Research Article | | Peer-Reviewed

Pests, Diseases, Growth and Yield of Tomato as Influenced by Variety and Cultivation Technology

Received: 6 August 2024     Accepted: 26 August 2024     Published: 6 September 2024
Views:       Downloads:
Abstract

Tomato (Solanum lycopersicum L.) is one of the most important vegetables in the world. However, dearth of knowledge exists on cultivation technology that contributes to increased production of the crop. Meanwhile, low yielding varieties, high pests and diseases attacks, climate variability and poor soil fertility are among key production constraints that limit the increased production and productivity of tomato in Sierra Leone. A two-year field experiment was conducted at the School of Agriculture and Food Sciences experimental site during 2022 and 2023 to evaluate the effects of variety and cultivation technology (CT) on pests, diseases, growth, yield and productivity of tomato. The experiment was laid in a 2 × 4 factorial (i.e. two varieties of tomato, and four treatments: CT 1, CT 2, CT 3 and CT 4 known as control) arranged in a randomized complete block design (RCBD) with three replications. Results showed that organic (CT 1 and CT 2) and inorganic (CT 3) treatments had a positive impact on growth parameters of tomato. The CT 1 (chicken dung, mulching, and neem extract biopesticide) was most effective in promoting vegetative growth and higher fruit yield, while CT 2 (NPK 15:15:15, urea, promethrin herbicide, and chlorpyrifos pesticide) exhibited highest potency in reducing population and damage caused by diseases and pests. Findings demonstrate that improved variety and cultivation technology boost tomato tolerance to pests and diseases, as well as its growth and yield performances that could be exploited for increased production and fruit quality of the crop. The CT1 was the most effective, followed by CT 2, while CT 4 or control plots had the lowest performance. The outperformance of the organic treatments relative to the inorganic and control is suggested to be attributable to its nitrogen-rich components. Weed control was also established to be effective in both inorganic and CT 2 treatments. The findings suggest that the CT 1 should be promoted for sustainable tomato cultivation, prioritizing environmentally friendly methods for long-term success.

Published in Journal of Plant Sciences (Volume 12, Issue 5)
DOI 10.11648/j.jps.20241205.11
Page(s) 122-137
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Pests, Diseases, Management, Cultivation Technologies, Tomato Productio

1. Introduction
Tomato (Solanum lycopersicum L.) holds global significance, closely trailing behind potato and sweet potato in cultivated area but leading as the most processed crop . In Sierra Leone, the relatively low tomato yield does not reflect the crop's full potential; instead, factors such as limited access to high-quality seeds, inadequate fertilization, irrigation, and pest and disease control measures contribute to this scenario. To enhance both yield and quality, varietal selection, balanced fertilization, and effective pest and disease control are crucial . Historically, conventional agriculture heavily relied on synthetic chemical pesticides and fertilizers to manage pests and diseases, boost productivity, and maximize profits. Despite being considered effective, these methods raised environmental and health concerns, posing threats to soil quality, human health, and fostering pesticide-resistant pests . The increasing global interest in organic agriculture emphasizes sustainable and eco-friendly practices .
Organic manures present a viable alternative, being more accessible and cost-effective compared to chemical fertilizers . Organic farming avoids synthetic inputs, advocating natural approaches to pest and disease management, including crop rotation, biological control, and the use of organic manures. These practices aim to maintain ecological balance in agricultural systems while ensuring soil and ecosystem health and fertility that results in higher yield and quality of crops. Organic fertilizers contribute essential nutrients, vitamins, growth promoters, and beneficial microorganisms, resulting in improved growth, higher yields, and enhanced crop quality . Various organic manures, such as cow dung, poultry manure, goat manure, farmyard manure, compost, vermicompost, and mustard oil cake, are commonly employed in tomato production. For instance, cow dung, when applied in combination with chemical fertilizers, significantly boosts tomato growth and yield . Organic manure enhances soil nutrient content and structure as well as contributing in improving yields of crops . Although organic manures may result in lower yields compared to inorganic fertilizers, a combined approach allows the maximization of organic resources while reducing dependence on costly inorganic fertilizers .
Amending agricultural soils with organic matter increases natural suppression of soil-borne pathogens through increasing beneficial microbes which creates biological competition and antagonism, and improves physicochemical of the soil . Among the soil organic amendments that have been noted to improve soil properties as well as be effective in suppressing soil borne diseases and pathogens are wedelia , devil weed , cabbage waste , chicken dung , sunflower and carbonized rice hull .
This study hypothesizes that integrating both organic and inorganic fertilizers can effectively control pests and diseases, enhance crop growth, yield, quality and productivity, and improve soil health. The present study evaluated the performances of two tomato varieties under different agronomic management strategies for their response to insects, weeds, diseases, growth and yield of tomato.
2. Materials and Methods
2.1. Description of the Experimental Site
A two-year (2022 and 2023) experiment was conducted at the School of Agriculture and Food Sciences experimental site, Njala University, Njala Campus, Sierra Leone to evaluate the effects of organic and inorganic management practices on pest, disease, weeds and the production and productivity of tomato. Njala University, Njala Campus is located in the Kori Chiefdom, Moyamba District Southern Sierra Leone. The campus, positioned at an elevation of 5 m above sea level on latitude 8° 06′N and longitude 12° 06′W, is about 114 miles from the capital city, Freetown. The landscape is predominantly covered with secondary bush, featuring a well-balanced mixture of sand, clay, and humus. The experimental site is densely covered with elephant grass, spear grass, and sedges, and situated relatively close to the swamp.
Njala University, Njala Campus, experiences distinct dry and wet seasons, with the rainy season spanning from April to November and the dry season from October to May. The mean monthly air temperature ranges from 21°C to 23°C during the greater part of the day and night, particularly in the rainy season. The soil of the experimental site belongs to the Njala University, Njala Campus soil series (Orthoxic palehumult). Prior to conducting the experiments, soil samples were collected at a 20 cm depth using a soil auger at different points within the site to assess the physical and chemical parameters (Table 1). Soil analysis revealed that the nitrogen levels were considerably low compared to phosphorus and potassium. The soils were generally low in moisture, have a low nutrient status and highly acidic in both 2022 and 2023, which are below the optimum pH of 6.5 (Table 1).
Table 1. Physico-chemical properties of soils of the experimental site for 2022 and 2023 cropping seasons.

Properties

Sampling in 2022

Sampling in 2023

Before planting

After harvesting

Before planting

After harvesting

Soil pH (1:1H2O)

3.9

3.8

3.7

3.7

Soil pH (1:1KCl)

4.2

4.5

4.5

4.5

Nitrogen (N)

1.4

1.9

1.6

2.0

Phosphorus (P)

18.0

19.0

17.0

19.0

Potassium (K)

9.4

9.7

8.1

8.8

2.2. Experimental Materials, Treatments, Design, Layout and Management
The experimental materials were botanic seeds of two varieties of tomato including Heirloom (improved) and Nornro (local). The seeds were acquired from the Central Agricultural Research Institute (CARI), Monrovia, Liberia. The seeds were first raised in a nursery at the Crop Protection Department, NU, Njala Campus, Sierra Leone for four weeks before transplanting.
The treatments involved two varieties of tomato (Heirloom and Nornro) and four cultivation technologies including cultivation technology 1 (CT 1), cultivation technology 2 (CT 2), cultivation technology 3 (CT 3) and control or cultivation technology 4 (CT 4). The CT 1 involved the use of chicken manure (CM) at 5 t ha-1, mulching and neem biopesticide. After incorporation CM, the manure was left to decompose for two weeks before transplanting. Mulching was applied one week after transplanting to prevent pest emergence. When pests and diseases appeared, a neem kernel extract was prepared from dried neem. The extract was prepared by dissolving 180 g neem powder and 5 g local soap in 1 L water, left to ferment for about a week and then applied. The CT 2 included locally prepared biofertilizer mango fertilizer (6 Lha-1), hand weeding at one, two, and three weeks after transplanting (WAT), and neem extract in aqueous form (AZAGRO 3000) applied at 30 ml 6 L H20-1 ha-1. The CT 3 comprised the application of pre-emergence herbicide promithrine at 6 ml 6 L H20-1 ha-1 at two weeks before transplanting (WBT), NPK 15:15:15 fertilizer application at 88.9 kg ha-1, applied 1 WAT, and chlorpyrifos application at 6 ml 6 L H20-1 ha-1 when diseases and pests attacked the plants). The CT 4 is the control treatment represented the conventional farming practices with no additional organic or inorganic inputs.
The experiment was laid in a 2 × 4 factorial arrangement implemented in a Randomized Complete Block Design (RCBD) with three replications. The plot size was 3 m × 5.25 cm (15.75 m2).
The experimental field was manually cleared of vegetation and thoroughly ploughed to a depth of about 10-15 cm and leveled using hoes and shovels. Transplanting was done in the evening using four weeks old tomato seedlings at a spacing of 75×75 cm (35,556 plants ha-1). The ball of earth method of transplanting was used.
2.3. Data Collection
Growth, parameters collected plant height and number of branches) were measured from ten randomly selected and tagged plants in each plot from the middle rows using a measuring tape from the soil surface to the tip of the plants at 2,4 and 6 WAT, whilst the number of trusses and fruits was counted at every harvest from ten randomly selected tagged plants in each plot. The total number of fruits obtained from the selected plants was divided by the total number of plants tagged, to get the average number of fruits per plant.
No. of fruits per plant=Total no. of fruits from ten hills10
At harvest the weight of the total number of fruits from ten tagged plants for each plot was recorded using a digital balance. The fresh fruit per plant was determined by dividing the total weight of the fruits by 10.
Fresh fruits wt. per plant=Total no. of fresh fruits10
The insect pest population was determined on randomly selected and tagged 10 plants from the middle rows per plot at 2 and 4 WAT. The number of insects per plant was estimated by dividing the total number of insects by 10.
No. of insects per plant=Total no. of insects on 10 plants10
The percentage leaf damage per plot by insects was determined by dividing the total percentage of leaf damage from the 10 selected plants by 10 and multiplying it by 100.
Percent leaf damage=Leaf damage by insects 10×100
The incidence of diseases was calculated as the percentage of diseases symptomatic plants out of the total of ten plants assessed using the formula provided by Sseruwagi et al. .
Mean incidence (%)=Infected plantsplants×100
The severity of diseases was calculated from ten randomly selected plants using a scale 1-5 as provided by Sseruwagi et al. .
The weed populations in the field were evaluated at 2 and 4 WAT. A quadrat measuring 0.5 m2 was randomly placed in each plot and thrown twice for collection of weeds. The weeds within the sampled area of the quadrat were then identified and counted. The harvested weed biomass per plot was subsequently oven-dried at 80°C for 48 h before reweighing, until a constant weight was obtained. This process ensured accurate measurements of the weed biomass.
2.4. Data Analysis
Data were subjected to analysis of variance (ANOVA) using the GENSTAT statistical program (GENSTAT, 15th release, Rothampstead, UK). The Student Newman-Keuls (SNK) multiple range test was used to compare between treatment means using a significance level of α = 0.05. The residuals of data for the parameters were first checked for normality and homogeneity using the Shapiro-Wilk test and Bartlett’s test to ensure that data are normally distributed.
3. Results and Discussion
3.1. Effects of Variety and Agronomic Management Practice on Growth of Tomato
Variety, agronomic management treatment, and variety × treatment interactions significantly (P ≤ 0.05) influenced growth (plant height and number of branches) of tomato plants (Table 2). For plant height, the improved variety consistently exhibited the highest measurements at 2 and 4 weeks after planting (WAT) in both years. In 2022, the improved variety reached 29.2 cm and 39.6 cm, while in 2023, the plants were 27.2 cm and 42.8 cm tall at 2 and 4 WAT, respectively. In contrast, the local variety produced shorter plants at 2 WAT (22.6 cm and 24.8 cm) and 4 WAT (37.8 cm and 40.0 cm) for both years, respectively. The CT 1 treated plots consistently recorded tallest plants for the improved variety at 2 WAT (30.33 cm and 38.43 cm) and 4 WAT (50.53 cm and 54.33 cm) in 2022 and 2023, respectively. Similar trends were observed for the local variety in terms of plant height.
Table 2. Growth of tomato as affected by variety and cultivation technology during 2022 and 2023 cropping seasons.

Treatment

2022

2023

Plant height (cm)

Number of branches plant-1

Plant height (cm)

Number of branches plant-1

2 WAP

4 WAP

2 WAP

4 WAP

2 WAP

4 WAP

2 WAP

4 WAP

Variety

Improved (Heirloom)

29.2±2. 0a

39.6±2.1a

0.0±0.0a

1.4±0.0a

27.2±1.3a

42.8±3.0a

0.0±0.0a

0.8±0.0a

Local (Nornro)

22.6±1.3a

37.8±2.4b

1.1±0.0b

5.9±0.1b

24.8±2.0b

40.0±2.6b

1.9±0.0b

6.4±0.3b

CT 1 Heirloom

30.3±2.3a

50.5±2.2a

0.0±0.0c

1.8±0.1c

38.4±1.0a

54.3±0.6a

0.0±0.0c

1.3±0.3d

CT 1 Nornro

30.2±1.6a

46.7±0.9b

2.3±1.0a

13.3±2.9a

30.6±2.0ab

49.0±1.6ab

3.0±2.0a

15.0±2.1a

CT 2 Heirloom

25.2±0.3b

46.1±1.5b

0.0±0.0c

1.6±0.4c

30.2±0.9ab

48.0±0.4ab

0.0±0.0c

1.0±0.0d

CT 2 Nornro

24.0±1.0b

44.9±0.9b

1.1±1.3b

5.0±2.0b

28.7±0.9b

47.3±0.9b

2.0±2.0b

6.0±2.1b

CT 3 Heirloom

20.9±1.6c

33.7±2.0c

0.0±0.0c

1.4±0.9c

24.9±1.4c

39.7±2.4c

0.0±1.0c

1.0±1.0d

CT 3 Nornro

20.3±0.9c

32.8±2.0c

1.0±0.2b

3.7±1.5b

25.3±1.0c

35.2±0.6d

1.6±0.3b

2.3±1.9c

CT 4 Control Heirloom

17.0±2.5d

27.9±3.0d

0.0±0.0c

1.0±0.6c

15.4±3.0d

29.5±3.7e

0.0±0.0c

0.0±0.0e

CT 4 Control Nornro

16.1±2.0d

27.4±3.0d

1.0±0.5b

2.1±0.9c

14.9±2.7d

29.1±4.0e

1.0±0.2b

2.7±1.2c

F-Statistic

Treatment (Pr> F)

0.020

0.05

0.047

<0.001

<0.001

<0.001

<0.001

<0.001

Variety (Pr> F)

ns

0.05

<0.001

<0.001

0.05

0.05

<0.001

<0.001

Treatment × Variety (Pr> F)

ns

0.05

0.03

<0.001

0.05

0.04

0.02

<0.001

CV (%)

12.4

18.0

11.3

14.5

12.0

20.3

10.0

11.0

Means with the same superscripts in column are not significantly different (P>0.05) as indicated by Student Newman-Keuls multiple range test; CT=cultivation technology; CV=coefficient of variation
For the number of branches, the local variety consistently showed significantly higher numbers of branches at 2 WAT (1.1 and 1.9 plant-1) and 4 WAT (5.9 and 6.4 plant-1) for both years compared to the improved variety. The CT 1 treated plot recorded the highest number of branches for both local and improved varieties at different sampling regimes. Overall, treated plots, especially those with organic treatments, produced significantly taller plants and higher numbers of branches compared to control plots. Furthermore, the number of branches in the 2023 cropping season was higher than in the previous year (2022). These findings indicate significant influence of variety and treatment application on plant growth characteristics, suggesting potential strategies for optimizing plant development in tomato cultivation.
3.2. Inventory of Weed Pests and Diseases of Tomato Identified
In both 2022 and 2023 evaluation periods, whitefly, aphid and leaf miner were the major insect pests identified in the field; whilst the major weeds found were Imperata cylindrica, Croton hirtus and Diodia scandens, and the major diseases identified were tomato mosaic and late blight (Table 3).
Table 3. Inventory of pest, weeds and diseases on tomato.

Name of insect pest

Status

Name of weed pest

Status

Name of disease

Status

Whitefly

Present

Imperata cylindrica

Present

Tomato mosaic disease

Present

Aphid

Present

Croton hirtus

Present

Late blight

Present

Leaf miner

Present

Diodia scandens

Present

Septoria leaf spot

Absent

Gram pod borer

Absent

Anthracnose fruit rot

Absent

Tobacco caterpillar

Absent

Spider mites

Absent

3.3. Effects of Variety and Cultivation Technology on Number and Percentage Damage of Tomato by Insect Pests
Whitefly and leaf miner populations and damages significantly (P ≤ 0.05) varied among agronomic management treatments, with no notable interactions between variety and treatment at both 2 and 4 weeks after planting (Tables 4 and 5). Across both years, the local variety consistently exhibited lower whitefly counts at 2 weeks after transplanting (WAT) (7.8 and 8.0 plant-1) and at 4 WAT (2.7 and 4.5 plant-1) regardless of treatment, compared to the improved variety at 2 WAT (8.6 and 8.1 plant-1) and at 4 WAT (2.9 and 4.6 plant-1). In 2022 and 2023, inorganic treatment plots consistently recorded the lowest whitefly counts for both improved and local varieties at 2 WAT (4.00 and 4.09 plant-1) and at 4 WAT (0.00 and 0.00 plant-1). The CT 1 treated plot for both varieties showed higher whitefly counts compared to inorganic treatments but were lower than control plots. Notably, whitefly populations were lower in 2022 across all evaluation periods compared to 2023.
Table 4. Effects of variety and cultivation technology on the population and percentage damage of whitefly in 2022 and 2023 cropping seasons.

Treatment

2022

2023

Number of whiteflies plant-1

Leaf damage by whiteflies (%)

Number of whiteflies plant-1

Leaf damage by whiteflies (%)

2 WAP

4 WAP

2 WAP

4 WAP

2 WAP

4 WAP

2 WAP

4 WAP

Variety

Improved (Heirloom)

8.6±0.5a

2.9±0. 0a

6.5±0.0a

2.5±0.0a

8.1±0.6a

4.6±0.2a

7.5±0.3a

5.3±0.4a

Local (Nornro)

7.8±0.4a

2.7±0.0a

6.4±0.0a

2.5±0.0a

8.0±0.5a

4.5±0.2a

7.4±0.5a

5.2±0.4a

CT 1 Heirloom

7.5±1.5b

2.0±0.5b

5.6±0.0b

0.0±0.0b

8.0±0.5b

3.0±0.5b

7.0±2.0b

5.3±3.3b

CT 1 Nornro

8.0±1.0b

2.0±0.0b

5.0±0.0b

0.0±0.0b

8.6±0.0b

3.0±0.0b

7.0±2.6b

5.1±1.7b

CT 2 Heirloom

8.2±1.6b

2.6±0.7b

5.4±0.6b

0.0±0.0b

9.1±0.7b

3.7±0.6b

7.7±2.0b

6.0±1.7b

CT 2 Nornro

8.9±1.6b

2.0±0.6b

5.8±0.2b

0.0±0.0b

9.0±0.6b

3.0±0.2b

8.0±1.9b

5.7±1.7b

CT 3 Heirloom

4.0±1.3c

0.0±0.0c

5.0±1.6b

0.0±0.0b

4.6±0.3c

0.0±0.0c

5.4±1.6c

0.0±0.0c

CT 3 Nornro

4.1±1.0c

0.0±0.0c

5.0±0.0b

0.0±0.0b

4.1±0.1c

0.0±0.0c

5.2±1.0c

0.0±0.0c

CT 4 Control Heirloom

10.5±1.6a

7.0±0.7a

10.0±0.3a

10.0±1.5a

11.0±1.6a

12.7±1.3a

10.0±2.0b

10.0±1.9a

CT 4 Control Nornro

10.3±1.8a

7.0±0.5a

10.0±0.2a

10.0±1.1a

11.0±1.7a

12.3±1.5a

10.0±2.0b

10.0±2.0a

F-Statistic

Treatment (Pr> F)

0.05

<0.001

<.001

<.001

<.001

<.001

0.044

<.001

Variety (Pr> F)

ns

ns

ns

ns

ns

ns

ns

ns

Treatment × variety (Pr> F)

ns

ns

ns

ns

ns

ns

ns

ns

CV (%)

19.0

12.2

10.4

8.3

13.8

9.0

13.0

10.0

Means with the same superscripts in column are not significantly different (P>0.05) as indicated by Student Newman-Keuls multiple range test; AMP=agronomic management practice; CV=coefficient of variation
Table 5. Effects of variety and cultivation technology on the population and percent leaf damage by leaf miner in 2022 and 2023 cropping seasons.

Treatment

2022

2023

Number of leaf miner plant-1

Leaf damage by leaf miner (%)

Number of leaf miner plant-1

Leaf damage by leaf miner (%)

2 WAP

4 WAP

2 WAP

4 WAP

2 WAP

4 WAP

2 WAP

4 WAP

Variety

Improved (Heirloom)

4.8±0.0a

2.6±0.0a

20.0±1.6a

11.2±0.7a

5.6±0.5a

2.7±0. 0a

23.6±2.0a

11.3±0.5a

Local (Nornro)

4.9±0.0a

2.7±0.0a

20.0±1.6a

11.3±0.7a

5.8±0.5a

2.7±0.0a

24.1±1.2a

11.5±0.6a

CT 1 Heirloom

4.3±0.6b

2.5±0.6b

20.0±2.7b

10.0±1.7b

5.3±0.6ab

2.3±0.6b

25.0±2.9b

10.0±2.9b

CT 1 Nornro

4.3±1.52b

2.3±0.5b

20.1±2.3b

10.1±1.3b

5.3±1.5ab

2.3±1.5b

21.7±4.4c

10.7±4.4b

CT 2 Heirloom

5.7±0.6ab

2.9±0.1b

20.0±2.7b

10.0±1.7b

5.7±0.6ab

2.7±0.6b

25.0±2.9b

10.0±2.9b

CT 2 Nornro

6.3±1.2a

2.8±0.2b

20.1±2.3b

10.1±1.3b

6.3±1.2a

2.3±1.2b

25.7±6.7b

10.7±6.6b

CT 3 Heirloom

2.7±0.6c

0.0±0.0c

10.0±0.0c

5.0±0.0c

4.7±0.6b

0.7±0.0c

10.1±0.0d

5.0±0.0c

CT 3 Nornro

2.3±1.5c

0.0±0.0c

10.0±0.0c

5.0±0.0c

4.3±0.5b

0.3±0.0c

10.1±5.0d

5.0±5.0c

CT 4 Control Heirloom

7.0±0.0a

6.0±0.0a

30.3±3.0a

20.3±3.0a

7.2±0.0a

6.0±0.0a

38.3±6.0a

20.3±6.0a

CT 4 Control Nornro

7.0±1.7a

6.0±1.7a

30.0±3.0a

20.0±3.0a

7.3±1.7a

6.0±1.7a

35.0±7.6ab

20.0±7.6a

F-Statistic

Treatment(Pr> F)

0.05

<0.001

<0.001

<0.001

<0.001

<0.001

<0.001

<0.001

Variety(Pr> F)

ns

ns

ns

ns

ns

ns

ns

ns

Treatment ×Variety(Pr> F)

ns

ns

ns

ns

ns

ns

ns

ns

Treatment × Year(Pr> F)

ns

ns

ns

ns

ns

ns

ns

ns

CV (%)

17.6

10.0

14.8

10.0

16.9

8.3

16.0

14.7

Means with the same superscripts in column are not significantly different (P>0.05) as indicated by Student Newman-Keuls multiple range test; AMP=agronomic management practice; CV=coefficient of variation
Similarly, treatments significantly influenced the percentage damage caused by whiteflies over the two evaluation years, with no significant Varietal or Variety × Treatment interactions at 2 and 4 weeks after planting. The local variety consistently exhibited lower percentage damage at both 2 WAT (6.4 and 7.4%) and 4 WAT (2.5 and 5.2%) compared to the improved variety. Inorganic treatments consistently resulted in the lowest percentage leaf damage for both varieties, followed by CT 1 treatment. Control plots consistently had the highest percentage leaf damage for both varieties, with higher damage observed in 2023 compared to 2022. This study highlights the significant impact of treatments on whitefly populations and associated damage, with inorganic treatments showing the most effective control measures. Additionally, the local variety displayed greater resistance to whiteflies compared to the improved variety across both years.
The improved variety consistently exhibited lower leaf miner counts at 2 WAT (4.8 and 5.6 plant-1) and at 4 WAT (2.6 and 2.7 plant-1) compared to the local variety. Inorganic treated plots consistently showed the lowest leaf miner counts, followed by CT 1 treated plot. However, control plots consistently exhibited the highest leaf miner counts for both varieties throughout both evaluation years (2022 and 2023), indicating the inefficacy of control methods in managing leaf miner populations.
The improved variety consistently demonstrated lower percentage leaf damage at both 2 WAT (20.0 and 23.6%) and 4 WAT (11.2 and 11.3%) compared to the local variety. Inorganic treated plots resulted in the lowest percentage leaf damage, while control plots consistently exhibited the highest percentage leaf damage for both varieties in both evaluation years. This study underscores the effectiveness of treatments in managing leaf miner populations and associated damage, with inorganic treatments showing the most promising outcomes. Additionally, the improved variety showcased greater resistance to leaf miners compared to the local variety across both evaluation years.
For aphid population, the local variety consistently had lower leaf aphid counts at 2 WAT (3.8 and 4.3 plant-1) and at 4 WAT (2.3 and 1.9 plant-1) compared to the improved variety (Table 6). Inorganic treated plots had the lowest leaf aphid counts, followed by CT 1 treated plots, across both years. However, control plots consistently exhibited the highest aphid numbers for both varieties throughout the two years of evaluations (2022 and 2023), indicating the inefficacy of control methods in managing aphid populations.
Table 6. Effects of variety and cultivation technology on the population and percentage damage of leaf by aphid in 2022 and 2023 cropping seasons.

Treatment

2022

2023

Number of aphid plant-1

Leaf damage by aphid (%)

Number of aphid plant-1

Leaf damage by aphid (%)

2 WAP

4 WAP

2 WAP

4 WAP

2 WAP

4 WAP

2 WAP

4 WAP

Variety

Improved (Heirloom)

4.0±0.1a

2.4±0.2a

11.4±0.4a

0.0±0.0a

4.3±0.3a

2.2±0.1a

12.9±1.8a

5.1±0.3a

Local (Nornro)

3.8±0.1a

2.3±0.1a

11.4±0.4a

2.7±0.1b

4.3±0.3a

1.9±0.0a

13.2±1.9a

5.2±0.3a

CT 1 Heirloom

3.0±1.9c

1.0±0.9b

10.1±0.9b

0.0±0.0b

2.3±1.9d

1.3±0.9b

10.2±2.9d

5.0±0.4b

CT 1 Nornro

3.0±0.9d

1.0±0.1b

10.3±0.7b

0.0±0.0b

2.6±0.9d

1.2±0.1b

8.3±1.7e

5.3±0.7b

CT 2 Heirloom

3.6±0.9d

1.6±0.9b

10.7±0.7b

0.5±0.0b

2.7±0.9d

1.7±0.1b

11.7±1.7d

5.7±0.5b

CT 2 Nornro

3.3±1.2c

1.1±0.2b

10.3±0.7b

0.5±0.0b

4.3±1.2c

1.3±0.02b

13.3±1.7c

5.3±0.4b

CT 3 Heirloom

2.7±0.9c

0.0±0.0c

10.0±0.7b

0.0±0.0c

2.1±0.9d

0.6±0.0c

8.0±1.7e

0.0±0.0c

CT 3 Nornro

2.0±0.6b

0.0±0.0c

10.0±0.9b

0.0±0.0c

2.0±0.6d

0.0±0.0c

10.0±2.9d

0.0±0.0c

CT 4 Control Heirloom

7.3±0.9a

7.3±0.9a

15.0±1.3a

10.3±0.3a

8.3±0.9a

5.3±0.5a

23.3±3.3a

10.3±1.3a

CT 4 Control Nornro

7.3±1.2a

7.3±1.2a

15.0±1.9a

10.0±0.9a

8.3±1.2a

5.3±0.2a

20.0±2.9b

10.0±1.9a

F-Statistic

Treatment (Pr> F)

0.05

<0.001

<.001

<.001

<.001

<.001

<.001

<.001

Variety(Pr> F)

ns

ns

ns

<.001

ns

ns

ns

ns

Treatment × variety

ns

ns

ns

<.001

ns

ns

ns

ns

Treatment × year

ns

ns

ns

<.001

ns

ns

ns

ns

CV (%)

9.7

10.6

14.0

18.4

16.3

10.4

20.1

22.0

Means with the same superscripts in column are not significantly different (P>0.05) as indicated by Student Newman-Keuls multiple range test; ns = non-significant at 5% SNK; CT=cultivation technology; CV=coefficient of variation
Regarding percentage leaf damage caused by aphids, treatments significantly influenced it during both evaluation years (P ≤ 0.05), with significant interactions observed at 4 WAT in 2022 (P ≤ 0.05). The improved variety consistently showed lower percentage leaf damage at both 2 WAT (11.4 and 12.9%) and 4 WAT (0.0 and 5.1%) compared to the local variety. Inorganic treated plots resulted in the lowest percentage leaf damage, while control plots consistently exhibited the highest percentage leaf damage for both varieties in both evaluation years. Overall, the study highlights the significant impact of treatments on leaf aphid populations and associated damage, with inorganic treatments showing promising results. Additionally, the improved variety displayed greater resistance to leaf aphids compared to the local variety across both evaluation years.
3.4. Effects of Variety and Cultivation Technology on Incidence and Severity of Diseases
The study found significant treatment effects on tomato mosaic disease incidence during both evaluation years (P ≤ 0.05), with significant interactions at 2 WAT in 2023 (Table 7). The local variety consistently had lower incidence at 2WAT (20.8 and 20.2%) and 4 WAT (16.4%) compared to the improved variety (21.3 and 22.5% at 2 WAT, 16.5 % at 4 WAT). Inorganic treatments consistently showed lower incidence at 2 (10.7 and 10.3%) and 4 WAT (5.7 and 5.3%) in 2022, and at 2 (10.6 and 10.0%) and 4 WAT (5.7 and 5.3%) in 2023. Overall, disease incidence decreased in 2023 compared to 2022, with control plots consistently showing the highest incidence. For disease severity, treatments significantly influenced it during both years (P ≤ 0.05), with no significant interactions at 2 and 4 WAT. The local variety consistently had lower severity at 2 WAT (2.7) and 4 WAT (1.8 and 2.0) compared to the improved variety (2.8 and 2.7 at 2 WAT, 1.8 and 2.1 at 4 WAT). Inorganic treatments consistently showed lower severity at 2 (2.0) and 4 WAT (1.0) in 2022, and at 2 (2.1) and 4 WAT (1.6) in 2023. Control plots consistently exhibited the highest severity values of 2.0 and 4.3 at 2 and 4 WAT in 2022, respectively. Overall, severity increased in 2023 compared to 2022.
Table 7. Effects of variety and cultivation on the incidence and severity of tomato mosaic disease.

Treatment

2022

2023

Incidence

Severity

Incidence

Severity

2 WAP

4 WAP

2 WAP

4 WAP

2 WAP

4 WAP

2 WAP

4 WAP

Variety

Improved (Heirloom)

21.3±0.1 a

16.5±1.0a

2.8±0.1a

1.8±0.1 a

22.5±1.1a

16.5±0.6 a

2.7±0.1a

2.1±0.2a

Local (Nornro)

20.8±0.1a

16.4±1.0a

2.7±0.2a

1.8±0.1a

20.2±1.2a

16.4±0.6a

2.7±0.1a

2.0±0.0a

CT 1 Heirloom

22.0±.0b

10.0±.0b

2.5±0.0b

1.0±0.1b

20.0±.0b

10.0±.0b

2.5±0.0b

1.5±0.1b

CT 1 Nornro

22.3±2.3b

10.3±3.3b

2.5±0.0b

1.0±0.1b

20.3±2.3b

10.3±3.3b

2.5±0.0b

1.4±0.1b

CT 2 Heirloom

22.0±2.9b

10.0±2.9b

2.7±0.3b

1.0±0.3b

20.0±2.9b

10.0±2.9b

2.7±0.3b

1.7±0.3b

CT 2 Nornro

20.7±1.3b

10.7±3.3b

2.5±0.3b

1.0±0.3b

10.7±1.3c

10.7±3.3b

2.5±0.32b

1.3±0.3b

CT 3 Heirloom

10.7±1.3c

5.7±3.3c

2.0±0.3b

1.0±0.3b

10.6±1.3c

5.7±3.3c

2.1±0.3b

1.6±0.3b

CT 3 Nornro

10.3±1.3c

5.3±3.3c

2.0±0.3b

1.0±0.3b

10.0±1.3c

5.3±3.3c

2.1±0.3b

1.6±0.3b

CT 4 Control Heirloom

30.7±1.3a

40.0±3.3a

4.0±0.0a

4.3±0.0a

39.7±1.3a

40.0±3.3a

4.0±0.0a

4.0±0.0a

CT 4 Control Nornro

30.0±0.0a

40.0±0.0a

4.0±0.0a

4.3±0.0a

40.0±0.0a

40.0±0.0a

4.0±0.0a

4.0±0.0a

F-Statistic

Treatment (Pr> F)

<.001

<0.001

0.05

<.001

<.001

<.001

<.001

<.001

Variety (Pr> F)

ns

ns

ns

ns

0.05

ns

ns

ns

Treatment × variety

ns

ns

ns

ns

0.05

ns

ns

ns

Treatment × year

ns

ns

ns

ns

0.05

ns

ns

ns

CV (%)

16.5

11.0

10.4

7.6

18.9

22.3

10.0

8.9

Means with the same superscripts in column are not significantly different (P>0.05) as indicated by Student Newman-Keuls multiple range test; ns = non-significant at 5% SNK; CT=cultivation technology; CV=coefficient of variation
The findings indicate the effectiveness of improved cultivation technologies in managing pests and diseases, reducing whitefly, leaf miner, aphid, tomato mosaic disease, and tomato bacteria leaf blight. Abbas et al. supported chemical pesticides' efficacy, attributing it to Glutathione s-transferase inhibition. Organic treatments also showed promise, aligning with Fening et al. , who highlighted neem extract's potential in crop protection. Although inorganic treatments were as effective as Organic 1, the latter is environmentally friendly, making it a preferred option.
3.5. Effects of Variety and Cultivation Technology on Number of Trusses, Flower and Fruit Yield
Findings revealed significant effects of management practices on the incidence and severity of bacteria leaf blight in tomatoes over the two-year evaluation (Table 8). For the incidence of late blight disease, treatments significantly affected it during both years (P ≤ 0.05), with significant interactions in 2023. The improved variety consistently showed lower incidence at 2 WAT (14.0 and 24.0%) and 4 WAT (5.2 and 16.5%) compared to the local variety. Inorganic treatments resulted in lower mean incidence at 2 (10.0 and 10.3%) and 4 WAT (0.0%) in 2022 and at 2 (20.0%) and 4 WAT (10.7 and 10.3%) in 2023. Control plots consistently had the highest mean incidence for both varieties in both years. Regarding the severity of late blight disease, treatments significantly influenced it during both years (P ≤ 0.05), with no significant interactions. The improved variety consistently showed lower severity at 2 WAT (2.5 and 2.4) and 4 WAT (1.6 and 18.0) compared to the local variety. Inorganic treatments resulted in lower mean severity at 2 (2.0) and 4 WAT (1.0) in 2022 and at 2 (2.0) and 4 WAT (1.0) in 2023. Control plots consistently exhibited the highest mean severity in 2022. Overall, severity was higher in 2022 than in 2023.
Table 8. Effects of variety and cultivation technology on the incidence and severity of tomato bacteria leaf blight disease.

Treatment

2022

2023

Bacteria leaf blight incidence

Bacteria leaf blight severity

Bacteria leaf blight incidence

Bacteria leaf blight severity

2 WAP

4 WAP

2 WAP

4 WAP

2 WAP

4 WAP

2 WAP

4 WAP

Variety

Improved (Heirloom)

14.0±1.3a

5.2±0.4a

2.5±0.2a

1.6±0.1a

24.0±1.5a

16.5±1.3a

2.4±1.0a

1.8±0.6a

Local (Nornro)

14.8±1.3a

5.3±0.4a

2.6±0.2a

1.6±0.1a

25.0±1.6a

17.7±1.2a

2.4±1.0a

1.8±1.5a

CT 1 Heirloom

10.5±1.0c

5.1±0.6b

2.5±0.3b

1.0±0.0b

20.6±.0c

10.0±.0e

2.3±0.0b

1.0±0.0b

CT 1 Nornro

13.3±1.3b

5.2±0.5b

2.5±0.3b

1.0±0.0b

23.3±3.3b

13.3±3.3d

2.3±0.0b

1.0±0.0b

CT 2 Heirloom

15.0±1.9ab

5.5±0.5b

2.6±0.4b

1.0±0.0b

25.0±2.9ab

15.0±2.9c

2.7±0.3a

1.0±0.0b

CT 2 Nornro

15.7±1.3ab

5.7±0.3b

2.3±0.3b

1.0±0.0b

26.7±3.3ab

16.7±3.3c

2.3±0.3a

1.0±0.0b

CT 3 Heirloom

10.0±1.3c

0.0±0.0c

2.0±0.0b

1.0±0.0b

20.0±3.3c

10.7±3.3c

2.0±0.3a

1.0±0.0b

CT 3 Nornro

10.3±1.3c

0.0±0.0c

2.0±0.0b

1.0±0.0b

20.0±3.3c

10.3±3.3b

2.0±0.3a

1.0±0.0b

CT 4 Control Heirloom

20.7±2.3a

10.7±3.3a

3.3±0.0a

3.5±0.6a

30.7±3.3a

30.6±3.3a

3.0±0.0a

3.0±0.0a

CT 4 Control Nornro

20.0±2.0a

10.0±0.0a

3.3±0.0a

3.5±0.8a

30.0±0.0a

30.5±0.0a

3.0±0.0a

3.0±0.2a

F-Statistic

Treatment (Pr> F)

<0.001

<0.001

0.05

<.001

<.001

<.001

0.040

<.001

Variety (Pr> F)

ns

ns

ns

ns

0.05

0.05

ns

ns

Treatment × variety (Pr> F)

ns

ns

ns

ns

0.05

0.05

ns

ns

Treatment × Year (Pr> F)

ns

ns

ns

ns

0.05

0.05

ns

ns

CV (%)

14.7

12.0

14.0

10.0

14.6

11.0

9.0

8.6

Means with the same superscripts in column are not significantly different (P>0.05) as indicated by Student Newman-Keuls multiple range test; ns = non-significant at 5% SNK; CT=cultivation technology; CV=coefficient of variation
The statistical analysis of variance indicated significant effects of both variety and treatment factors (P ≤ 0.05) on the number of trusses and flowers in tomato plants, with significant interactions between variety and treatment observed in both 2022 and 2023 (Table 9). The local variety consistently outperformed the improved variety, exhibiting higher numbers of trusses (13.4 and 13.6 plant-1) and flowers (38.1 and 38.6 plant-1) in the 2022 and 2023 cropping seasons, respectively. The CT 1 plot recorded the highest numbers of trusses (24.00 and 22.33 plant-1) and flowers (57.13 and 55.66 plant-1) for both local and improved varieties across the two years.
Table 9. Effects of variety and cultivation technology on number of trusses per plant and number of flowers per plant.

Treatment

2022

2023

Number of trusses plant-1

Number of flowers plant-1

Number of trusses plant-1

Number of flowers plant-1

Variety

Improved (Heirloom)

12.4

36.1

12.5

36.7

Local (Nornro)

13.4

38.1

13.6

38.7

CT 1 Heirloom

22.9±1.0a

55.0±5.2ab

20.0±0.6a

53.3±4.4a

CT 1 Nornro

24.0±2.4a

57.1±5.1a

22.3±1.5a

55.7±8.7a

CT 2 Heirloom

14.0±1.7b

44.7±4.0b

13.7±1.2b

41.3±3.7b

CT 2 Nornro

15.8±1.7b

44.1±6.4b

15.0±1.5b

43.0±7.0b

CT 3 Heirloom

7.6±1.4c

25.0±2.0d

9.3±1.2c

29.3±2.3d

CT 3 Nornro

8.0±1.0c

30.1±1.8c

10.0±1.2c

33.0±1.5c

CT 4 Control Heirloom

5.1±1.0.8d

20.0±1.8e

7.3±1.3d

24.0±0.6e

CT 4 Control Nornro

6.0±0.5d

21.2±1.8e

7.0±0.0d

23.0±1.7e

F-Statistic

Treatment (Pr> F)

<0.001

<0.001

<0.001

<0.001

Variety(Pr> F)

0.05

0.05

0.05

0.05

Treatment × Variety

0.02

0.04

0.02

0.05

CV (%)

15.6

13.0

10.0

13.7

Means with the same superscripts in column are not significantly different (P>0.05) as indicated by Student Newman-Keuls multiple range test; ns = non-significant at 5% SNK; CT= cultivation technology; CV=coefficient of variation
Table 10. Effects of variety and cultivation technology on fresh fruit yield of tomato.

2022

2023

Treatment

Fresh fruit yield (t ha-1)

Fresh fruit yield (t ha-1)

Variety

Improved (Heirloom)

2.8±0.2b

3.1±0.3a

Local (Nornro)

3.5±0.2a

3.4±0.3a

CT 1 Heirloom

4.2±0.3b

4.6±0.3b

CT 1 Nornro

5.3±0.5a

5.5±0.5a

CT 2 Heirloom

4.5±0.4b

4.5±0.2b

CT 2 Nornro

5.6±0.5a

4.6±0.4b

CT 3 Heirloom

2.0±0.1c

2.6±0.1c

CT 3 Nornro

2.5±0.2c

2.7±0.2c

CT 4 Control Heirloom

0.5±0.0d

0.5±0.0d

CT 4 Control Nornro

0.6±0.0d

0.6±0.0d

F-Statistic

Treatment (Pr> F)

<.001

<.001

Variety (Pr> F)

0.050

ns

Treatment × variety (Pr> F)

0.050

ns

Treatment × year(Pr> F)

ns

ns

CV (%)

10.0

13.0

Means with the same superscripts in column are not significantly different (P>0.05) as indicated by Student Newman-Keuls multiple range test; ns = non-significant at 5% SNK; CT=cultivation technology; CV=coefficient of variation
Variety and biotic constraint management options significantly (P<0.05) influenced fresh fruit yield during both 2022 and 2023 (Table 10). Local variety consistently produced higher fresh fruit yields of 5.6 and 4.6, and 3.5 and 3.4 t ha-1, compared to the improved variety (2.8 t ha-1 and 3.1 t ha-1) in both years, respectively. The CT 1 treated plots showed the highest fruit yield for both improved (4.2 t ha-1 and 4.6 t ha-1) and local (5.3 t ha-1 and 5.5 t ha-1) varieties in 2022 and 2023, respectively. Overall, the fresh fruit yields for both varieties were slightly higher in 2023 than in 2022. Control plots consistently recorded the lowest fresh fruit yields for both improved and local varieties across both evaluation years. These findings emphasize the significance of both variety selection and specific treatments, particularly CT 1, in influencing the growth, flowering, and fresh fruit yield of tomato. Findings also indicate that organic amendments not only improve soil conditions, but also soil-water-plant relations, by modifying soil bulk density, total porosity, and importantly provide nutrients. Consequently, amendments increase plant growth, yield and water use efficiency . In addition, several reports mentioned that application of different organic soil amendments can increase the yield of crops including lettuce , potato , and tomato . The observed interactions between variety and treatment further highlight the need for a holistic approach in optimizing tomato crop production.
3.6. Effects of Variety and Cultivation Technology of Tomato on Weed Density (Weeds m-2) and Weed Dry Weight (g m-2)
The study investigated the impact of treatments on the yield of tomato crops and weed management over two evaluation years. The results showed significant effects of treatments (P ≤ 0.05) on fruit and seed yield, with significant interactions between variety × treatment, and treatment × year factors (Table 12). Weed infestation was influenced by the treatments, with a significant reduction observed in inorganic treated plots, where permethrin herbicide was applied. Generally, the quantity of weeds in the experimental field was higher in 2023 than in 2022. In 2022, at 2 and 4 WAT, the weed quantity was notably lower in CT 3 treated plots (2.66 and 6.03 weeds m-2) compared to CT 2 (3.46 and 6.36 weeds m-2) and control (20.66 and 60.60 weeds m-2) plots. A similar trend was observed in 2023, with CT 3 plots showing lower weed quantities at 2 and 4 WAT (4.06 and 7.33 weeds m-2) compared to other treatments.
Table 11. Effects of variety and cultivation technology on weed density.

Weed density (weeds m-2)

Treatment

2022

2023

2 WAP

4 WAP

2 WAP

4 WAP

Variety

Improved (Heirloom)

8.7±0.80a

22.1±2.00a

11.4±0.10a

24.1±2.00a

Local (Nornro)

9.0±0.70a

22.0±2.00a

11.3±0.10a

25.6±2.11a

CT 1 Heirloom

8.60±0.10b

15.30±1.60b

10.60±0.20b

18.33±1.66b

CT 1 Nornro

7.67±0.13b

15.34±1.07b

9.67±0.33b

18.33±1.67b

CT 2 Heirloom

3.46±0.03c

6.36±0.06c

5.40±0.13c

9.33±0.66c

CT 2 Nornro

3.13±0.06c

6.03±0.60c

5.10±0.06c

9.33±0.67c

CT 3 Heirloom

2.66±0.16c

6.03±0.06c

4.06±0.16d

7.33±0.66c

CT 3 Nornro

2.33±0.03c

6.60±1.03c

4.30±0.33d

8.66±1.33c

CT 4 Control Heirloom

20.66±0.60a

60.60±1.60a

25.66±0.66a

61.67±1.66ab

CT 4 Control Nornro

23.00±0.70a

60.33±1.30a

26.00±0.00a

66.03±1.33a

F-Statistic

Treatment(Pr> F)

<.0001

<.0001

<.0001

<.0001

Variety(Pr> F)

ns

Ns

ns

ns

Treatment × variety(Pr> F)

ns

Ns

ns

ns

Treatment × Year(Pr> F)

ns

Ns

ns

ns

CV (%)

12.9

10.3

10.0

20.3

Means with the same superscripts in column are not significantly different (P>0.05) as indicated by Student Newman-Keuls multiple range test; ns = non-significant at 5% SNK; CT=cultivation technology; CV=coefficient of variation
Table 12. Effects of variety and cultivation technology on weed dry matter.

Treatment

Weed dry weight (g m-2)

2022

2023

2 WAP

4 WAP

2 WAP

4 WAP

Variety

Improved (Heirloom)

6.7±0.53a

8.4±0.60a

4.9±0.23a

6.8±0.63a

Local (Nornro)

6.8±0.46a

8.6±0.16a

5.0±0.16a

6.9±0.65a

CT 1 Heirloom

6.96±0.13b

8.00±0.10b

4.96±0.23b

6.40±0.20b

CT 1 Nornro

6.83±0.16b

8.20±0.10b

4.83±0.16b

6.23±0.13b

CT 2 Heirloom

4.33±0.10c

5.33±0.06c

2.33±0.16c

3.33±0.16c

CT 2 Nornro

4.33±0.10c

5.30±0.06c

2.33±0.16c

3.33±0.16c

CT 3 Heirloom

2.06±0.03d

3.60±0.30d

1.06±0.03d

1.96±0.03d

CT 3 Nornro

2.93±0.00d

3.07±0.30d

0.93±0.06d

1.97±0.03d

CT 4 Control Heirloom

13.66±0.63a

17.07±0.33a

11.66±0.33a

15.67±0.33a

CT 4 Control Nornro

13.00±0.80a

18.03±0.60a

12.00±0.50a

16.33±0.67a

F-Statistic

Treatment (Pr> F)

<.001

<.001

<.001

<.001

Variety (Pr> F)

ns

ns

ns

ns

Treatment × variety (Pr> F)

ns

ns

ns

ns

Treatment × Year (Pr> F)

ns

ns

ns

ns

CV (%)

8.5

16.0

10.2

10.0

Means with the same superscripts in column are not significantly different (P>0.05) as indicated by Student Newman-Keuls multiple range test; ns=non-significant at 5% SNK; CT=cultivation technology; CV=coefficient of variation.
Weed dry weight was significantly influenced by treatments in both years (Table 12). In 2022, inorganic treated plots had the lowest weed dry weight at 2 and 4 WAT (2.06 and 3.60 g m-2), followed by organic 2 treated plots (4.33 and 5.33 g m-2), and control plots had the highest (13.66 and 17.07 g m-2). A similar pattern was observed in 2023, with lower weed dry weights in inorganic treated plots at 2 and 4 WAT (1.06 and 1.96 g m-2). The study emphasizes the significance of treatments in managing weed infestation, with inorganic treatments showing more effective weed control compared to organic treatments and control plots. The observed interactions highlight the complexity of the relationships between varietal selection, treatment application, and environmental conditions in determining crop yield and weed management outcomes. Findings indicate that some amendment species have toxic effects on the growth of tomato plants. This agrees with the view that some amendment species have toxic effects on the growth of some plants, such as the green manure of Brassicaceae plants (Brassica juncea L., Sinapsis alba L.) , sunflower (Helianthus annus L.), dhaincha (Sesbania aculeata Poiret) , or red clover (Trifolium pratense L.) . Weed control is essential for optimal crop yields as depicted in the improved agronomic management practices compared to the control, which was consistent with Tiwari et al. , who emphasized weeding efficacy for improved growth and yield of crop.
4. Conclusions
This study assessed organic and inorganic methods for improving tomato growth and managing pests, diseases, and weeds. Findings demonstrate that variety and cultivation technology (crop management practices) boost tomato tolerance to pests and diseases, as well as its growth and yield that could be exploited for increased production and fruit quality of the crop. Cultivation technology 1 (CT 1), comprising chicken dung and Gliricidia sepium mulching, was the most effective, followed by CT 2, while CT 4 could not support the crop partly due to poor soil structure and fertility status. The outperformance of the organic treatments relative to the inorganic and control is suggested to be attributable to its nitrogen-rich components. Moreover, agronomic management practices involving organic materials applied at optimal rates are environmental friendly. Weed control was also established to be effective in both inorganic and CT 2 treatments. The findings suggest that the CT 1 should be promoted for sustainable tomato cultivation, prioritizing environmentally friendly methods for long-term success.
Abbreviations

CARI

Central Agricultural Research Institute

CT

Cultivation Technology

RCBD

Randomized Complete Block Design

SLARI

Sierra Leone Agricultural Research Institute

WAT

Weeks After Transplanting

Acknowledgments
The authors are grateful for the technical support by field support staff of the Department of Crop Protection, Njala University.
Author Contributions
Alusaine Edward Samura: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Methodology, Resources, Supervision, Validation, Writing – original draft
Pricellia Nornor Watson: Conceptualization, Investigation, Methodology, Project administration, Resources, Validation, Writing – original draft, Writing – review & editing
Vandi Amara: Conceptualization, Data curation, Formal Analysis, Investigationb, Methodology, Software, Visualization, Validation, Writing – original draft, Writing – review & editing
Prince Emmanuel Norman: Conceptualization, Formal Analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing
Musa Decius Saffa: Investigation, Writing – original draft, Writing – review & editing
Funding
This work is not supported by any external funding.
Conflicts of Interest
The authors declare no conflicts of interest.
References
[1] Tamburino, R., Sannino, L., Cafacco, D., Cantarella, C., Orru, L., Cardi, T., Cozzolino, S., D’Agostino, N., Scotti, N. Cultivated tomato (Solanum lycopersicum L.) suffered a severe cytoplasmic bottleneck during domestication: Implications from cytoplast genomes. Plants, 2020, 9(11), 1443.
[2] Barłóg, P. Improving Fertilizer Use Efficiency—Methods and Strategies for the Future. Plants, 2023, 12, 3658.
[3] Pathak, V. M., Verma, V. K., Rawat, B. S., Kaur, B., Babu, N., Sharma, A., Dewali, S., Yadav, M., Kumari, R., Singh, S., Mohapatra, A., Pandey, V., Rana, N., Cunill, J. M. Current status of pesticide effects on environment, human health and it’s eco-friendly management as bioremediation: A comprehensive review. Frontiers in Microbiology, 2022, 13, 962619.
[4] Hazmi, M., Suryaningrum, D. A., Umarie, I., Oktarina, Hari, Swasono, M. A. H. Emerging Trends and Future Directions in Organic Agriculture and Environmentally-friendly Farming Practices: A Bibliometric Analysis. West Science Interdisciplinary Studies, 2023, 01(07), 438-447.
[5] Han, S. H., An, J. Y., Hwang, J., Kim, S. B., Park, B. B. The effects of organic manure and chemical fertilizer on the growth and nutrient concentrations of yellow poplar (Liriodendron tulipifera Lin.) in a nursery system. Forest Science and Technology, 2016, 12(3), 137–143.
[6] Zhou, Z., Zhang, S., Jiang, N., Xiu, WE., Zhao, J., Yang, D. Effects of organic fertilizer incorporation practices on crops yield, soil quality, and soil fauna feeding activity in the wheat-maize rotation system. Frontiers in Environmental Science, Section Soil Processes, 2022, 10.
[7] Cen, Y., Guo, L., Liu, M, Gu, X., Li, C., Jiang, G. Using organic fertilizers to increase crop yield, economic growth, and soil quality in a temperate farmland. PeerJ, 2020, 8, e9668
[8] Farid, M. N., Kobir, M. S., Obaidullah, A. J. M., Haque, M. E., Islam, M. R., Mondal, M. F. Effects of different manures and fertilizers on growth and yield of tomato. Asian Journal of Crop, Soil Science and Plant Nutrition, 2023, 08(01), 299-307.
[9] Saha, K., Kabir, M. Y., Mondal, C., Mannan, M. A. Growth and yield of tomato as affected by organic and inorganic fertilizers. Journal of Bangladesh Agricultural University, 2019, 17(4), 500–506.
[10] Gram, G., Roobroeck, D., Pypers, P., Six, J., Merckx, R., Vanlauwe, B. Combining organic and mineral fertilizers as a climate-smart integrated soil fertility management practice in sub-Saharan Africa: A meta-analysis. PLoS ONE, 2020, 15(9), e0239552.
[11] Kugbe, J. Increase in The Use of Organic Fertilizers as Complements to Inorganic Fertilizers in Maintenance of Soil Fertility and Environmental Sustainability. World Journal of Agriculture and Soil Science, 2019, 4(1).
[12] Janvier, C., Villeneuve, F., Alabouvette, C., Edel-Hermann, V., Mateille, T., Steinberg, C. H. Soil health through soil disease suppression: Which strategy from descriptors to indicators? Soil Biology and Biochemistry, 2007, 39, 1-23.
[13] Holopainen, J. K. (2004). Multiple functions of inducible plant volatiles. Trends in Plant Science, 9(11), 529–533.
[14] Ana, U. R., Sugha, S. K. Role of cultural practices in the management of colocasia blight. Plant Disease Research, 2007, 22(1), 30-33.
[15] Brown, P. D., Morra, M. J. Control of soil-borne plant pests using glucosinolate-containing plants. Advances in Agronomy, 1997, 61, 167 231.
[16] Gonzales, A., Canto-Saenz, M. A. Comparison of five organic amendments for the control of Globodera pallida in microplots in Peru. Nematropica, 1993, 23, 133-139.
[17] Agustin, FT. Evaluating the Biofumigation Potentials of Various Brassica Species for the Control of Ralstonia solanacearum (E.F. Smith) Yabuuchi et al. Affecting Potatoes (Undergraduate thesis), Benguet State University, La Trinidad, Benguet, 2007. Retrieved on Nov. 10, 2017 from
[18] Gergon, E. B., Gapasin, R., Opina, O. S., Halbrendt, J. M. Evaluation of Rice Hull Burning for Management of Rice Root-Knot Nematode in Rice-Onion Cropping System, in Proceedings of the 31st Anniversary Scientific Convention of the Pest Management, 3-6 May 2000, Council of the Philippines, Baguio City, Philippines, 2000, pp 58-59.
[19] Sseruwagi, P., Sserubombwe, W. S., Legg, J. P., Ndunguru, J., Thresh, J. M. Methods of surveying the incidence and severity of cassava mosaic disease and whitefly vector populations on cassava in Africa: a review. Virus Research, 2004, 100(1), 129–142.
[20] Liu, J., Wang, X. Tomato diseases and pests detection based on improved Yolo V3 Convolutional Neural Network, Frontiers in Plant Science, Section Technical Advances in Plant Science, 2020, 11.
[21] Fening, K. O., Forchibe, E. E., Afreh-Nuamah, K. Neem as a cost-effective and potent biopesticide against the diamondback moth Plutella xylostella L. (Lepidoptera: Plutellidae) and the cabbage webworm Hellula undalis F. (Lepidoptera: Crambidae). West African Journal of Applied Ecology, 2020, 28(2), 52–63.
[22] Obi, M. E., Ebo, P. The effect of organic and inorganic amendments on soil. physical properties and production in a severely degraded sandy soil in southern Nigeria. Bioresource Technology, 1995, 51(2-3), 117-123.
[23] Song, Z., Gao, H., Zhu, P., Peng, C., Deng, A., Zheng, C., Mannaf, M. A., Islam, M. N., Zhang, W. Organic amendments increase corn yield by enhancing soil resilience to climate change Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing 100081, China. The Crop Journal, 2015, 3(2), 110–117.
[24] Kimpinski, J., Gallant, C. F., Henry, R., Macleod, J. A., Sanderson, J. B., Sturz, A. V. Effect of compost and manure soil amendments on nematodes and yields of potato and barley: a 7-year study. Journal of Nematology, 2003, 35(3), 289–293.
[25] Ghorbani, R., Koocheki, A., Jahan, M., Asadi, G. A. Impact of organic amendments and compost extracts on tomato production and storability in agroecological systems. (Impact of organic amendments and compost extracts on tomato production and storability in agroecological systems. Agronomy for Sustainable Development, 2008, pp. 307-311. ISSN: 1774-0746.
[26] Norsworthy, J. K., Brandenberger, L., Burgos, N. R., Riley, M. Weed suppression in Vigna unguiculata with a spring-seeded Brassicaceae green manure. Crop Protection, 2005, 24(5), 441-447.
[27] Om, H., Dhiman, S., Kumar, S., Kumar, H. Allelopathic response of Phalaris minor to crop and weed plants in rice-wheat system. Crop Protection, 2002, 21(9), 699-705.
[28] Ohno, T. K., Doolan, K., Zibilske, L. M., Liebman, M., Gallandt, E. R., Berube, C. Phytotoxic effects of red clover amended soils on wild mustard seeding growth. Agriculture, Ecosystems and Environment, 2000, 78(2), 187-192.
[29] Tiwari, R., Bashyal, M., Kanissery, R. Weed Management Strategies for Tomato Plasticulture Production in Florida. Plants (Basel), 2022, 29; 11(23), 3292.
Cite This Article
  • APA Style

    Samura, A. E., Watson, P. N., Amara, V., Norman, P. E., Saffa, M. D. (2024). Pests, Diseases, Growth and Yield of Tomato as Influenced by Variety and Cultivation Technology. Journal of Plant Sciences, 12(5), 122-137. https://doi.org/10.11648/j.jps.20241205.11

    Copy | Download

    ACS Style

    Samura, A. E.; Watson, P. N.; Amara, V.; Norman, P. E.; Saffa, M. D. Pests, Diseases, Growth and Yield of Tomato as Influenced by Variety and Cultivation Technology. J. Plant Sci. 2024, 12(5), 122-137. doi: 10.11648/j.jps.20241205.11

    Copy | Download

    AMA Style

    Samura AE, Watson PN, Amara V, Norman PE, Saffa MD. Pests, Diseases, Growth and Yield of Tomato as Influenced by Variety and Cultivation Technology. J Plant Sci. 2024;12(5):122-137. doi: 10.11648/j.jps.20241205.11

    Copy | Download

  • @article{10.11648/j.jps.20241205.11,
      author = {Alusaine Edward Samura and Pricellia Nornor Watson and Vandi Amara and Prince Emmanuel Norman and Musa Decius Saffa},
      title = {Pests, Diseases, Growth and Yield of Tomato as Influenced by Variety and Cultivation Technology
    },
      journal = {Journal of Plant Sciences},
      volume = {12},
      number = {5},
      pages = {122-137},
      doi = {10.11648/j.jps.20241205.11},
      url = {https://doi.org/10.11648/j.jps.20241205.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jps.20241205.11},
      abstract = {Tomato (Solanum lycopersicum L.) is one of the most important vegetables in the world. However, dearth of knowledge exists on cultivation technology that contributes to increased production of the crop. Meanwhile, low yielding varieties, high pests and diseases attacks, climate variability and poor soil fertility are among key production constraints that limit the increased production and productivity of tomato in Sierra Leone. A two-year field experiment was conducted at the School of Agriculture and Food Sciences experimental site during 2022 and 2023 to evaluate the effects of variety and cultivation technology (CT) on pests, diseases, growth, yield and productivity of tomato. The experiment was laid in a 2 × 4 factorial (i.e. two varieties of tomato, and four treatments: CT 1, CT 2, CT 3 and CT 4 known as control) arranged in a randomized complete block design (RCBD) with three replications. Results showed that organic (CT 1 and CT 2) and inorganic (CT 3) treatments had a positive impact on growth parameters of tomato. The CT 1 (chicken dung, mulching, and neem extract biopesticide) was most effective in promoting vegetative growth and higher fruit yield, while CT 2 (NPK 15:15:15, urea, promethrin herbicide, and chlorpyrifos pesticide) exhibited highest potency in reducing population and damage caused by diseases and pests. Findings demonstrate that improved variety and cultivation technology boost tomato tolerance to pests and diseases, as well as its growth and yield performances that could be exploited for increased production and fruit quality of the crop. The CT1 was the most effective, followed by CT 2, while CT 4 or control plots had the lowest performance. The outperformance of the organic treatments relative to the inorganic and control is suggested to be attributable to its nitrogen-rich components. Weed control was also established to be effective in both inorganic and CT 2 treatments. The findings suggest that the CT 1 should be promoted for sustainable tomato cultivation, prioritizing environmentally friendly methods for long-term success.
    },
     year = {2024}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Pests, Diseases, Growth and Yield of Tomato as Influenced by Variety and Cultivation Technology
    
    AU  - Alusaine Edward Samura
    AU  - Pricellia Nornor Watson
    AU  - Vandi Amara
    AU  - Prince Emmanuel Norman
    AU  - Musa Decius Saffa
    Y1  - 2024/09/06
    PY  - 2024
    N1  - https://doi.org/10.11648/j.jps.20241205.11
    DO  - 10.11648/j.jps.20241205.11
    T2  - Journal of Plant Sciences
    JF  - Journal of Plant Sciences
    JO  - Journal of Plant Sciences
    SP  - 122
    EP  - 137
    PB  - Science Publishing Group
    SN  - 2331-0731
    UR  - https://doi.org/10.11648/j.jps.20241205.11
    AB  - Tomato (Solanum lycopersicum L.) is one of the most important vegetables in the world. However, dearth of knowledge exists on cultivation technology that contributes to increased production of the crop. Meanwhile, low yielding varieties, high pests and diseases attacks, climate variability and poor soil fertility are among key production constraints that limit the increased production and productivity of tomato in Sierra Leone. A two-year field experiment was conducted at the School of Agriculture and Food Sciences experimental site during 2022 and 2023 to evaluate the effects of variety and cultivation technology (CT) on pests, diseases, growth, yield and productivity of tomato. The experiment was laid in a 2 × 4 factorial (i.e. two varieties of tomato, and four treatments: CT 1, CT 2, CT 3 and CT 4 known as control) arranged in a randomized complete block design (RCBD) with three replications. Results showed that organic (CT 1 and CT 2) and inorganic (CT 3) treatments had a positive impact on growth parameters of tomato. The CT 1 (chicken dung, mulching, and neem extract biopesticide) was most effective in promoting vegetative growth and higher fruit yield, while CT 2 (NPK 15:15:15, urea, promethrin herbicide, and chlorpyrifos pesticide) exhibited highest potency in reducing population and damage caused by diseases and pests. Findings demonstrate that improved variety and cultivation technology boost tomato tolerance to pests and diseases, as well as its growth and yield performances that could be exploited for increased production and fruit quality of the crop. The CT1 was the most effective, followed by CT 2, while CT 4 or control plots had the lowest performance. The outperformance of the organic treatments relative to the inorganic and control is suggested to be attributable to its nitrogen-rich components. Weed control was also established to be effective in both inorganic and CT 2 treatments. The findings suggest that the CT 1 should be promoted for sustainable tomato cultivation, prioritizing environmentally friendly methods for long-term success.
    
    VL  - 12
    IS  - 5
    ER  - 

    Copy | Download

Author Information
  • Abstract
  • Keywords
  • Document Sections

    1. 1. Introduction
    2. 2. Materials and Methods
    3. 3. Results and Discussion
    4. 4. Conclusions
    Show Full Outline
  • Abbreviations
  • Acknowledgments
  • Author Contributions
  • Funding
  • Conflicts of Interest
  • References
  • Cite This Article
  • Author Information