Abou Kamer, M., Khalil, G., yousry, M. (2022). Yield and Quality Performance of Some New Sweet Melon Lines Under Water Stress Conditions. Journal of the Advances in Agricultural Researches, 27(1), 148-161. doi: 10.21608/jalexu.2022.114554.1036
Mohamed E. Abou Kamer; Gamal Abdel-Nasser Khalil; Mona Mohamed yousry. "Yield and Quality Performance of Some New Sweet Melon Lines Under Water Stress Conditions". Journal of the Advances in Agricultural Researches, 27, 1, 2022, 148-161. doi: 10.21608/jalexu.2022.114554.1036
Abou Kamer, M., Khalil, G., yousry, M. (2022). 'Yield and Quality Performance of Some New Sweet Melon Lines Under Water Stress Conditions', Journal of the Advances in Agricultural Researches, 27(1), pp. 148-161. doi: 10.21608/jalexu.2022.114554.1036
Abou Kamer, M., Khalil, G., yousry, M. Yield and Quality Performance of Some New Sweet Melon Lines Under Water Stress Conditions. Journal of the Advances in Agricultural Researches, 2022; 27(1): 148-161. doi: 10.21608/jalexu.2022.114554.1036
Yield and Quality Performance of Some New Sweet Melon Lines Under Water Stress Conditions
1Cross-Pollination Vegetable Dept., Horticulture Research Institute; A.R.C., Egypt.
2Faculty of Agriculture Saba Basha Bolkely P.O. 21531
3Faculty of Agriculture Saba- Basha Alexandria University
Abstract
sweet melon is an important crop in Egypt in terms of cultivated area, total production, and consumption, whether domestic or export, in addition to its high nutritional value and high water content. One of the main reasons that hinder the horizontal agricultural expansion is the shortage of irrigation water. Therefore, this study was conducted under the drip irrigation system to legalize the use of irrigation water and increase water use efficiency through evaluating the number of sweet melon inbred lines that could maintain an acceptable level of productivity and quality characteristics under water shortage conditions. Seven inbred lines (genetic material) of sweet melon named: New Matrouh line (L1), Mass Matrouh line (L2) as a local ecotype, orange line (L3), Sandafa line (L4) as a local ecotype, Primal line (L5), Ideal line (L6) and Kooz Assal Assuit line (L7) as a local ecotype were planted under drip irrigation system during the summer seasons of 2017 and 2018. The experiment took place at the Experimental Farm, Faculty of Agriculture, Saba-Basha, Alexandria University, Egypt. Three irrigation rate treatments (40%, 70%, and 100% of ET0) were performed. The gained results revealed that the best results for plant length (cm) trait were achieved with the treatment of 100 % of evapotranspiration. Many branches/plant traits scored the highest mean values with the treatment of 40 % of evapotranspiration. Total fruit yield/plant (kg) character and its component traits [ no. of fruits/plant and average fruit weight (g)] were significantly affected by both studied variables (sweet melon genotypes and irrigation rates). As for the main effect of irrigation rates on total fruit yield/plant (kg) and its component traits, there is a significant and direct proportional relationship between the independent variable (irrigation rates) and dependent one (studied characters) during the two studied seasons. The significantly highest mean values for total fruit yield/f were scored at 100 % of irrigation rate during the two seasons, followed with the treatment 70 % of irrigation rate; while 40 % of irrigation rate treatment possessed the lowest mean values in this respect. Most studied fruit characteristics were not significantly affected by different tested irrigation rates from 100% down to 70%. The significantly lowest values for fruit characteristics were scored at 40% irrigation rate treatment. The results of the irrigation water use efficiency (IWUE) of the tested lines proved that the line Ideal (L6) is the best line under the conditions of irrigation shortage supply. Through the gained results over the two seasons of this investigation, it is recommended to select the inbred line "Ideal" (L6) because it is characterized by high productivity (kg/plant) at 100% irrigation rate or when there is a shortage of water supply (70% or even 40% of evapotranspiration) compared with other tested sweet melon genotypes; In addition to, its distinctiveness, to some extent, in their fruit characteristics.
Melon (Cucumis melo, L.), or sweet melon 2n = 2X = 24, is considered one of the most important crops of the cucurbita family, which enjoys a high market and export value (Naroui et al., 2015). Like many fruits and vegetables, melon is mostly water. One cup of fresh melon has 144 calories, 6% of your daily serving of fiber, zero fat, and cholesterol. Also provides 100% of the daily value for vitamin C, a powerful antioxidant that keeps the cells from damage. Melon contains vitamin A, which keeps the eyes, skin, bones, and immune system healthy. It also contains about 12% of recommended daily potassium, important for your heart, muscles, and blood pressure. Melon is also full of vitamins and minerals like folic acid, calcium, zinc, copper, and iron (Abdel-Aziz and Sadik, 2017 and Tabassum et al., 2021). The area cultivated locally in Egypt with cantaloupe and melon reached in the year 2019, 67836 fed. with a total production of 742570 tons with an average production of about 10.4 tons / fed. Most of this area is in newly reclaimed lands, which suffer greatly from the shortage of irrigation water, whether in terms of quality or quantity. Concerning the global cultivated area with all types of melon was 2569180 fed. with the average total productivity of 27501360 tons with average productivity of 10.7 tons/fed (FAOSTAT, 2020).
Many studies showed that there were significant increases in root length and decrease in shoot length under drought stress (Turkan et al., 2004). It is recognized that photosynthetic efficiency is the first physiological target of environmental stress, such as high temperatures, lack of water in the soil, and salinity (Liu and Huang 2008). Biotic and abiotic stresses are the most important factors that severely limit plant growth and metabolism (Makbul et al., 2011 and Giordano et al., 2021). A large proportion of cultivated land in the world is affected by poor quality or scarcity of water in the first place. Water scarcity is a major limiting factor in crop production (Wahb-Allah et al., 2011). Tolerance of drought is an important trait that has a linkage with yield and its components, so to improve this trait, underwater stress requires fundamental changes in the set of relevant attributes, finally emerging as something named drought tolerance (Maleki et al., 2013). Hence, the outstanding performance in light of the low amount of water is necessary to sustain the increasing demand in food production in many regions in the world. The future of irrigated agriculture poses the need to develop irrigation strategies using saline and deficit irrigation water to fulfill the food and fiber production gap, to ensure long-term sustainability in irrigated agriculture (Kuşçu et al., 2015 and Kapoor et al., 2020). In general, melon is known to be moderately resistant to drought. It has been shown that drought stress causes several types of damage such as growth inhibition. Therefore, this investigation is concerned to evaluate new sweet melon inbred lines, aiming at the possibility of expanding sweet melon cultivation in areas where is a shortage of irrigation water capable of meeting the growing needs for sweet melon, whether in the local or foreign markets.
MATERIALS AND METHODS
Location and date of the experiment
This experiment was carried out during two successive summer seasons of 2017 and 2018, at the Experimental Farm, Faculty of Agriculture, Saba-Basha, Alexandria University, Alexandria, Egypt. Sowing was accomplished on the 1st of April and 15th of March for the summer seasons 2017 and 2018, respectively.
Genetic material source
Seven inbred lines of sweet melon (Cucumis melo, L., 2n=2 X =24) named as; New Matrouh line (L1), Mass Matrouh line as a local ecotype (L2), orange line (L3), Sandafa line as a local ecotype (L4), Primal line (L5), Ideal line (L6) and Kooz Assal Assuit line as a local ecotype (L7). The previously mentioned inbred lines were kindly supplied by the breeding program for Improving the Cucurbitaceae Vegetables Project, Horticultural Research Institute, Agriculture Research Center, Egypt.
The soil of the experimental site
Some physical and chemical analyses of the experimental soil are presented in Table 1. Soil analysis demonstrated that the experimental soil has a sandy clay loam texture.
Table (1). Some physical and chemical properties of the experimental soil for the summer season in 2017.
Particle distribution
Sand
%
Silt
%
Clay
%
Texture class
pH
(1:1, water suspension)
EC (dS/m-1)
(1:1, water extract)
O.M.
%
Total CaCO3
%
55.9
20.4
23.7
Sand Clay Loam
7.8
0.44
0.30
32.0
Chemical analyses
Soluble cations (meq/L)
Soluble anions (meq/L)
Ca++
Mg++
Na+
K+
HCO3-
Cl-
SO4--
1.70
2.04
1.30
0.19
5.45
1.48
0.19
Nutrient available (mg kg-1)
KCl-extractable (N)
NaHCO3 extractable (P)
NH4-Ac-extractable (K)
116.3
21.0
430.0
Agricultural operations:
Seeds were sown on 209 cells tray on 1st April and on 15th March of seasons 2017 and 2018, respectively. Seedlings were transplanted 23-25 days after sowing. Two seedling were planted in each hole in terraces with a width of 1.5 m and a length of 30 m . After 35 days of planting the plants were thinned so that each hole became one plant, the experiment has been cultivated in three replicates, each replicate containing fifteen plants. Phosphorus fertilizer was applied at the rate of 150 kg/fed. in the form of mono-calcium phosphate (15.5 % P2O5) at soil preparation, plus 5 tons/fed. of compost were added. Nitrogen fertilizer was applied throughout the drip irrigation system at the rate of 50 kg N/fed. in the form of ammonium sulfate (21.0% N) after 30 days of planting. Potassium fertilizer was added at the rate of 50 kg K /fed in the form of potassium sulfate (48% K2O) throughout the drip irrigation system. The total amount of drip irrigation at different treatments was calculated. The irrigation numbers, the time, and the water quantity (m3); in every irrigation, are expressed in terms of time based on the rate of water flow through the drippers (4L/h.).The common cultural practices were carried out according to the recommended practices for commercial sweet melon production in the area.
Irrigation regime
A drip irrigation system was designed for the experiment. Distribution lines consisted of PVC pipe manifolds for each plot. The diameter of the polyethylene laterals was 16 mm and each lateral irrigated one plant row. The inline emitter discharge rate was 4 L h-1.
The values of reference evapotranspiration (ET0) were calculated using the Penman-Monteith method (Allen et al., 1998) with climatic conditions (Table 2) obtained for the experimental site (NASA, 2021) according to the following equation (Eq. 1):
Where:
ET0
Reference evapotranspiration, mm day-1
Rn
Net radiation at the crop surface, MJ m-2 day-1,
G
Soil heat flux density, MJ m-2 day-1, Generally very small and assumed to be zero).
T
Mean daily air temperature at 2.0 m height, °C,
U2
Wind speed at 2 m height, m s-1,
es
Saturation vapor pressure at 1.5 to 2.5m height, kPa,
ea
Actual vapor pressure at 1.5 to 2.5m height, kPa,
es -ea
Saturation vapor pressure deficit, kPa,
Slope vapor pressure curve, kPa°C-1,
g
Psychrometric constant, kPa°C-1.
Table (2). Some climatic conditions of the experimental site during the 2017 and 2018 growing seasons
Month
2017 Growing season
Pe
Mm
U2
m/s
RHm
%
Tdew
C°
Tx
C°
Tn
C°
Tm
C°
P
kPa
RA
MJ/m2/day
ET0
mm/season
April
51.51
3.98
69.61
12.37
21.32
15.66
18.22
101.52
36.59
173.17
May
0.05
3.81
68.43
15.43
24.92
19.07
21.78
101.33
39.98
228.39
June
4.09
3.83
67.59
18.01
27.68
22.14
24.66
101.18
41.19
208.96
2018 Growing season
March
2.04
4.03
63.94
11.19
21.66
15.23
18.19
101.34
32.79
116.05
April
2.68
3.67
66.90
13.29
23.03
16.82
19.61
101.32
36.56
206.14
May
0.00
3.93
69.26
16.93
25.90
20.34
22.84
101.05
39.96
236.28
June
0.01
3.65
65.98
18.69
28.25
23.01
25.48
101.02
41.19
227.63
The crop evapotranspiration (ETc) is the daily use of water by sweet melon and calculated using the following equation (Allen et al., 1998), Eq. 2:
Where:
Kc is the crop coefficient
The crop coefficient (Kc) values for different growth stages of the sweet melon (Allen et al., 1998) are shown in Table (4).
Table (3). Crop coefficient of sweet melon according to the growth stages
Growing stage
Kc value
Initial stage
0.50
Mid-stage
1.05
End-stage
0.70
The crop water requirements were calculated according to the Penman-Monteith equation (Allen et al., 1998) using the following equation (Cuenca, 1989), Eq. 3:
ETdrip is the crop water requirements under the drip irrigation system.
Kr is the reduction factor that reflects the percentage of irrigation treatments.
Irrigation water – use efficiency or water productivity (IWUE):
Irrigation water–use efficiency (IWUE) or water productivity (WP) was calculated as kg of fruits fresh weight yield produced per one cubic meter of applied water (Doorenbos and Kassem, 1979; Ahmed, 1987 and Sharma et al., 2015), Eq.4.
The plant measurements were recorded for vegetative characters, flowering date, and maturity date; average plant length (cm), the average number of branches/plant, flowering date (days), and fruit maturity date (days). The yield and yield components as total fruit yield/plant (kg), number of fruits/plant, and average fruit weight/plant (g) were recorded. The fruit characteristics such as fruit shape index were calculated as reported by Winiger and Ludwing (1974). Placenta hardness is graded on a scale from 1 to 10; whereas 1 denotes the soft placenta hardness and 10 refers to the extremely placenta hardness. Fruit netting degree: was graded on a scale from 1 to 10; 1 denotes the extremely smooth fruit skin, while 10 denotes the heavily rough skin fruit. Fruit skin color: was graded on a scale from 1 to 10; 1 denotes green skin, while 10 denotes yellow skin. Fruit total soluble solids (T.S.S.) were determined using the Zeiss hand refractometer and fruit moisture content was determined by oven drying.
Experimental design and statistical analysis
The experimental design was presented as a split-plot design with three replicates. Three irrigation rate treatments are named: I1 (40% of the ET0), I2 (70% of The ET0), and I3 (100% of the ET0) were assigned in the main plots, whereas, seven sweet melon genotypes were, randomly, distributed in the sub-plots. The collected data from the experiment were statistically analyzed using the analysis of variance method (Statistix, 2010). Comparisons among the means of different clones were carried out, using the Least Significant Differences (LSD) test procedure at p ≤ 0.05 level of probability, as explained by using Snedecor and Cochran (1980).
RESULTS AND DISCUSSION
1. Mean performances of the vegetative growth parameters, flowering and fruiting duration of sweet melon genotypes
The results presented in Table (4) are the averages of plant length, the number of main branches/plant, flowering, and fruiting duration as affected by sweet melon genotypes, irrigation rates (% ET0), and their combinations during the first and second seasons (2017 and 2018).
By comparing the performance averages of different traits it can be cleared that plants treated by irrigation rate (I3) and (I2) scored the tallest plants and highest branches number in the two seasons of study 2017 and 2018. Concerning flowering and fruiting duration irrigation rate (I1) enhanced the early flowering and reduced maturity duration for fruits (44.28 and 41.85 days) for the first female flower appearance for the two seasons of study 2017 and 2018, respectively and (84.19 and 84.85) days for first fruit was picked for two seasons of the study 2017 and 2018 respectively.
Concerning the performance of lines under study, L5 had the tallest plants (225.44 cm) in S1 2017, and L6 (212 cm) in S2 2018. L2 scored the highest branches number (5 and 4.77 branches in the two seasons of study). Regarding the flowering date, L7 scored the earliest flowering date (with 43.33 days to first flower appearance in S1 2017) and L6 (with 41.66 days to first flower appearance in S2 2018). In the maturity of fruit duration, L5 had the earliest maturity duration (with 84.66 and 83.88 days to first fruit picked in the two seasons of study). For irrigation rate x Lines interaction, in general, L4 and L5 in irrigation rate I3 (100 % of field capacity) scored the tallest plants in S1 2017, and L3 and L4 in S2 2018. But in irrigation rate I1 (40% of field capacity) L5 had the tallest plant (204.33 cm) in S1 2017 and L6 (182 cm) in S2 2018. L2 and L6 in irrigation rate I2 (70% of field capacity) scored the biggest branches number in S1 2017, and L6 in S2 2018. But in Irrigation rate I1 (40% of field capacity) L7 had the highest branches number (4 branches) in S1 2017 and L1, L6, and L7 (4 branches) in S2 2018. Regarding flowering date duration trait, L6 in irrigation rate I2 (70% of field capacity) had the earliest flowering date (41 days to first flower appears) in S1 2017, and L1 in irrigation rate I3 (100 % of field capacity) had the earliest flowering date (39.33days) in S2 2018. In the fruiting duration trait, L1 and L5 in irrigation rate I1 (40 % of field capacity) have the earliest fruiting duration in S1 2017, but L6 in I2 (70% of field capacity) has the earliest duration in S2 2018 Generally, the obtained data of Table (4) indicated that irrigation of the tested lines with the treatment of irrigation rate 40% leads to an early yield during the two study seasons; regardless of its quantity, compared with the other tested treatments of 70% and 100% irrigation rates. Similar results were found by Sebnem (2012), Tschoeke et al., (2015),Radet al., (2017) and Giordano et al., (2021) reported that the thirst or scarcity of water increases vegetative growth, such as plant height and the number of branches. Also, it was noticeable that early flowers appeared on plants and the speed of fruit ripening in an attempt for the plant to preserve its genes and pass them on to future generations in the event of exposure to unfavorable conditions. Seleiman et al., (2021) observed that the water scarcity in the soil harms the hormonal balance in the plant and causes reduced transfers from root to leaves and the accumulation of some acids in the leaves. It was noticed that increasing the concentration of some ions has a special effect on the activity of enzymes in the plant, therefore, the effectiveness of the dehydrogenase enzyme in the plant decreases when the water in the medium is decreased, this explains the decrease that occurs in the number of branches and the length and vegetative characteristics in general. Sebnem, (2012), Haitham et al., (2019), and Ashraful et al., (2020); where the authors reported that the performance of genotype differed from one irrigation rate to another because the durability of water scarcity varies from one genotype to another and this often may be largely due to hereditary reasons. The growth reduction that followed drought stress may be taken place to a massive and irreversible expansion of stomatic cells produced by less meristematic divisions, inhibition of cell expansion. It is well-known water stress resulted in less water content in tissues, which less in the turgor pressure of the cell, and the expansion of the cell, producing a decline in plant progress (Shao et al., 2007).
Table (4). Averages of the vegetative growth characters, flowering and fruiting duration of seven sweet melon genotypes as affected by three irrigation rates during two successive seasons of 2017 and 2018
Seasons
2017
2018
Treatments
Vegetative measurements
Flowering and fruiting duration
Vegetative measurements
Flowering and fruiting duration
plant length
(cm)
No. of branches/
plant
Days for first female flowering
(days)
Fruit maturity
(days)
plant length
(cm)
No. of branches/
plant
Days for first female flowering
(days)
Fruit maturity
(days)
Irrigation rates
40% (I1)
184.33c
4.09b
44.28b
84.19b
160.52c
3.76b
41.85b
84.85c
70% (I2)
211.52b
5.09a
45.23a
87.14a
198.90b
4.95a
44.23a
88.85b
100% (I3)
231.04a
4.95a
46.04a
88.90a
242.95a
4.76a
45.19a
91.95a
Genotypes (Sweet melon inbred lines)
Matrouh (L1)
195.11bc
4.55a
43.44cd
85.55b
185.44b
4.33ab
43.33b
89.11a
Mass Matrouh (L2)
213.77ab
5.00a
47.88b
89.00a
195.55ab
4.77a
45.88a
91.11a
orange line (L3)
188.88c
4.77a
44.33c
90.88a
205.00ab
4.33ab
42.77bc
91.55a
Sandafa (L4)
213.33ab
4.66a
49.88a
85.88b
204.55ab
3.88b
46.77a
89.22a
Primal (L5)
225.44a
4.55a
43.44cd
84.66b
198.33ab
4.44ab
42.22cd
83.88b
Ideal (L6)
213.33ab
4.77a
44.00cd
84.77b
212.00a
4.77a
41.66d
85.11b
Kooz Assal Assuit (L7)
212.88ab
4.66a
43.33d
86.44b
204.66ab
4.88a
43.66b
89.88a
Irrigation rates x Genotypes
I1×L1
167.00h
3.66c
43.33efg
83.00ef
150.00ij
4.00cde
39.33j
82.00hi
I1×L2
186.66fgh
4.33abc
43.66def
82.00f
146.66j
3.33e
41.00g-j
81.66hi
I1×L3
171.66gh
4.33abc
43.33efg
91.33ab
170.00gj
3.66de
40.66hij
88.66c-f
I1×L4
188.33fgh
4.00bc
47.66bc
84.33ef
158.33hij
3.66de
42.00f-j
85.33f-i
I1×L5
204.33def
3.66c
42.66fg
82.00f
166.66g-j
3.66de
42.00f-j
84.33f-i
I1×L6
191.66efg
4.00bc
46.00cd
83.66ef
182.00f-i
4.00cde
44.33d-h
87.66d-g
I1×L7
180.66fgh
4.66abc
43.33efg
83.00ef
150.00ij
4.00cde
43.66d-i
84.33f-i
I2×L1
205.00def
5.33ab
43.33efg
87.00be
189.66eh
4.66bc
44.66dg
90.33be
I2×L2
215.66bcde
5.66a
49.66ab
92.33a
205.00def
5.66a
47.33ad
95.00ab
I2×L3
196.66ef
4.66abc
44.33def
90.33a-d
190.66e-h
4.66bc
42.33e-j
91.66bcd
I2×L4
205.00def
4.66abc
50.66a
86.33def
182.00fi
4.33cd
48.66abc
89.00cf
I2×L5
226.66abcd
4.66abc
44.66def
85.33ef
195.00efg
5.33ab
43.00ej
84.33fi
I2×L6
215.66bcde
5.66a
41.00g
83.33ef
210.00def
4.66bc
40.33ij
81.33i
I2×L7
216.00bcde
5.00abc
43.00efg
85.33ef
220.00cde
5.33ab
43.33e-i
90.33b-e
I3×L1
213.33cde
4.66abc
43.66def
86.66cde
216.66cde
4.33cd
46.00b-e
95.00ab
I3×L2
239.00ab
5.00abc
50.33a
92.66a
235.00bcd
5.33ab
49.33ab
96.66a
I3×L3
198.33ef
5.33ab
45.33cde
91.00abc
254.33ab
4.66bc
45.33c-f
94.33ab
I3×L4
246.66a
5.33ab
51.33a
87.00b-e
273.33a
3.66de
49.66a
93.33abc
I3×L5
245.33a
5.33ab
43.00efg
86.66cde
233.33bcd
4.33cd
41.66f-j
83.00ghi
I3×L6
232.66abc
4.66abc
45.00def
87.33b-e
244.00abc
5.66a
40.33ij
86.33e-h
I3×L7
242.00a
4.33abc
43.66def
91.00abc
244.00abc
5.33ab
44.00d-i
95.00ab
Means followed by the same alphabetical letter within a column for each parameter are not significantly different from each other at the 0.05 level of probability by L.S.D. test procedure.
2. Mean performances of the yield and its component characters of sweet melon genotypes
Mean performances of yield components characters presented in Table (5) from comparing in general between three irrigation rate it can be concluded that plants which treated by irrigation rate (I2) and (I3) (70% and 100% from field capacity) scored the highest average fruit weight, fruit number and total fruit yield/plant in two study seasons 2017 and 2018.
Concerning the performance of lines under study, L6 had the highest average fruit weight, fruit number, and total yield (kg) (720.44 g, 5 fruits, and 3.64 kg) in S1 2017) and L6 (777.00 g) for
average fruit yield, L5 (4.88 fruits) for fruits number and L3 (3.25 kg) for total yield/plant in S2 2018. Concerning irrigation rate x Lines interaction, in general L3 in irrigation rate I3 (100 % of field capacity) scored the highest average fruit yield in S1 2017 and S2 2018 (861.66 g and 983.33 g respectively) and L6 in irrigation rate I3 (100 % of field capacity) gave the highest fruit number and total fruit yield in S1 2017, in S2 2018, L3 in irrigation rate I3 scored the highest average fruit weight (983.33 g) and total yield/plant (4.56 kg). for the number of fruits/plant in 2018, L7 in irrigation rate I2 and L5 in irrigation rate I3 have the highest scored. Leskovar et al., (2001) concluded that plants that are exposed to unusual conditions such as intense lighting, extreme cold, heat severe thirst, drowning, radiation, pollution, whether with toxic gases or an increase in the concentration of a certain gas like ozone, pathogen incidence. All those and other environmental stressors stimulate the production of the so-called active oxygen species. This is responsible for genes present in salt-tolerant plants that are capable of adapting under stress conditions, This explains the superiority of some strains over others under the same stress conditions, for example in Irrigation rate I1 (40% of field capacity) L6 had the highest average fruit weight and total yield/plant (kg) (493 g and 2.29 kg in S1 2017) (513 g and 2.05 kg in S2 2018). L2 scored the highest fruit number (5 fruits) in S1 2017 and L5 (4.33 fruits) in S2 2018 under the most water-scarce conditions. These results were in harmony with those found by Abd El-Mageeda and Semida (2015) , Widaryanto et al., (2017) and Kapoor et al., (2020). The yield and its components are among the traits that are severely affected by the shortage of water, but the comparison between the genotypes in the severity of their tolerance to water scarcity is useful in the different breeding programs that aim to produce strains that can stabilize with economic production under less favorable conditions such as irrigation water shortage. Ghosh et al., (2000) explained that the decline happened in total yield due to water stress may be ascribed to the lessening in leaf area due to fewer and small leaves, and the increase in stomatal resistance and gas exchange; along with, the reduction in transpiration ratio, which all resulting in a decline in photosynthesis.
Table (5). Averages of yield and yield components of seven sweet melon genotypes as affected by three irrigation rates during two successive seasons of 2017 and 2018
Seasons
2017
2018
Treatments
yield components characters
yield components characters
Average fruit weight (g)
No. of fruits/ plant
Total yield
(kg)/
plant
average fruit weight (g)
No. of fruits/
Plant
Total yield
(kg)/
Plant
Irrigation rates
40% (I1)
425.42c
4.04b
1.72c
426.19c
3.52c
1.50c
70% (I2)
660.71b
4.52ab
3.00b
677.38b
4.66a
3.15b
100% (I3)
753.47a
4.71a
3.57a
850.00a
4.42b
3.69a
Genotypes (Sweet melon inbred lines)
Matrouh (L1)
554.77de
4.44ab
2.44c
648.88b
4.00bc
2.67bc
Mass Matrouh (L2)
631.11bc
5.11a
3.25ab
656.66b
4.33ab
3.00ab
orange line (L3)
696.11ab
4.00bc
2.87bc
751.66a
4.22b
3.25a
Sandafa (L4)
617.77cd
3.88bc
2.43cd
626.66bc
3.55c
2.26c
Primal (L5)
542.22e
5.00a
2.71c
528.33d
4.88a
2.62bc
Ideal (L6)
720.44a
5.00a
3.64a
777.77a
4.44b
3.08ab
Kooz Assal Assuit (L7)
530.00e
3.55c
1.96d
568.33cd
4.04ab
2.62bc
Irrigation rates x Genotypes
I1×L1
388.33ef
4.33a-d
1.68hi
390.00j
3.33ef
1.28h
I1×L2
433.33ef
5.00ab
2.16gh
418.33hij
2.66f
1.14h
I1×L3
476.66e
3.33de
1.60hi
500.00ghi
3.66def
1.82gh
I1×L4
470.00e
3.33de
1.57hi
400.0ij
3.33ef
1.53h
I1×L5
363.33f
5.00ab
1.82hi
361.66j
4.33b-e
1.54gh
I1×L6
493.00e
4.66abc
2.29e-h
513.33gh
4.00cde
2.05fgh
I1×L7
353.33f
2.36e
0.92i
400.00ij
3.33ef
1.53h
I2×L1
596.66d
4.66abc
2.82d-g
656.66f
4.33b-e
2.84def
I2×L2
636.66d
5.00ab
3.19b-e
638.33f
3.66def
3.63a-d
I2×L3
750.00bc
4.00bcd
3.00d-g
771.66de
4.33b-d
3.35bcd
I2×L4
626.66d
4.00bcd
2.49d-h
633.33f
3.66def
2.35efg
I2×L5
600.00d
5.33a
3.21b-e
621.66f
5.00abc
3.10cde
I2×L6
810.00ab
5.00ab
4.05ab
790.00d
4.33b-e
3.43bcd
I2×L7
605.00d
3.66cd
2.22fgh
630.00f
5.33ab
3.37bcd
I3×L1
679.33cd
4.33a-d
2.95d-g
900.00bc
4.33b-e
3.88abc
I3×L2
823.33ab
5.33a
4.40a
913.33bc
4.66a-d
4.23ab
I3×L3
861.66a
4.66abc
4.01abc
983.33ab
4.66a-d
3.77a-d
I3×L4
756.66abc
4.33a-d
3.24bcd
846.66cd
3.66def
3.08cde
I3×L5
663.33cd
4.66abc
3.11c-f
601.66fg
5.33ab
3.20cde
I3×L6
858.33a
5.33a
4.57a
1030.00a
5.66a
4.56a
I3×L7
631.66d
4.33a-d
2.74d-g
675.00ef
4.66a-d
3.14cde
Means followed by the same alphabetical letter within a column for each parameter are not significantly different from each other at the 0.05 level of probability by L.S.D. test procedure.
3. Mean performances of fruit characteristics of sweet melon genotypes
Performances of the plant under different irrigation treatments in fruit measurements are presented in Table (6) from comparing characters performance under the three irrigation rates it can be noticed that plants which treated by irrigation rate (I3) (100% from field capacity) scored the highest values of all fruit measurements in the two seasons of study 2017 and 2018.
Concerning the Mean performance of lines under study, L6 had the highest netting degree (8.44) in S1 2017 and L5 and L7 (8.88) in S2 2018. L6 exhibited an oval shape index and by that this characteristic is less affected by environmental conditions, it was constant in the two seasons. Most yellow darkness was found in L6 in S1 2017 and L7 in S2 2018 (9 in two seasons). In total soluble solids, L5 scored the highest values in two seasons of the study S1 2017 and S2 2018 (13.31 and 13.71% respectively), highest moisture content was exhibited by L6 in two seasons S1 2017 and S2 2018 (93.15 and 94.07 respectively). Irrigation rate x Lines interaction, lines which outperformed under the most severe stress conditions (I1 = 40% from field capacity), were L4 in fruit netting degree (8.33), L6 in fruit shape index (1.28), L1, L2, and L4 in skin color (8 degrees for the darkness of yellow color), L5 in total soluble solids percentage % (12.13) and L6 in moisture content % (92.3%) on S1 2017. In S2 2018, L5 in fruit netting degree (7.66), L6 in fruit shape index (1.03), L7 in skin color and total soluble solids (7.66 and 12.36 respectively), and L4 in moisture content % exhibited the highest values overall lines on the study, Hence, it can be said that these traits cannot be neglected except for the fruit shape index, as it characterizes the variety or strain and is fairly stable under any circumstances. These results were in disagreement with those found by Erdem et al., (2001) and Erdem and Yuksel (2003) on watermelon. The authors found a positive relationship between water shortage and traits like total soluble solids content; where the increasing of shortage irrigation water rate led to an increase in the percentage of the total soluble solids (T.S.S.). The results of this study are in agreement with those found by Ashraful et al., (2020); where the authorsfound that the fruit quality characteristics were strongly affected by the shortage of irrigation water rates and also by the increase in the amount of irrigation water. It is necessary to moderate the amount of irrigation water so that an increase will also work to disrupt these characteristics. The results of this experiment confirmed that the fruit shape index trait did not affect by the tested water rates as this trait is considered one of the genetic traits that distinguish each genotype and is almost unaffected by the environmental conditions (irrigation water rates) to a large extent; as also illustrated by Henane et al., (2015).
Table (6): Averages of fruit characteristics of seven sweet melon genotypes as affected by three irrigation rates during two successive seasons of 2017 and 2018
Seasons
2017
2018
fruit characteristics
fruit characteristics
Treatments
Fruit netting degree
Fruit shape index
Skin color
T.S.S
%
Moisture content%
Fruit netting degree
Fruit shape index
Skin color
T.S.S
%
Moisture content%
Irrigation rates
40% (I1)
7.14b
1.08a
7.52b
10.45c
90.94b
6.09c
1.01c
6.76b
11.18b
91.41b
70% (I2)
9.14a
1.06a
8.76a
12.52b
93.40a
8.76b
1.08b
9.19a
12.89a
92.91a
100% (I3)
9.23a
1.08a
9.28a
13.45a
93.92a
9.23a
1.13a
9.42a
13.06a
93.59a
Genotypes (Sweet melon inbred lines)
Matrouh (L1)
7.88b
1.08c
8.55a
12.2b
92.78a
8.11ab
1.15b
8.77a
12.54b
91.87c
Mass Matrouh (L2)
8.33ab
1.14b
8.33a
12.44ab
92.58a
8.33ab
1.15b
8.55a
12.95ab
92.75bc
orange line (L3)
8.55ab
1.04d
8.33a
12.27b
92.34a
7.44bc
1.02c
8.77a
13.40ab
92.52bc
Sandafa (L4)
9.22a
1.02d
8.33a
10.51c
92.75a
6.88c
1.01cd
6.88b
9.92c
93.58ab
Primal (L5)
8.66ab
1.02d
8.33a
13.31a
92.98a
8.88a
0.97d
8.66a
13.71a
92.16c
Ideal (L6)
8.44ab
1.21a
9.00a
11.15c
93.15a
7.66bc
1.22a
8.55a
10.78c
94.07a
Kooz Assal Assuit (L7)
8.44ab
1.01d
8.77a
13.12ab
92.68a
8.88a
0.99d
9.00a
13.35ab
91.55c
Irrigation rates x Genotypes
I1×L1
6.33d
1.09def
8.00a-d
11.33hk
90.77de
5.33gh
1.06e
6.66efg
11.36d-g
89.38f
I1×L2
6.66cd
1.16bcd
7.33cd
10.26jkl
90.16de
6.00fgh
1.03ef
6.33fg
10.9fgh
90.09ef
I1×L3
7.66bcd
1.02eh
8.00ad
10.10kl
90.05e
6.66efg
0.97fgh
7.00d-g
12.3cf
91.16def
I1×L4
8.33abc
1.03eh
8.00ad
8.70m
91.42b-e
4.66h
0.97fgh
5.66g
9.36h
93.46ad
I1×L5
8.00ad
0.98h
6.33d
12.13ei
90.89cde
7.66cde
0.98fgh
6.66efg
11.53dg
91.9be
I1×L6
6.33d
1.28a
7.66bcd
9.33im
92.30a-d
5.33gh
1.03ef
7.33def
10.46gh
92.84ad
I1×L7
6.66cd
1.03eh
7.33cd
11.33hk
90.99cde
7.00def
0.99e-h
7.66def
12.36cf
91.02def
I2×L1
8.33abc
1.08ef
8.33abc
12.20di
93.50ab
9.33ab
1.24b
9.66ab
13.40bc
92.21ae
I2×L2
9.33ab
1.10cde
8.00ad
12.70cg
93.96a
9.33ab
1.16cd
9.66ab
14.00abc
94.16ab
I2×L3
8.66ab
1.02eh
8.00ad
13.20ae
93.26ab
6.33efg
0.92h
9.33abc
14.36ab
93.24ad
I2×L4
10.00a
1.02eh
8.66abc
11.03ijk
93.01abc
8.66abc
1.02ef
8.00cde
10.03gh
93.38a-d
I2×L5
9.00ab
1.01fgh
9.33ab
13.56abc
93.83a
9.66ab
1.00efg
9.33abc
14.26ab
91.42cf
I2×L6
9.00ab
1.18b
9.66a
11.46gj
93.26ab
8.33bcd
1.22bc
8.33bcd
11.16eh
94.64a
I2×L7
9.66ab
1.02eh
9.33ab
13.50ad
92.97abc
9.66ab
0.99eh
10.00a
13.03bcd
91.34c-f
I3×L1
9.00ab
1.10de
9.33ab
13.06bf
94.06a
9.66ab
1.15d
10.00a
12.86be
94.03ab
I3×L2
9.00ab
1.16bcd
9.66a
14.36ab
93.67ab
9.66ab
1.26b
9.66ab
13.96abc
94.01ab
I3×L3
9.33ab
1.09def
9.00abc
13.53ad
93.72a
9.33ab
1.17cd
10.00a
13.53abc
93.16a-d
I3×L4
9.33ab
1.02eh
8.33abc
11.80fi
93.84a
7.33c-f
1.03ef
7.00d-g
10.36gh
93.76abc
I3×L5
9.00ab
1.07efg
9.33ab
14.23ab
94.23a
9.33ab
0.94gh
10.00a
15.33a
93.16ad
I3×L6
10.00a
1.17bc
9.66a
12.66ch
93.88a
9.33ab
1.41a
10.00a
10.73fgh
94.73a
I3×L7
9.00ab
0.99gh
9.66a
14.53a
94.07a
10.00a
0.98fgh
9.33abc
14.66ab
92.29ae
Means followed by the same alphabetical letter within a column for each parameter are not significantly different from each other at the 0.05 level of probability by L.S.D. test procedure.
4. Water requirements
The crop water requirements of sweet Melon as calculated with the Penman-Monteith method (Allen et al., 1998) using the local climatic conditions during the growth stages of Melon are presented in Table (7).
The water requirements of Melon were calculated as 3007.1, 2105.0, and 1202.8 m3/ha in the first season and 2417.3, 1692.1, and 966.9 m3/ha in the second season corresponding to 100, 70, and 40% of the ET0, respectively.
According to the obtained data, the late season or maturity stage of sweet melon has the highest water requirements, followed by the fruiting stage. This result may be due to that the maturity stage needs more water for fruit turgidity and maturity.
Table (7): Crop water requirements (m3/ha) during growth stages of Sweet Melon
2017 growing season
Irrigation deficit (% of ETo)
Growth Stages
100%
70%
40%
Initial (Germination)
450.2
315.1
180.1
Development(Vegetative)
699.1
489.4
279.6
Mid (Fruiting)
1298.4
908.9
519.4
Late (Maturity)
559.4
391.6
223.8
Total
3007.1
2105.0
1202.8
2018 growing season
Irrigation deficit (% of ETo)
Growth Stages
100%
70%
40%
Initial (Germination)
316.3
221.4
126.5
Development(Vegetative)
579.6
405.7
231.8
Mid (Fruiting)
997.1
698.0
398.9
Late (Maturity)
524.4
367.0
209.7
Total
2417.3
1692.1
966.9
Irrigation Water-Use Efficiency (IWUE)
When water is the limiting factor of crop production, water stress can improve WUE, so that available water is better allocated. Irrigation Water Use Efficiency (IWUE) is calculated as the harvested yield (kg) / amount of irrigation water (m3) according to the recommendations of the Food and Agriculture Organization (Doorenbos and Kassam, 1979). Among the many biotic and abiotic factors, the most important factors affecting productivity as well as the quality of production are the responsible and optimal management of water (Bhriguvanshi etal., 2012 and Tabassum et al., 2021).
The applied irrigation water was accounted as 3112.4, 2178.7, and 1244.9 m3/ha in the first season and 2659.1, 1861.3, and 1063.6 m3/ha in the second season for 100, 70, and 40% of the ET0 irrigation treatments, respectively.
The data of irrigation water-use efficiency (IWUE) is presented in Table (8). The results indicated that IWUE was significantly affected by irrigation levels, in which the recorded values increased with decreased irrigation levels. The irrigation level of 2178.7 and 1861.3 m3/ha (70% of ET0) in the two seasons possessed the highest values of IWUE (29.29 and 39.85 kg/m3, respectively). As seen from Table (8), the IWUE ranged between 24.19 and 29.29 kg/m3 in the first season and between 32.19 and 39.85 kg/m3 in the second season. Decreasing the irrigation water level resulted in a significant effect on IWUE.
In addition, IWUE was significantly (p<=0.05) affected by sweet Melon genotypes (Table, 8). The IWUE ranged between 18.49 and 36.14 kg/m3 in the first season and between 29.60 and 39.80 kg/m3 in the second season. The highest values attained for line L6 in both seasons and the lowest values attained with line L7 in the first season, but L4 has the lowest value in the second season.
As for the interaction between irrigation water treatments and sweet melon genotypes, the obtained data of Table (8) showed that IWUE was significantly affected (p ≤ 0.05) with these two independent variables during the two study seasons. The L6 and L3 genotypes with 70% of ET0 significantly gave the highest IWUE (39.58 kg/m3) in the first season. The line L2 gave the highest value of IWUE (45.88 kg/m3) followed by the line L6 which gave 43.35 kg/m3 for the IWUE in the second season. The high values for the IWUE regarding line L6 under water shortage conditions during the two study seasons could be attributed to the effect of the genotypic characteristic of this line.
The lower values of IWUE for the deficit irrigation treatment may be due to the lower values of sweet melon yield in both seasons. It can be concluded that sweet Melon is sensitive to water stress.
Table (8). Gross yield and Irrigation Water-Use Efficiency (IWUE) of Sweet Melon as affected by irrigation deficit, genotypes, and their interactions.
Treatments
Total Yield (ton/ha)
IWUE (kg/m3)
Total Yield (ton/ha)
IWUE (kg/m3)
2017
2018
Irrigation rates (% of ET0)
40% (I1)
37.84 c
28.47 a
34.22 c
32.80 b
70% (I2)
65.94 b
29.29 a
69.36 b
39.85 a
100% (I3)
78.63 a
24.19 b
81.27 a
32.19 c
Genotypes
Matrouh (L1)
54.63 cd
25.11 b
58.67 d
32.23 e
Mass Matrouh (L2)
71.50 ab
32.24 a
66.00 c
35.59 b
orange line (L3)
63.14 bc
27.65 b
67.83 b
40.15 a
Sandafa (L4)
53.53 d
24.08 b
51.04 f
29.60 f
Primal (L5)
59.69 cd
27.52 b
57.49 e
33.18 d
Ideal (L6)
80.00 a
36.14 a
71.35 a
39.8 a
Kooz Assal Assuit (L7)
43.12 e
18.49 c
58.96 d
34.07 c
Irrigation rates X Genotypes
40%
L1
36.96 hi
27.81 de
28.16 p
26.99 m
L2
47.52 fghi
35.75 abc
25.08 q
24.03 m
L3
35.20 hij
26.48 def
40.04 n
38.37 f
L4
34.54 ij
25.99 def
33.66 o
32.26 j
L5
40.04 ghi
30.12 cd
33.88 o
32.47 j
L6
50.38 defgh
37.91 ab
45.10 m
43.22 bc
L7
20.24 j
15.23 h
33.66 o
32.26 j
70%
L1
64.04 bcdef
27.56 de
62.48 k
35.89 h
L2
70.18 bc
31.17 bcd
79.86 e
45.88 a
L3
66.00 bcd
39.58 a
73.70 g
42.34 d
L4
54.78 cdefg
24.33 defg
51.70 l
29.70 k
L5
70.62 b
31.37 bcd
68.20 ij
39.18 e
L6
89.10 a
39.58 a
75.46 f
43.35 b
L7
48.84 efghi
21.69 efgh
74.14 g
42.59 cd
100%
L1
64.90 bcde
19.96 fgh
85.36 c
33.81 i
L2
96.80 a
29.78 cd
93.06 b
36.85 g
L3
88.22 a
27.14 de
100.32 a
39.73 e
L4
71.28 b
21.93 efgh
67.76 j
26.84 m
L5
68.42 bc
21.05 efgh
70.40 h
27.88 l
L6
100.54 a
30.93 bcd
82.94 d
32.85 j
L7
60.28 bcdef
18.54 gh
69.08 i
27.36 lm
Means followed by a similar letter within a column for each parameter are not significantly different from each other at the 0.05 level of probability by L.S.D. test procedure.
Thus, the main concern of deficit irrigation is that it maximizes water productivity, although some reduction in yields is observed. In regions where water is the limiting factor for crop production, maximizing water productivity by deficit irrigation is often more economically profitable for a farmer than maximizing yield.
Results of irrigation water use efficiency (IWUE); which were presented in (Table, 8), the importance of water deficit to obtain high yields and better usage of water, and this can be mainly attributed to adequate and homogeneous moisture distribution in the root zone in improving crop resistance to water stress (Abdelhamid et al., 2013 and Rahimizadeh et al., 2007).
Increases in water productivity under insufficient irrigation can be attributed to several reasons, one of which is that the negative effect of drought stress during certain growth stages on the division of biomass between reproductive and vegetative biomass (harvest index) is reduced (Fereres and Soriano, 2007; Reynolds and Tuberosa, 2008) due to increased reproductive organs (Karam et al., 2014). In this respect, Steduto et al., (2007) stated that increasing water production for net assimilation of biomass while relieving drought stress or increased crop hardening occurs due to the conservative behavior of biomass growth in response to transpiration. Water productivity for the net assimilations of biomass is increased due to the synergy between irrigation and fertilization (Steduto and Albrizo, 2005). Negative agronomic conditions are avoided during crop growth, such as pests, diseases, anaerobic conditions in the root zone due to waterlogging (Pereira et al., 2002; Geerts et al., 2008 and Tabassum et al., 2021).
CONCLUSION
water stress is referred to as a limited water supply to plant roots, which reduces the rate of transpiration in plants. It is mainly caused by a water deficit as a result of drought conditions. The thirst or scarcity of water increases vegetative growth, such as plant height and the number of branches. Also, it was noticeable that early flowers appeared on plants and the speed of fruit ripening in an attempt for the plant to preserve its genes and pass them on to future generations in the event of exposure to unfavorable conditions. Yield and its components are among the traits that are severely affected by the shortage of water, but the comparison between the genotypes in the severity of their tolerance to water scarcity is useful in the different breeding programs that aim to produce strains that can stabilize with economic production under unfavorable conditions such as lack of irrigation water. Fruit quality is strongly affected by the shortage in the amount of water and also by the increase in the amount of irrigation water, it is necessary to moderate the amount of irrigation water so that an increase will also work to disrupt these characteristics. There are characteristics such as the fruit shape index that are not affected by the amount of water as it is one of the characteristics of the variety.
References
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