 years ago, and 11.11% reporting it appearing more than 9 years ago. These findings are consistent with Kharal and Bhandari (2019), who did not report citrus greening as a major disease in mandarin orchards in Syangja a couple of years ago, and its incidence has escalated in recent years. Lastly, for foot rot disease, 68.89% of respondents reported it appearing in their orchard 3–9 years ago, 16.67% reported it appearing more than 9 years ago, and 14.44% reported it appearing less than 3 years ago (Table 6).

Table 6. Appearance of major diseases in the mandarin orchard in Syangja (2021).

Diseases	Disease appearance in orchards (frequency)
	<3 years	3–9 years	>9 years
Sooty mold	12 (13.33)	60 (66.67)	18 (20)
Citrus greening	53 (58.89)	27 (30)	10 (11.11)
Foot rot	13 (14.44)	62 (68.89)	15 (16.67)

Figures in parentheses indicate percents.

3.3.2. Disease management strategies

The majority of the respondents (80%) had adopted various management strategies to control diseases in their mandarin orchards, while 20% did not use any control measures. Among the 80% of respondents implementing disease control measures, 61.11% adopted both mechanical and chemical methods. The most common practices included training pruning and the application of Bordeaux mixture and paste. Following this, some respondents opted for mechanical control only, and 7.78% applied local practices to control diseases. These local practices involved the use of kerosene, cow urine, red soil, and cow dung (Table 7).

Table 7. Disease management methods adopted by respondents.

Disease management methods	Frequency	Percentage
Mechanical methods	10	11.11
Mechanical and chemical methods	55	61.11
Other local practices	7	7.78
No management practices adopted	18	20
Total	90	100.0

3.3.3. Management of citrus greening

Approximately 31.11% of respondents were familiar with citrus greening, and only 21.11% knew about the transmission of this disease. The majority of respondents (91.11%) did not practice any management measures, while 8.89% implemented training pruning for its control. The recommended measures for controlling citrus greening include the use of healthy planting material inside screen houses in nurseries at an elevation higher than 1300 m (as the vector of the disease, citrus psylla, is less active above this height), plant quarantine, management of citrus psylla, and conducting a greening test on infected plant leaves through PCR. Besides, infected plants need to be destroyed according to the guidelines (MOAD & FAO, 2011). The lag in knowledge could potentially contribute to the high disease incidence in mandarin orchards, leading to a subsequent decrease in production. During the survey, farmers were asked about the reasons behind their inability to manage pests effectively in the orchard. Each respondent experiencing higher disease incidence cited the lack of training and knowledge about disease management as a major contributing factor. This underscores the crucial role of knowledge gaps in hindering farmers from implementing effective pest control measures, ultimately impacting orchard health and yield (Figure 6).

Figure 6. Management practices adopted by farmers to control citrus greening.

3.3.4. Management of sooty mold

The study revealed that 61.11% of the respondents applied the Bordeaux mixture to manage sooty mold, while 25.56% did not practice any management strategies for sooty mold. The remaining 13.33% of the respondents used chemicals like Rogor for sooty mold management. The recommended practice involved controlling scale insects, leaf miners, and other sucking insects using specific measures like Imidacloprid for scale insects, Spinosad for leaf miners, and Cypermethrin and Malathion for sucking insects. However, due to their easy availability and broad-spectrum application, growers primarily relied on Rogor and Bordeaux mixtures as general pest management methods, lacking a clear understanding of the etiology and nature of the damage caused (Figure 7).

Figure 7. Management practices adopted by farmers to ­control sooty mold.

3.3.5. Management of foot rot

The study revealed that 56.67% of the respondents didn’t practice any management practices to control foot rot, while 37.78% used Bordeaux mixture and paste, and 5.55% used cow urine. The recommended practices include the use of grafted saplings as planting material, pruning of the infected parts, and drenching with a 1% Bordeaux mixture (MOAD & FAO, 2011) (Figure 8).

Figure 8. Management practices adopted by farmers to ­control foot rot.

3.4. The influence of independent factors on different management practices

3.4.1. Comparison of categorical variables among municipalities

The overall average of technical service received was 46.6%. The average technical service received by farmers in Putalibazar municipality was higher (66.7%), followed by Bhirkot municipality (33.3%) and Waling municipality (13.7%), which was found statistically significant at a 5% level of significance, as shown in Table 8. This difference might be attributed to the proximity of Putalibazar municipality to the Mandarin Superzone and Agriculture Knowledge Center, given that Putalibazar municipality serves as the district headquarters of Syangja and hosts various agriculture-related offices. This statement is supported by the fact that regular contact, attendance at trainings, obtaining assistance, communication, and interactions between farmers and agriculture technicians commonly occur in this area. This observation is further reinforced by the findings of a higher number of trained farmers in Putalibazar municipality compared to the other two municipalities under study. Similarly, the overall average of training pruning practice was found to be 90%. Farmers in Bhirkot municipality demonstrated a higher average training pruning practice (96.7%), followed by Waling municipality (93.3%) and Putalibazar municipality (80%), which was statistically significant at a 10% level of significance.

Table 8. Different management practices adopted by farmers in different municipalities.

Variables	Putalibazar (n = 30)	Bhirkot (n = 30)	Waling (n = 30)	Overall (N = 90)	Chi-square	P-value
Technical service received
No	10(33.3)	20(66.7)	19(63.3)	49(54.4)	8.153**	0.017
Yes	20(66.7)	10(33.3)	11(13.7)	41(46.6)
Training and pruning practice
No	6(20)	1(3.3)	2(6.7)	9(10)	5.026*	0.081
Yes	24(80)	29(96.7)	28(93.3)	81(90)
Use of Bordeaux mixture
No	4(13.3)	5(16.7)	6(20)	15(16.7)	0.480	0.787
Yes	26(86.7)	25(83.3)	24(80)	75(83.3)
Use of Jhol-mol
No	11(36.7)	7(23.3)	10(33.3)	28(31.1)	1.348	0.510
Yes	19(63.3)	23(76.7)	20(66.7)	62(68.9)
Adoption of Mulching Practice
No	8(26.7)	9(30)	9(30)	26(28.9)	0.108	0.947
Yes	22(73.3)	21(70)	21(70)	64(71.1)

Note: Figures in parentheses indicate the percentage. * and ** indicate a 10% and 5% level of significance, respectively.

3.4.2. Comparison of production-related variables (continuous variables) by the training status of farmers

Trained farmers are characterized by their participation in agriculture-based training sessions offered by agricultural experts or organizations such as the Prime Minister Agriculture Modernization Project (PMAMP), the Agriculture Knowledge Centre (AKC), and local entities. These training sessions specifically concentrate on enhancing mandarin farming practices, encompassing disease management campaigns and programs. In contrast, non-trained farmers lack exposure to such specialized training initiatives.

The study revealed an average production of 39.81 kg per mandarin plant among the farmers involved in mandarin cultivation. The average production per plant from trained farmers (44.62 kg) was statistically higher than that from non-trained farmers (36.14 kg) at a 5% level of significance. Similarly, the average height of the sapling or nursery was 1152.89 m. The average height of a nursery or sapling from trained farmers (1181.03 m) was statistically higher than the height of a nursery from non-trained farmers (1131.37 m) at the 10% level of significance. Furthermore, the average amount of manure used was 44.61 kg. The average marketed yield was 5469.00 kg per year. The average marketed yield from trained farmers (7933.21 kg/year) was statistically higher than that of the average marketed yield from non-trained farmers (3584.61 kg/year) at a 1% level of significance. Training proves to be beneficial in making farmers aware of the benefits of various management practices and encouraging their adoption. Therefore, training on orchard management practices has a positive and significant impact on production attributes. This finding is also consistent with the studies by Genius et al. (2014) and Ashraf et al. (2015) (Table 9).

Table 9. Comparison of production-related variables (continuous variables) by training.

Variables	Overall (N = 90)	Training (Yes) (n = 39)	Training (No) (n = 51)	Mean difference	t- value	p-value
Average production per plant (kg)	39.81	44.62	36.14	8.478	2.033**	0.045
Nursery height (m)	1152.89	1181.03	1131.37	49.653	1.803*	0.075
Manure used (kg)	44.61	44.49	44.71	−0.219	−0.054	0.957
Marketed yield (kg)	5469.00	7933.21	3584.61	4348.597	3.152***	0.002

Note: *, **, and *** indicate significant at the 10%, 5%, and 1% level of significance, respectively.

3.5. Factors affecting the adoption of management practices for diseases and pests

3.5.1. Factors affecting the adoption of the application of Bordeaux mixture or paste

The results showed that active members of the family had a positively significant impact (p < 0.05) on the application of the Bordeaux mixture or paste. This implies that with an additional unit increase in a family member, the odds of applying Bordeaux paste increase by a factor of 1.461, keeping all other variables constant. Family size generally serves as a source of labor force in the study area, and a larger family might facilitate the adoption of these labor-intensive practices (Doss, 2006).

Similarly, farming experience had a positively significant impact (p < 0.01) on the application of Bordeaux mixture or paste. This means that the amount of a Bordeaux mixture applied increases by a factor of 1.805, with an additional increase in years of farming experience. These findings align with those of Dhital and Joshi (2016), who observed a positive association between farming experience and the level of adoption.

Moreover, access to technical assistance had a positively significant impact on the application of Bordeaux paste at a 10% level of significance. The odds of applying Bordeaux paste by farmers with access to technical assistance were 3.012 times higher than those of farmers without access to technical assistance, as shown in Table 2. Poudel et al. (2021) also reported a positive relationship between access to extension agents and technology adoption.

3.5.2. Factors affecting the use of Jhol-mol

The results showed that active members of the family have a positive and significant impact (p < 0.1) on the use of Jhol-mol. This indicates that with each additional increase in active members in the family, the use of Jhol-mol increases by 34.6%. Farming experience also had a positively significant impact on the use of Jhol-mol, significant at a 1% level. With each additional increase in years of farming experience, the odds of farmers using Jhol-mol were found to increase by 1.557 times (Table 2).

3.5.3. Factors affecting the use of neem-based pesticides

The results showed that the odds of farmers using neem-based pesticides increased by 1.348 times with each additional increase in active members in the family (p < 0.05). Mandarin-cultivated areas had a positively significant impact (p < 0.1) on the use of neem-based pesticides. This means that the odds of farmers using neem-based pesticides increase by 1.090 times with an increase in mandarin cultivated area of 1 ropani. Similarly, access to technical assistance had a positively significant impact (p < 0.05) on the use of neem-based pesticides. It means that the odds of using neem-based pesticides by farmers with access to technical assistance were 2.884 times higher than the odds of using neem-based pesticides by farmers who did not have access to technical assistance, as shown in Table 2.

3.5.4. Factors affecting the use of traps for insects

The results showed that mandarin-cultivated areas had a positive and significant impact (p < 0.01) on the use of traps for insects. This means that the odds of farmers using traps for insects increase by 1.178 times with an increase in mandarin cultivated area of 1 ropani. Commercial orchards with a large number of trees, possibly for farming efficiency, are more likely to adopt improved practices like these (Uaiene, 2011). Access to technical assistance also had a positively significant impact (p < 0.05) on the use of traps for insects. It means that the odds of using traps for insect pests by farmers who had access to technical assistance were 5.682 times higher than the odds of using traps for insects by farmers who didn’t have access to technical assistance.

The knowledge of farmers about orchard management practices and technology adoption was influenced by factors such as caste, education level, social participation, and landholding size, aligning with findings reported by Yadav et al. (2013).

4. Conclusion

In conclusion, this study has provided crucial insights into the intricate dynamics of major diseases impacting mandarin orchards in the Syangja district of Nepal. The analysis of citrus greening, sooty mold, and foot rot incidence and severity across different municipalities has revealed significant variations attributed to factors such as initial inoculum levels, diverse management practices, and climatic influences. Factors influencing the adoption of management practices, such as family size, farming experience, and access to technical assistance, were identified, with training emerging as a pivotal factor positively influencing production attributes. Besides, the study accentuates the imperative for targeted interventions to bolster disease resilience and orchard productivity. Emphasizing educational programs to enhance farmers’ understanding of disease management strategies, especially for emerging threats like citrus greening, is crucial. Future research should focus on addressing disparities in the formulation and adoption of essential orchard management practices, including strategies for effective disease management. This emphasis aims to ensure widespread access to critical resources and promote sustainable agricultural practices in mandarin cultivation.

Disclosure statement

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

Data availability statement

The data supporting the findings of this study are available within the manuscript.

Additional information

Notes on contributors

Santosh Subedi

Santosh Subedi, an agriculture graduate from AFU, now holds a position as a Section Officer in the Civil Service. Currently, he is pursuing a Master’s degree at the Central Department of Public Administration to further enrich his expertise in governance and public affairs.

Krishna Raj Pandey

Krishna Raj Pandey is an agriculture graduate (B.Sc.Ag) from AFU, Nepal. He discovered his passion for plant pathology during his undergraduate studies. Now at the National Plant Pathology Research Centre (NPPRC), he’s engaged in researching crop diseases, refining his skills in molecular techniques, and is committed to advancing agricultural research for sustainable farming practices.

Asbin B K

Asbin B K also holds a bachelor’s degree in agriculture from AFU and is currently pursuing his master’s at the University of Missouri-Columbia.

Aashish Bhandari

Both Ashish Bhandari and Pradeep Khanal are agriculture graduates (B.Sc.Ag) and are currently engaged in agricultural research.

Pradeep Khanal

Both Ashish Bhandari and Pradeep Khanal are agriculture graduates (B.Sc.Ag) and are currently engaged in agricultural research.