Isabel Abrisqueta

Stem water potential estimation of drip-irrigated early-maturing peach trees under Mediterranean conditions

Seasonal Ψstem is a useful diagnostic tool for peach tree irrigation management.The autumn rainfall events point to the resilient behaviour of the peach cultivar studied.The soil water content was the main contributor to Ψstem estimation.Ψstem was estimated by regression equation of soil water content, GDH and VPDm data. In the last decade deficit irrigation strategies allowed growers to deal with water shortages, while monitoring stem water potential (Ψstem) is deemed essential for maximising fruit yield and quality. However, because of the intensive labour involved in measuring Ψstem, alternative methods are desirable. The experiment described was conducted in Murcia (Spain) with adult peach trees (Prunus persica (L.) Batsch cv. Flordastar) submitted to different drip irrigation treatments, measuring Ψstem with a pressure chamber and the soil water content with a neutron probe. Agro-meteorological variables were recorded. Seasonal patterns of stem water potential provide a useful diagnostic tool for irrigation management in peach trees. Rainfall events and the meteorological conditions prevailing in autumn pointed to the resilient nature of the peach cultivar studied. Fitting Ψstem by linear regression analysis as a function of soil and atmosphere yielded a significant correlation, with the soil water content being the main contributor to estimating Ψstem. Linear regression analysis highlighted the importance of considering plant water status as a function of the peach tree cultivar, the atmospheric conditions in which it develops and the soil water conditions resulting from irrigation. A multiple linear regression equation based on soil water content in the soil profile, mean daily air vapour pressure deficit (VPDm) and growing degree hours (GDH) data explained 72% of the variance in Ψstem, and is proposed as an alternative to the field measurement of Ψstem.

Soft computing applied to stem water potential estimation

Soft computing was applied to agro-meteorological and soil moisture data.Soil moisture at 0.3m, day of year and air temperature were the most relevant inputs.Fuzzy rules-based model with only 5 rules estimated Ψ st with 86% variance explained.Supplied agro-linguistic terms improved the interpretability of the fuzzy rules.The model was almost as accurate as artificial neural networks, while being simpler. Measuring the stem water potential ( Ψ st ), which is an essential parameter for assessing plant water status, is a tedious and labor-consuming task. In this work, hybrid soft computing techniques were applied to design a model able to estimate Ψ st based on agro-meteorological and soil water content data. A Takagi-Sugeno-Kang fuzzy inference system (TSK-FIS) was obtained. This kind of model approximates non-linear systems by combining a set of functions local to fuzzy regions described by fuzzy rules. Such models have approximative power and are sufficiently descriptive. Starting from a set of input-output data, inputs relevant to Ψ st were automatically selected and fuzzy rules were identified based on the fuzzy clusters found in the data. The rule parameters were optimized by means of a neuro-fuzzy approach. The result was an accurate (86% variance explained) and simple model with five rules that considered soil water content at 0.3m depth, the day of the year and mean daily air temperature as input variables, confirming the suitability of such approach. In addition, a rule simplification method allowed a consistent agro-linguistic interpretation of the fuzzy sets of the rules: DRY, MOIST and WET for the soil water content, BLOOM, FRUIT GROWTH, EARLY POSTHARVEST and LATE POSTHARVEST for the day of the year, and COLD, MILD and WARM for mean daily air temperature.

Persimmon (Diospyros kaki) Trees Responses to Restrictions in Water Amount and Quality

Abstract Persimmon cultivation is gaining importance in many semiarid areas of the world. In this chapter, existing information in the literature on persimmon water requirements and responses to variations in water supply and quality are summarized. It is concluded that persimmon water needs can be particularly high during summer, when the crop coefficient can reach values close to or even above 1.0. To cope with water scarcity, regulated deficit irrigation (RDI) has been shown as a useful technique for reducing fruit drop in persimmon trees. Late RDI strategies during fruit ripening can accelerate fruit color development resulting in earlier harvesting but with lower fruit weight. This chapter also provides important information on persimmon tree responses to salinity, along with methods to alleviate the detrimental impacts of low-quality irrigation waters on tree performance.

Water Management of Irrigated Cabernet Sauvignon Grapevines in Semi-Arid Areas

The effect of four years of deficit irrigation on water savings, yield, crop load, plant growth, and juice composition was determined on Cabernet Sauvignon grapes grown on the Central Coast of California. The growing season was divided into three periods. The first was from budburst to fruit set, during which there was no irrigation. The second was from fruit set to three weeks post-fruit set, during which 75% of calculated crop water use (ETc) was applied for all treatments. The third began three weeks post-fruit set and continued to harvest, during which irrigation resumed whenever the leaf water potential (LWP) reached −1.2 MPa in one of three sustained deficit irrigation treatments equal to 25/35% (LOW), 50% (MED), and 75/65% (HIGH) of ETc. The sum of rainfall and irrigation applied during the growing season ranged from 91 to 196 mm, from 145 to 234 mm, and from 198 to 273 mm for the LOW, MED, and HIGH treatments, respectively. Total water use, including soil water during the growing season, ranged from 250 to 359 mm, 288 to 418 mm, and 313 to 378 mm for the LOW, MED, and HIGH treatments, respectively. Yield was linearly related to the sum of irrigation and rain and to the total available water (rain, irrigation, and stored soil water) during the growing season. Yield was consistently lower in the LOW treatment across all years than in the MED and HIGH treatments; while yields in the MED and HIGH treatments were not different. Average pruning weight and cane weight declined in all treatments over the four years of the study, as did average berry size. Berry and wine composition was not affected by irrigation treatment within a given year, but were different across years due to climate, irrigation schedules, and harvest dates. Our results illustrate potential applied water savings during the growing season with moderate deficit irrigation (i.e., MED), with minimal or no significant effect on fruit yield and juice composition, while severe reduction of applied water (i.e., LOW) led to loss of yield without changing juice composition and would not be considered economically sustainable.