Impact of soil moisture and temperature on potato production using ...

Agricultural Water Management 165 (2016) 230–236

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Impact of soil moisture and temperature on potato production using seepage and center pivot irrigation Xiaolin Liao a , Zhihua Su b , Guodong Liu a,∗ , Lincoln Zotarelli a , Yuqi Cui a , Crystal Snodgrass c a

Horticultural Sciences Department, University of Florida, Gainesville, FL 32611, USA Statistics Department, University of Florida, Gainesville, FL, 32611, USA c Manatee County Extension, UF/IFAS, Palmetto, FL 34221, USA b

a r t i c l e

i n f o

Article history: Received 23 June 2015 Received in revised form 19 October 2015 Accepted 25 October 2015 Available online 18 November 2015 Keywords: Irrigation Water table Potato yield Volumetric soil water content Soil temperature

a b s t r a c t Irrigation, soil moisture and temperature play an important role in potato production. This field study was conducted at a private potato farm in SW Florida from 2012 to 2014. The randomized complete block design was used: four production farms each with a pair of seepage and hybrid center pivot irrigation systems. Soil moisture and temperature at five soil depths, rainfall, and water table in situ were monitored. Nitrate levels at the top 20 cm soils were measured at harvest in the second growing season. Water usage was calculated by the flow meters and rain gauges. Potato yields were measured. The stepwise linear regression showed that the potato yield was mainly regulated by the surface (10 cm) soil temperature and soil water moisture at 20 and 30 cm depths. Hybrid center pivot can save more than 50% of irrigation water without significant yield loss, suggesting center pivot has great potential in water savings. Hybrid center pivot irrigation had relatively low nitrate concentrations at the top 20 cm soil, indicating a new fertilizer program may be needed for overhead irrigation. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Potato (Solanum tuberosum L.) is a shallow rooted crop and extremely sensitive to water stress (Jefferies and Heilbronn, 1991; Fabeiro et al., 2001; Alva et al., 2012). The deficit irrigation is not practical for commercial potato production (Alva et al., 2012). Florida is ranked 7th nationally for its potato production with a value of $ 146 million and produces one-third of the winter/spring crop in the nation (Mossler and Hutchinson, 2014). Because of its high economic value, growers may opt to apply excessive amounts of water and nutrients as an “insurance” to minimize production risks (Trippensee et al., 1995). Seepage irrigation for commercial potato production is the predominant practice in Florida (Smajstrla et al., 2000; Zotarelli et al., 2013a). With seepage irrigation, the water table is managed based on the target depth to irrigate the crop. This type of irrigation involves pumping groundwater to maintain the desired depth to the water table. The water table in the field is controlled at a depth just below the plant root zone by either adding or removing

∗ Corresponding author. Fax: +1 352 846 0909. E-mail addresses: guodong@ufl.edu, [email protected] (G. Liu). http://dx.doi.org/10.1016/j.agwat.2015.10.023 0378-3774/© 2015 Elsevier B.V. All rights reserved.

water from the field. As a result, seepage irrigation is likely to input excessive water to raise the water table, which frequently results in water and nutrient/fertilizer loss through deep drainage and runoff. In contrast, sprinkler irrigation, namely, overhead irrigation has greater water-use efficiency compared to seepage irrigation (Simonne et al., 2002). Overhead irrigation has also shown potential to improve water quality by reducing nutrient leaching associated with high irrigation volume application (Singh et al., 2011). Using soil moisture measurements is one of the best and simplest ways to get feedback to help make improved water management decisions (Peters et al., 2013). Soil moisture sensors can be used to determine the appropriate interval between irrigation events, depth of wetting, depth of extraction by roots and adequacy of wetting (Hanson et al., 2000). Besides, soil temperature can affect soil microbial processes and the nutrient movement in the soil, which will further have a great influence on plant growth (Wilkinson 1967; Power and Willis, 1975; Reddell et al., 1985). Both soil water and temperature have been shown to influence potato plant growth and tuber production (Epstein 1966; Singh 1969; Wang et al., 2005). Various models have been developed to predict potato yields, among which soil water and temperature are considered as the core parameters (Hartz and Moore, 1978; MacKerron and Waister, 1985; Jefferies and Heilbronn, 1991; Kooman and

X. Liao et al. / Agricultural Water Management 165 (2016) 230–236 Table 1 Soil particle size distributions of the four farms. Farm ID

Sand (%) >0.05

1 2 3 4

94.8 94.7 95.8 95.4

± ± ± ±

0.2 0.5 0.1 0.1

Silt (%) 0.05–0.002 1.9 2.5 1.7 1.8

± ± ± ±

0.2 0.3 0.0 0.2

Clay (%) 0.5) in soil moisture content at 10, 20, 30 cm (Table 4). Overall, water table showed significant correlation with soil moisture at 20 and 30 cm for both irrigation systems (Table 4 and Fig. 3). Munoz-Arboleda and Hutchinson (2006) reported that water table depth under seepage irrigation was an effective indicator of soil moisture at 20, 30, 40 cm. They suggested that a variable water table depth for different growth stages optimized soil moisture in the potato root zone which minimized the tuber internal problems of potato tubers such as hollow heart and brown center. The influence of the water table on soil moisture varied with different soils. For sandy soils, the water table plays little role as a source if it is below the root zone (Miguez-Macho et al., 2008). In our study, the water table fluctuated between 60 and 120 cm below the soil surface (Fig. 3). Fluctuation in water table had little impact on the soil water content at the soil depth of 70 cm where the soil was saturated with comparatively stable soil VWCs exceeding 30% (Fig. 3). For seepage irrigation, the water table can affect the soil moisture content as deep as 50 cm soil depth whereas for center pivot, the water table was likely to have less influence on the 50 cm soil depth but greater influence on the top 10–20 cm soil compared to seepage irrigation (Table 4). Though we rarely found similar studies as ours, the different response of soil moisture at different depths to water table between the two irrigation systems was somehow intuitive because of the distinct water movement unique to the two irrigation methods. For the hybrid irrigation system with seepage and center pivot, the downward and upward water movement would contribute to the high correlation of water table with soil moisture content at top 10 cm soil whereas the upward water movement for seepage was more likely to affect the deeper soil.

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X. Liao et al. / Agricultural Water Management 165 (2016) 230–236

Fig. 3. Water table depth below soil surface (m), rainfall, and soil volumetric water content at five soil depth (0.1 m, 0.2 m, 0.3 m, 0.5 m, and 0.7 m), monitored at seepage (left) and hybrid center pivot (right) at farms 1–3 during 2013/14 season. The data for farm 4 was excluded due to the failure of the water level sensor.

Table 4 Linear regression between water table depth (WD) and soil water volumetric content (VWC) at different soil profile depths at the three farms* . Farm ID

Soil depth (m)

Seepage

Center pivot

1

0.1 0.2 0.3 0.5 0.7

VWC = −4.8 WD + 18.4, R2 = 0.45 VWC = −5.8 WD + 25.7, R2 = 0.66 VWC = −4.5 WD + 31.2, R2 = 0.63 VWC = −16.4 WD + 41.7, R2 = 0.34 VWC = −9.4 WD + 46.5, R2 = 0.17


2

0.1 0.2 0.3 0.5 0.7



3

0.1 0.2 0.3 0.5 0.7

VWC = −7.0 WD + 16.5, R2 = 0.34 VWC = −9.0 WD + 25.2, R2 = 0.77 VWC = −11.5 WD + 32.1, R2 = 0.85 VWC = − 13.6 WD + 35.0, R2 = 0.72 VWC = −1.6 WD + 27.2, R2 = 0.27

VWC = −9.2 WD + 26.8, R2 = 0.83 VWC = −9.2 WD + 22.2, R2 = 0.81 VWC = −11.2 WD + 31.9, R2 = 0.81 VWC = − 14.2 WD + 40.1, R2 = 0.20 VWC = −0.7 WD + 27.7, R2 = 0.07

*

Farm 4 was not included due to the failure of the water levelogger. The bold R2 highlighted those with R2 > 0.5, all relationship were significant with P < 0.05.

3.4. Factors that affect yields Considering all variables, the moisture contents at 20 and 30 cm depth (i.e., mois2 and mois3) as well as temperature at 10 cm (temp1) were considered as significant predictors in the model (R2 = 0.776, Table 5). The linear model Potato yield = 208.62 − 7.475 × temp1 + 398.517 × mois2 – 299.66 × mois3 can be written as Potato yield = 208.62 where − 7.475 × temp1 + 98.856 × mois3 − 398.517 × mois dif mois dif equals mois3 – mois2.

The negative coefficient of the surface soil temperature at 10 m depth suggests that potato yield is negatively impacted by high temperature. The effects of temperature on potato production were discussed and various ranges of the optimum temperatures for maximum potato yields have been proposed (Isleib and Thompson, 1959; Yamaguchi et al., 1964; Epstein, 1966). In our study, the temperature at the surface soil varied from less than 10–30 ◦ C. There was no significant linear correlation between soil temperature and water table depth. The soil temperature at 10 cm soil depth was


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Fig. 4. Box-whisker plots for soil temperatures at five soil depths (i.e., 0.1, 0.2, 0.3, 0.5, 0.7 m) at the four sites during 2013/14 season. The strips show the median, the whiskers show the maximum and minimum values and the box shows the inter-quartiles.

Table 5 Linear regression of potato yield with soil temperature and soil volumetric water content at different depths by forward stepwise procedure during the two growing seasonsa . Coefficient Original variables 208.62 Intercept temp1 −7.475 mois2 398.517 mois3 −299.66 Transformed variables 208.62 Intercept temp1 −7.475 mois3 98.856 mois dif −398.517

Standard Error

t value

P value

20.23 1.121 96.509 95.603

10.313 −6.666 4.129 −3.134

***

20.23 1.121 34.297 96.509

10.313 −6.666 2.882 −4.129

***

*** *** **

*** ** ***

a

temp1: soil temperature at 0.1 m soil depth; mois2 and mois3: soil volumetric water content at 0.2 m and 0.3 m depth, respectively; mois dif: difference in soil volumetric water content between 0.3 m and 0.2 m depth. R2 = 0.7759, F3,28 = 32.31. ** P < 0.01. *** P < 0.001.

that large variations of soil moisture across the depth will reduce potato yield. We did not, however, find other studies that reported the same results. As aforementioned, water table was significantly correlated with soil mois2 and mois3 (Table 4), therefore, it is easier to understand that appropriate irrigation system is the key for increasing tuber yield by regulating soil water moisture. Our regression model highlighted the effects of temperature and soil moisture at specific soil depths on potato yields. Similarly, Fabeiro et al. (2001) established a linear function between potato yield and the volume of water received in different stages of potato growth in a semi-arid zone of Spain. These statistical models were performed ad-hoc with other factors fixed and had limited power in predicting the actual yields. More factors such as soil properties (e.g., nutrient levels and soil water), weather, and management (e.g., planting, irrigation, fertilizer, and harvesting) are needed to give a more reasonable prediction on tuber yields (Ritchie et al., ˇ 1995; St’astná et al., 2010).

4. Conclusions more likely to be regulated by the air temperature (Zheng et al., 1993). The positive coefficient with soil mois3 was consistent with most of the literature that a high soil moisture content should be maintained at all stages of plant growth to obtain high tuber yields (Singh, 1969). The negative coefficient with soil mois dif indicates

In this study, we had four sites for potato trials in southwest Florida to compare water usage and potato tuber yields between seepage and hybrid center pivot irrigations. The hybrid center pivot irrigation contributed to 55% savings on average of irrigation water as compared to that with seepage irrigation only, with no signifi-

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cant difference in tuber yields between the two irrigation methods. More trials are needed to monitor tuber yields and nutrient status in the two irrigation systems. Water table depth was an effective predictor of volumetric soil water content, particularly at the soil depth of 20–30 cm. Most importantly, the temperature at the surface soil (20 cm soil depth), and the soil moisture content at 20–30 cm depth were considered as the significant factors that affected potato yields. Different irrigation practices regulate the water table which further controls the soil moisture dynamics. A better understanding of the correlation between water table, soil moisture content, and soil temperature can help make proper water management decisions. Acknowledgments The authors express their gratitude to Ed Hanlon, Professor Emeritus at the University of Florida for reviewing the manuscript, to Alan Jones at Jones Potato Farm for providing the farmlands for this research, to David Fleming and Jesse Cavillo, Farm Managers on the farm and Benjamin Hogue and Doron Moshe, Biological Scientists, at the University of Florida for their field help. This study is supported by Southwest Florida Water Management District (13C00000017) and National Science Foundation DMS-1407460. References Akaike, H., 1974. A new look at the statistical model identification. IEEE Trans. Autom. Control 19, 716–723. Alva, A., Moore, A.D., Collins, H.P., 2012. Impact of deficit irrigation on tuber yield and quality of potato cultivars. J. Crop Improv. 26, 1–17. Boman, B., Obreza, T., 2012. Water table measurement and monitoring for flatwoods citrus. Available online at: http://edis.ifas.ufl.edu/ch151. Dukes, M.D., Zotarelli, L., Liu, G.D., Simonne, E.H., 2012. Principles and practices of irrigation management for vegetables. http://edis.ifas.ufl.edu/cv107. Epstein, E., 1966. Effect of soil temperature at different growth stages on growth and development of potato plants. Agron. J. 58, 169–171. Fabeiro, C., Martín de, S.O.F., de Juan, J.A., 2001. Yield and size of deficit irrigated potatoes. Agric. Water Manag. 48, 255–266. Foroud, N., Lynch, D.R., Entz, T., 1993. Potato water content impact on soil moisture measurement by neutron meter. Plant Soil 148, 101–106. Hanson, B.R., Orloff, S., Peters, D., 2000. Monitoring soil moisture helps refine irrigation management. Calif. Agric. 54 (3), 38–42, http://dx.doi.org/10.3733/ ca.v054n03p38. Harris, P.M., 1978. In: Harris, P.M. (Ed.), The potato crop: the scientific basis for improvement. Chapman and Hall, London, pp. 244–277. Hartz, T.K., Moore III, F.D., 1978. Prediction of potato yield using temperature and insolation data. Am. Potato J. 55, 431–436. Isleib, D.R., Thompson, N.R., 1959. The influence of temperature on the rate of root and sprout growth of potatoes. Am. Potato J. 36, 173–178. Jefferies, R.A., Heilbronn, T.D., 1991. Water stress as a constraint on growth in the potato crop. 1. Model development. Agric. Forest Meteorol. 53, 185–196. Kooman, P.L., Haverkort, A.J., 1995. Modelling development and growth of the potato crop influenced by temperature and daylength: LINTUL-POTATO. Potato Ecol. Modell. Crops Cond. Limiting Growth 3, 41–59. Lemmelä, R., Sucksdorff, Y., Gilman, K., 1981. Annual variation of soil temperature at depth 20 to 700 cm in an experimental field in Hyrylä, South-Finland during 1969 to 1973. Geophysica 17, 143–154. MacKerron, D.K.L., Waister, P.D., 1985. A simple model of potato growth and yield Part 1. Model development and sensitivity analysis. Agric. For. Meteorol. 34, 241–252. Miguez-Macho, G., Li, H., Fan, Y., 2008. Simulated water table and soil moisture climatology over North America. Bull. Am. Meteorol. Soc. 89, 663–672.

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