Este archivo ha sido creado el 18-12-2024 por Alfonso Moriana Elvira GENERAL INFORMATION ------------------ 1. Dataset title: Dataset of the article Influence of the rehydration periodo on yield quality and harvest performance in Manzanilla de Sevilla super high-density olive orchards 2. Authorship: Name:Morales-Sillero, Ana Institution:Universidad de Sevilla Email:amorales@us.es ORCID:0000-0002-8436-3620 Name:González-Fernández, Antonio Institution:Universidad Sevilla Email:agonzalez2@us.es ORCID:0000-0002-9855-1999 Name:Casanova, L Institution:Universidad de Sevilla Email:laucaler@us.es ORCID: 0000-0003-2729-4793 Name: Martín-Palomo, María José Institution: Universidad de Sevilla Email:mjpalomo@us.es ORCID:0000-0002-0314-4363 Name:Jiménez, MR Institution:Universidad de Sevilla Email:rjg@us.es ORCID:0000-0002-9020-2065 Name:Rallo, P Institution:Universidad de Sevilla Email:prallo@us.es ORCID:0000-0001-5673-9136 Name: Moriana, Alfonso Institution:Universidad de Sevilla Email:amoriana@us.es ORCID:0000-0002-5237-6937 DESCRIPTION ---------- 1. Dataset language: English 2. Abstract: This article present data of two different irrigation schedulings in a hedgerow table olive orchard. Data compare the trational management in the farm with an approach based on water potential measurements. The strategy based on water potential provided the optimization of water resources because irrigation was used in the period of rehydration, just before harvest. This strategy produced the improving ofyield quality in some of the sesaons studied. 3. Keywords: Deficit irrigation, olive trees, irrigation scheduling 4. Date of data collection (fecha única o rango de fechas): Seasonal data of 2018, 2019 and 2020 5. Publication Date: 20-05-2024 6. Grant information: Contrato con la empresa Aceitunas Guadalquivir FIUS19/0049.. 7. Geographical location/s of data collection: Morón de la Frontera (37.1° N, 5.5 W, 297 mas,Seville, Spain), ACCESS INFORMATION ------------------------ 1. Creative Commons License of the dataset: cc-BY 2. Dataset DOI: https://doi.org/10.12795/11441/166727 3. Related publication: Morales-Sillero, A, González-Fernández, A., Casanova, L., Martín-Palomo, MJ, Jiménez, MR, Rallo, P., Moriana A. 2024. Influence of the rehydration periodo on yield quality and harvest performance in Manzanilla de Sevilla super high-density olive orchards. Irrigation Science https://doi.org/10.1007/s00271-024-00934-6 METHODOLOGICAL INFORMATION ----------------------- 1. Description of the methods used to collect and generate the data: A three-year study was initiated in 2018, in a drip irrigated commercial olive orchard (cv Manzanilla de Sevilla) located in Morón de la Frontera (37.1° N, 5.5 W, 297 mas, Seville, Spain), with trees placed in a 4.5 × 1.5 m layout and a North–South orientation. The orchard was three years old at the beginning of the experiment. The climate of the area was Mediterranean, with warm winters and very dry summers. The annual precipitation was 722 mm in 2018, 345 mm in 2019, and 415 mm in 2020. The reference evapotranspiration (ETo) was 1202 mm, 1335 mm, and 1323 mm, respectively. The average annual temperature was around 18 °C and ranged between 37 °C in August and 4 °C in January or February, depending on the year. The soil is a red vertisol, very hard when dry, and extremely plastic when wet. The useful depth is of approximately 1 m, with a clayey texture in the first 0.4 m and clayey-silty below that. It is an alkaline soil (pH ≈7.6), not saline (electrical conductivity ≤ 0.110 dS/m), with high Cation Exchange Capacity (29.5 meq/100 g) and a carbonate content that ranges between 0.7 and 22.6% CaCO3). The hedges were always pruned in February. The height was capped to around 2.3 m using a disc pruner. The width of the row was limited to 1 m in 2018 and 1.4 m in 2019 and 2020, by eliminating the thickest or badly positioned branches. In 2019, a lateral pruning was done first with the disc pruner. The nutritional needs were met through fertigation supported by a foliar analysis carried out in July. All treatments received similar amount of nutrients and no significant differences were found in foliar analysis (data not shown). Regarding soil management, a natural plant cover was maintained between rows and mowed in spring. Weed control in the tree lines was done by spraying herbicides. The water was applied using a localized irrigation system with an integrated line of drippers and a flow rate of 2.3 L/h, placed 0.75 m apart. Water source was groundwater and it had an alkaline pH (7.6), a moderate electrical conductivity (1.07 dS/m), and high alkaline (234 ppm), calcium (151 ppm) and nitrate content (115 ppm). The experimental design consisted of completed randomized plots with two irrigation treatments and four repetitions per treatment. Each plot had a central row, where measurements were obtained, and it was flanked by two guard rows. Two irrigation treatments were applied: • Common Farm Management (CFM). This management was decided by the owner of the orchard. Irrigation scheduling consisted of almost constant rate of irrigation between phenological stages were found, and differences between years were related to the fruit load (in 2019, fruit load was very small) and rainfall distribution. • Regulated deficit irrigation (RDI). Irrigation scheduling was based on water status measurements and considered the phenological stage of the trees. The water stress level was characterized using midday shaded water potential (SWP) measurements. The irrigation season was divided in three different phases, according to Moriana et al. (2012): o Phase I. From shoot sprouting until the beginning of pit hardening (DOY 197 in 2018, DOY 170 in 2019, and DOY 174 in 2020). The most sensitive phenological stages occurred during this period (vegetative growth, flowering, and fruit set). Therefore, full irrigation conditions were provided and SWP was around -1.2 MPa (Moriana et al. 2012). o Phase II. From the beginning of pit hardening until the third week of August (DOY 246 in 2018, DOY 238 in 2019, DOY 230 in 2020). This is considered the less sensitive part of the season. The beginning of pit hardening was estimated according to Rapoport et al. (2013). In short, longitudinal fruit length was measured with an electronical caliper in ten fruits per repetition. Statistical analysis was performed with the average of these measurements per repetition. Then, pit hardening started when the increase in fruit length decreased. Because pit hardness was not measured, the end of this period was estimated with a fix date, which was commonly recommended for RDI (Girón et al. 2015a; Corell et al. 2020). The level of SWP considered was -3.0 MPa, which minimized the risk of fruit drop according to several authors (Girón et al. 2015a; Corell et al. 2020). o Phase III. From the third week of August until harvest. Partial recovery was performed during this period. The target value of SWP was -2.0 MPa, which would allow the fruit size to recover, according to several authors (Girón et al. 2015a; Corell et al. 2020; Martín-Palomo et al. 2020). The irrigation scheduling in the RDI treatment was adjusted to the target values of SWP in each period. Irrigation was increased from 1 mm day−1 to 4 mm day−1 according to the weekly measurements of SWP in each plot of RDI treatment. The increase was similar to the ones suggested by Moriana et al. (2012) and ranged based on the distance from the SWP measurement to the target value of SWP. Each repetition of this treatment was scheduling individually every week. Then, all repetitions were not irrigated at the same time, mainly during pit hardening period. 3. Software or instruments needed to interpret the data: Excel program 4. Information about instruments, calibration and standards: Midday stem water potential (SWP) measurements were taken using the pressure bomb technique (model 600, PMS, USA) in full expanded healthy leaves, which were grown in the interior of the canopy and received minimum radiation. Although this is not the approach for stem water potential measurement, the comparison between both (shaded and stem) was very similar (A Moriana unpublished data, Shaded = 1.06*Stem; n = 165; R2 = 0.83). These data were used for estimating the stress integral (SI) and to include the effect of the water stress duration. The SI was calculated according to a modified version of the Myers formula (Myers 1988). Myers (1988) suggested the estimation of SI using the maximum value obtained in the season. However, this value changed and could not be a reference for water stress. Consequently, the maximum value was estimated on each measured date as the one obtained using the baseline of Corell et al. (2016). In each experimental unit, ten trees were randomly selected in April 2018 (before the beginning of the study) to determine the canopy height, the perimeter of the trunk at 0.3 m,and the mean width from measurements at 0.8 and 1.7 m of height. From the height and width measurements, the average External Foliar Surface (EFS, m2ha1) was determined considering a rectangular prism shape in the hedge. All these measurements were also made in December of each experimental year. Besides, hedgerow porosity was estimated by image analysis of digital pictures that were taken with a Nikon D600 reflex camera (Nikon Corp., Tokyo, Japan) with a red sheet previously placed in the background of the hedgerow. A CobCal software ver. 2.0 (Bs As, Argentina) was used to process the images digitally and to estimate the average percentage of gaps by dividing the number of red pixels (i.e., background sheet) by the total number of red and green pixels (i.e., leaves and stems). Fruits were harvested mechanically on 25 October (DOY 298) in 2018, 17 September (DOY 260) in 2019, and 30 September (DOY 273) in 2020. At first, the harvest was planned to be carried out once the fruits had yellowish-green epidermis and the pulp was easily separated from the stone. However, in 2018 it was delayed due to the rainfall occurred (≈ 65 mm) two weeks before achieving this maturity index (Fig. 1). Previously, samples of three kilograms of olives per each experimental unit were taken for fruit trait measurement. Thus, the unitary and the average fruit weight (g) were obtained from a subsample of 100 fruits, and the size distribution (fruit count per kg) was established according to the US Standards for Green olive size designations (USDA 2019), that consider the following categories: Extra-large (< 200), Large (220–240), Medium and Small (241–300), Petite (301–400), Subpetite (401–420) and smaller than subpetite (> 420). The pulp-to-pit ratio was estimated using a 0.5 kg subsample based on the difference between the weights of fruit and pits. The average fruit volume (mL) was determined by immersion of 100 fruits in a 1 L graduated cylinder filled with 500 mL of water. Fruit shape is the ratio between the maximum longitudinal and equatorial diameters (mm), that were measured in 50 fruits with a digital caliper. The L*, a* and b* skin color parameters were measured on the equatorial zone of 30 fruits with a Minolta CM-700d (Konica Minolta Inc., Tokyo, Japan) spectrophotometer, and the color index was estimated as indicated in Castellano et al. (1993). The moisture and oil contents (%) were estimated using 10 g of crushed olives after oven-drying at 100 °C for 24 h until reaching a constant weight. The oil content was measured in the dry samples by nuclear magnetic resonance on a Maran Ultra spectrometer (Oxford Instruments, UK). Mechanical harvesting was done at dawn with a New Holland VX 7090 combine (CNH Global, Belgium) at a speed of 1.5 km h−1 and a 60% header opening in 2018 and 2019, and 2 km h−1 and 90%, respectively in 2020, all years with a frequency of 430 beats/min. Later, fruit yield (kg ha− 1) was estimated for each experimental unit from the total production removed by the harvester and the number of trees, the weight of the fruits left in 10 randomly selected trees (fruits were hand-picked from 0.6 m above the ground), and the weight of fallen fruits to the ground collected in a 4.5 × 2.5 m net placed on each side of the hedge. The removal efficiency was established as the percentage of fruits that were collected by the harvester. The number of fruits per external surface area (Number fruit m−2) was estimated from the number of fruits per kilogram, number of fruits per hectare and EFS data (m2 ha−1). Samples of three kilograms of olives per each experimental unit were also taken immediately after mechanical harvesting for texture and damage measurements. Fruit firmness, hardness, and texture were assessed using a TA.XT.plus texture analyzer (Stable Micro Systems Ltd) connected to the Texture Exponent software (version 6.1.15.0). Three types of tests were respectively conducted: (a) puncture (N/mm), with a probe of a 2 mm diameter steel punch that penetrated up to 4 mm into the fruit at a constant speed of 0.50 mm/s; (b) compression (N), with a 20 mm diameter TPA (Texture Profile Analysis) probe used at a speed of 1 mm/s, a deformation time of 2 s, and a deformability of 15%; and (c) shear compression force (N/g) by means of a Kramer cell (HDP/ KS10 Cell), with 10 blades of 3 mm thickness each at a return speed of 10 mm/s. For each experimental unit, the measurements were made on the equatorial zone of 10 pitted fruits in the puncture test, 10 intact fruits in the compression test, and in 10 batches of three pitted fruits of similar weight in the compression-shear test. Bruising damage was estimated from the percentage of fruits with cuts, bruising incidence, and the area and volume of the largest bruise. The percentage of fruit with cuts was measured 2 h after harvesting in a 100-fruit subsample for each experimental unit. In the same subsample, the bruising incidence was determined after classifying the fruits into three categories: non-bruised fruits, fruits with low damage (< 25% of the surface), and fruits with severe damage (≥ 25%), according to Morales-Sillero et al. (2014). For the external bruised area (BA, mm2) and bruising volume (BV, mm3),30 fruits were fixed two hours after harvest in formalin acetic acid [95% ethanol and distilled water (10:5:50:35 v/v/v/v)]. An impact located in the equatorial zone of each fruit was chosen and the length, width, and damage depth were measured, assuming an elliptical shape in the damaged zone as indicated by Morales-Sillero et al. (2014). 5. Environmental or experimental conditions: The climate of the area was Mediterranean, with warm winters and very dry summers (Fig. 1). The annual precipitation was 722 mm in 2018, 345 mm in 2019, and 415 mm in 2020. The reference evapotranspiration (ETo) was 1202 mm, 1335 mm, and 1323 mm, respectively. The average annual temperature was around 18 °C and ranged between 37 °C in August and 4 °C in January or February, depending on the year. The soil is a red vertisol, very hard when dry, and extremely plastic when wet. The useful depth is of approximately 1 m, with a clayey texture in the first 0.4 m and clayey-silty below that. It is an alkaline soil (pH ≈7.6), not saline (electrical conductivity ≤ 0.110 dS/m), with high Cation Exchange Capacity (29.5 meq/100 g) and a carbonate content that ranges between 0.7 and 22.6% CaCO3). FILE OVERVIEW ---------------------- 1. Explain the file naming conversion, si es aplicable: There is a unique file with all data. Each sheet is data of each table at the reference publication 2. File list: File name:Dataset Morales-Sillero 2024 Description: Excel file 4. File format: Excel