Optimization of irrigation-drainage scheme for tomato crop based on multi-index analysis and projection pursuit model

Abstract

Various indexes should be considered when developing a suitable irrigation and drainage scheme for crops. Our study chosen tomato as plant material and conducted a field experiment under saline soils. Nine treatments distinguished by different irrigation quotas and different drain ditch depths were used for the optimization of irrigation-drainage scheme. A flooding irrigation treatment with no surface drainage was adopted as control. The system of evaluation indexes was established in comprehensive consideration of the electrical conductivity and nutrient of soil, and the water use efficiency, nitrogen use efficiency, quality and marketable yield of tomato. Moreover, the multi-index analysis and projection pursuit (PP) model were used to evaluate the irrigation-drainage schemes according to the observed values of these six evaluation indexes. Results showed that different irrigationdrainage treatments decreased the electrical conductivity in plough layer by 24.6-51.3%, and increased the tomato water use efficiency and nitrogen use efficiency by 0.3-24.2% and 20.3-96.0%, respectively. The tomato marketable yield was increased by 14.4-31.3% with the irrigation-drainage treatments when compared to the control. As analyzed by the PP model, I3D1 (300 m 3 hm -2 of irrigation quota combined with 10 cm of ditch depth) was the treatment that possessed best comprehensive benefits due to the highest projection value of 1.6724 thus was recommended by this study as the optimal irrigation-drainage scheme.

Assessment on the coupling effects of drip irrigation and organic fertilization based on entropy weight coefficient model

“…The previous study by Zhai, Yang & Hou (2015) found that salt stress inhibited the growth of tomato fruit, thereby decreasing the weight of single fruit and the yield from a single plant. However, some studies revealed that slight salt stress improved the tomato quality and increased the concentration of nutrient in the fruit ( Hou & Shao, 2016 ; Wan et al, 2007 ). Even so, for those greenhouse soils subjected to strong evaporation and less water supply, the soil salinity was expected to be lower.…”

“…The total sugar content was measured using the Fehling reagent titration method. The total acid content was measured using the sodium hydroxide titration method ( Hou & Shao, 2016 ). The SAR is calculated as the ratio of total sugar to total acid content.…”

“…(4) Salt content in soil profile (g/kg). At seven days after the last irrigation (Sep 25), the soil samples in profile were collected using 5-point method as different soil layers of 0–20, 20–40 and 40–60 cm ( Hou & Shao, 2016 ). The 5 points were in a line that was perpendicular to the tomato row, including the edge of the soil ridge (two points), the dripper position (two points), and the middle of two drippers (one point).…”

Soil Salt Distribution and Tomato Response to Saline Water Irrigation under Straw Mulching

“…Hou [70] adopted the projection pursuit model to select the best drip irrigation scheme for crop. Other methods, such as principal component analysis, entropy weight coefficient model were also used for guiding the agricultural production [71].…”

Growth, Water Use, and Nitrate-15N Uptake of Greenhouse Tomato as Influenced by Different Irrigation Patterns, 15N Labeled Depths, and Transplant Times

“…ET is calculated using the water balance equation of the farm land (Hou and Shao, 2016): $\begin{array}{c}eqnarrayleft\mathrm{\text{ET}}=\mathrm{\text{P}}+\mathrm{\text{I}}+\mathrm{\text{U-R-D-}}\Delta \mathrm{\text{W}}\end{array}$ where, P is the valid rainfall (mm), I is the irrigation amount (mm), U is the groundwater recharge (mm), R is the runoff (mm), D is the deep percolation (mm), and ΔW is the variation of soil moisture before and after the experiment (mm). For this study, P, U (the ground water level is below 9 m), R and D can be ignored.…”