Assessment of “Sugranineteen” Table Grape Maturation Using Destructive and Auto-Fluorescence Methods

The optimal harvesting of table grapes is commonly determined based on technological and phenolic indices analyzed over the course of its maturity. The classical techniques used for these analyses are destructive, time-consuming, and work for a limited number of samples that may not represent the heterogeneity of the vineyard. This study aimed to follow the ripening season of table grapes using non-destructive tools as a rapid and accurate alternative for destructive techniques. Grape samples were collected from a Sugranineteen vineyard during the ripening season to measure the basic maturity indices via wet chemistry, and total polyphenols, anthocyanins, and flavonoids were evaluated by spectrophotometry. Fluorescent readings were collected from intact clusters with a portable optical sensor (Multiplex® 3, Force-A, France) that generates indices correlated to different maturity parameters. Results revealed strong relationships between the Multiplex® indices ANTH_RG and FERARI and the skin anthocyanin content, with R2 values equal to 0.9613 and 0.8713, respectively. The NBI_R index was also related to total anthocyanins (R2 = 0.8032), while the SFR_R index was linked to the titratable acidity (R2 = 0.6186), the sugar content (R2 = 0.7954), and to the color index of red grapes (CIRG) (R2 = 0.7835). Results demonstrated that Multiplex® 3 can be applied on intact clusters as an effective non-destructive tool for a rapid estimation of table grapes’ anthocyanin content

Non-destructive evaluation of external and internal table grape quality

Thesis (PhDAgric)--Stellenbosch University, 2021.ENGLISH ABSTRACT: Determining the correct harvest maturity parameters of table grapes is an essential step before harvesting. The chemical analysis of table grapes to determine harvest and quality parameters such as total soluble solids (TSS), titratable acidity (TA) and pH, is very time-consuming, expensive, and destructive. Developing faster and more cost-effective methods to obtain the information can benefit the table grape industry by reducing losses suffered at the postharvest stage. There are multitudes of factors that can influence table grape postharvest quality leading to huge losses. These losses are exacerbated even further by the long list of postharvest external and internal defects that can occur, including browning in all its various manifestations. The application of cutting-edge technologies such as Fourier Transform Near-Infrared (FT-NIR) spectroscopy that can accurately assess the external and internal quality of fruit is, therefore, essential. This particularly concerns the identification of defects or assessment of the risks of defects that are likely to develop during post storage. The aim of this application would thus be to evaluate these new technologies to monitor table grape quality non-destructively, before, during, and/or after harvest. This study, therefore, focussed on the development and optimisation of faster, cost- effective, and fit-for-purpose methods to monitor harvest maturity and quality of table grapes in the vineyard before harvesting and during packaging and cold storage. Harvest of three different cultivars, namely, Thompson Seedless, Regal Seedless and Prime, happened over two seasons (2016 and 2017) from six different commercial vineyards. Five of these vineyards were in the Western Cape (two in the Hex River Valley, three in Wellington) and one in the Northern Cape (Kakamas), South Africa. Harvest occurred twice at each vineyard, at optimum ripeness and two weeks later (after the optimum harvest date). The incidence and intensity of browning on each berry on a bunch were evaluated for different defects and browning phenotypes. Quantitative harvest maturity and indicative quality parameters such as TSS, TA and pH, as well as the sensory-related parameters – sugar:acid ratio (TSS:TA ratio) and BrimA, were investigated by scanning whole table grape bunches contactless with Bruker’s MATRIX-F spectrometer in the laboratory. Partial Least Squares (PLS) regression was used to build prediction models for each parameter. Two different infrared spectrometers, namely the Bruker Multipurpose Analyser Fourier Transform Near-Infrared (MPA FT-NIR) and MicroNIR Pro 1700 were also used to determine TSS on whole table grape berries. The MicroNIR Pro 1700 was utilised in the vineyard and the laboratory and the MPA only in the laboratory. The same spectral dataset used to build the quantitative models was used to build classification models for two browning phenotypes, namely chocolate browning and friction browning. Partial Least Squares Discriminant Analysis (PLS-DA) and Artificial Neural Networks (ANN) were used for the classification tasks. Key results showed that the incidence and intensity of different defects and browning phenotypes such as sulphur dioxide (SO2) damage were prevalent on all three white seedless table grape cultivars. The incidences of fungal infection, sunburn and abrasion damage were high on Regal Seedless and Thompson Seedless in 2016. Contact browning, mottled browning and friction browning and bruising damage had higher incidences in 2017 than in 2016. Overall, the intensity of defects was very high in 2016 except on Regal Seedless from Hex River Valley. Prime from Kakamas and Wellington had the highest intensity of defects in 2017, which appeared on the grapes after 7 weeks of cold storage. Prediction models were successfully developed for TSS, TA, TSS:TA, pH, and BrimA minus acids on intact table grape bunches using FT-NIR spectroscopy in a contactless measurement mode, and applying spectral pre-processing techniques for regression analysis with PLS. The combination of Savitzky-Golay first derivative coupled with multiplicative scatter correction on the original spectra delivered the best models. Statistical indicators used to evaluate the models were the number of latent variables (LV) used to build the model, the prediction correlation coefficient (R2p) and root mean square error of prediction (RMSE). For the respective parameters TSS, TA, TSS:TA ratio, pH, and BrimA, the number of LV used when the models were build according to a random split of the calibration and validation set were 6, 4, 5, 5 and 10, the R2p = 0.81, 0.43, 0.66, 0.27, and 0.71, and the RMSEP = 1.30 °Brix, 1.09 g/L, 7.08, 0.14, and 1.80. When 2016 was used as the calibration set and 2017 as the validation set in model building the number of LV used were 9, 5, 5, 4 and the R2p = 0.44, 0.06, 0.17, 0.05, and 0.05 and the RMSEP = 3.22 °Brix, 2.41 g/L, 14.53, 0.21, and 8.03 for for the respective parameters. Determining TSS of whole table grape berries in the vineyard before and after harvesting using handheld and benchtop spectrometers on intact table grape berries showed that spectra taken in the laboratory with the MicroNIR were more homogenous than those taken in the vineyard with the same spectrometer, over the two years investigated. The results obtained with the MPA were not as good as those obtained with the MicroNIR in the laboratory were. The model constructed with the combined data of 2016 and 2017 taken in the laboratory with the MicroNIR had the best statistics in terms of R2p (0.74) and RPDp (1.97). The model constructed with the 2017 data obtained in the laboratory with the MicroNIR had the lowest prediction error (RMSEP = 1.13°Brix). Good models were obtained using PLS-DA and ANN to classify bunches as either clear or as having chocolate browning and friction browning based on the spectra obtained from intact table grape bunches with the MATRIX-F spectrometer. The classification error rate (CER), specificity and sensitivity were used to evaluate the models constructed using PLS-DA and the kappa score was used for ANN. The CER for chocolate browning (25%) was better than that of friction browning (46%) after Weeks 3 and 4 in cold storage for both class 0 (absence of browning) and class 1 (presence of browning). Both the specificity and sensitivity of class 0 and class 1 of friction browning were not as good as for chocolate browning. With ANN, the testing kappa score to classify table grape bunches as clear or having chocolate browning or friction browning showed that chocolate browning could be classified with the strong agreement after Weeks 3 and 4 and Weeks 5 and 6 and that friction browning could be classified with moderate agreement after three and four weeks in cold storage. Classification of chocolate browning and friction browning phenotypes was done using PLS-DA and ANN and the result showed that both types of browning can be classified with moderate agreement. The implications of the results of this study for the table grape industry are that the industry can move beyond just assessing methods and techniques in the laboratory towards implementation in the vineyard and the packhouse. Much quicker decisions regarding grape quality and destination of export can now be made using a combination of the MicroNIR handheld and MATRIX-F instruments for onsite quality measurement and the models to predict internal (e.g. TSS) and external (browning) quality attributes.AFRIKAANSE OPSOMMING: Die bepaling van die korrekte oesrypheidsparameters van tafeldruiwe is 'n noodsaaklike stap voor oes. Chemiese ontleding van tafeldruiwe om oes- en kwaliteitsparameters te bepaal, soos totale oplosbare vaste stowwe (TOVS), titreerbare suur (TS) en pH, is baie tydrowend, duur en vernietigend. Die ontwikkeling van vinniger en kostedoeltreffender maniere om die inligting te bekom, kan die tafeldruifbedryf bevoordeel deur verliese wat in die na-oesstadium gely word, te verminder. Dit sluit die menigte faktore in wat die gehalte van tafeldruiwe ná oes kan beïnvloed en tot verliese lui. Hierdie verliese word nog verder vererger deur die lang lys van verskillende na-oes-verwante gebreke wat kan voorkom, insluitend verbruining in al sy verskillende manifestasies. Die toepassing van toonaangewende tegnologieë soos Fourier-transform-naby- infrarooi (FT-NIR) spektroskopie wat die eksterne en interne kwaliteit van vrugte akkuraat kan beoordeel, is dus noodsaaklik. Dit is veral die identifisering van gebreke, of die beoordeling van die risiko's van gebreke, wat waarskynlik tydens die opberging kan ontstaan. Die doel van hierdie toepassing was dus om hierdie nuwe tegnologieë te evalueer om die kwaliteit van tafeldruiwe nie-vernietigend te monitor, voor, tydens en/of ná oes. Hierdie studie het dus gefokus op die ontwikkeling en optimalisering van vinniger, koste- effektiewe en geskikte doeleindes om oesrypheid en kwaliteit van tafeldruiwe in die wingerd te monitor voor oes en tydens verpakking en koelopberging. Druiwe-oes van drie verskillende kultivars (Thompson Seedless, Regal Seedless en Prime) het gedurende twee jare (2016 en 2017) uit ses verskillende kommersiële wingerde plaasgevind. Vyf van hierdie wingerde was in die Wes-Kaap (twee in die Hexriviervallei, drie in Wellington) en een in die Noord-Kaap (Kakamas), Suid-Afrika. Die oes het twee keer by elke wingerd plaasgevind, dit wil sê op die beste rypheid en twee weke later ná die optimale oesdatum. Die voorkoms en intensiteit van verbruining op elke korrel op 'n tros is op verskillende defekte en verbruiningsfenotipes geëvalueer. Kwantitatiewe oesrypheid en kwaliteitsindikatiewe parameters, naamlik TOVS, TS en pH, sowel as sensoriese verwante parameters suiker:suur-verhouding (TOVS:TS- verhouding) en BrimA is ondersoek deur heel tafeldruiftrosse sonder kontak met die Bruker se MATRIX-F-spektrometer in die laboratorium te skandeer. Gedeeltelike minste kwadrate (GMK) regressie is gebruik om modelle vir die parameters te bou. Twee verskillende infrarooi- spektrometers naamlik (a) die Bruker Multipurpose Analyzer Fourier Transform Near-Infrared (MPA FT-NIR) en (b) MicroNIR Pro 1700 is ook gebruik om TOVS op heel tafeldruifkorrels te bepaal. Die MicroNIR Pro 1700 is in die wingerd en in die laboratorium gebruik en die MPA slegs in die laboratorium. Met behulp van dieselfde spektrale datastel as die een wat gebruik word om die kwantitatiewe modelle op te stel, is klassifikasiemodelle vir twee verskillende verbruiningsfenotipes (sjokoladeverbruining en wrywingverbruining) gebou. Hierdie keer is gedeeltelike minste-kwadrate-diskriminant-analise (GMK-DA) en kunsmatige neurale netwerke (KNN) gebruik. Die belangrike resultate het getoon dat die voorkoms en intensiteit van verskillende defekte en verbruiningsfenotipes soos swaeldioksied (SO2)-skade op al drie wit pitlose tafeldruifkultivars voorgekom het. Die voorkoms van swaminfeksie, sonbrand en skaafskuur was hoog op Regal Seedless en Thompson Seedless in 2016. Kontak-, gevlekte- en wrywing verbruining sowel as kneusplekke het in 2017 'n hoër voorkoms as in 2016 gehad. Oor die algemeen was die intensiteit van defekte baie hoog in 2016 behalwe op Regal Seedless vanaf die Hexriviervallei. Prime van Kakamas en Wellington het in 2017 die hoogste intensiteit van gebreke gehad wat ná 7 weke se koelopberging op die druiwe verskyn het. Die suksesvolle ontwikkeling van modelle vir TOVS, TS, TOVS:TS verhouding, pH en BrimA op heel tafeldruiftrosse met behulp van FT-NIR-spektroskopie is bewys as inderdaad moontlik – veral as GMK met verskillende spektrale voorverwerkingstegnieke gepaard gaan. Statistiese aanwysers wat gebruik is om die modelle te evalueer, was die aantal latente veranderlikes (LV) wat gebruik is om die model te bou, die voorspellingskorrelasiekoëffisiënt (R2p) en wortelgemiddelde vierkante voorspellingsfout (WGVVF). Die kombinasie van die eerste afgeleide Savitzky-Golay tesame met die vermenigvuldigende verstrooiingskorreksie op die oorspronklike spektra het die beste modelle gelewer. Statistiese aanwysers wat gebruik is om die modelle te evalueer, was die aantal latente veranderlikes (LV) wat gebruik is om die model te bou, die voorspellingskorrelasiekoëffisiënt (R2p) en wortelgemiddelde vierkante voorspellingsfout (RMSE). Vir die onderskeie parameters TSS, TA, TSS: TA-verhouding, pH en BrimA, was die aantal LV wat gebruik is toe die modelle volgens 'n ewekansige verdeling van die kalibrasie- en valideringstel gebou is, 6, 4, 5, 5 en 10, die R2p = 0,81, 0,43, 0,66, 0,27 en 0,71, en die RMSEP = 1,30 ° Brix, 1,09 g / l, 7,08, 0,14 en 1,80. Toe 2016 as die kalibrasiestel gebruik is en 2017 as die validasieset in modelbou, was die aantal gebruikte LV 9, 5, 5, 4 en die R2p = 0,44, 0,06, 0,17, 0,05 en 0,05 en die RMSEP = 3,22 ° Brix, 2,41 g / l, 14,53, 0,21 en 8,03 vir die onderskeie parameters. Die bepaling van TOVS van heel tafeldruifkorrels in die wingerd voor en ná oes oor twee jaar met behulp van hand- en tafelbladspektrometers het getoon dat spektra wat in die laboratorium met die MicroNIR geneem is meer homogeen was as dié wat in die wingerd met dieselfde spektrometer geneem is. Die resultate wat met die MPA behaal is, was nie so goed soos met die MicroNIR in die laboratorium nie. Die model wat saamgestel is met die gekombineerde data van 2016 en 2017 wat in die laboratorium met die MicroNIR geneem is, het die beste statistieke gehad in terme van die R2p (0.74) en die RPDp (1.97). Die model wat opgestel is met die 2017 data wat in die laboratorium met die MicroNIR verkry is, het die laagste voorspellingsfout (RMSEP = 1.13°Brix) gehad. Goeie modelle is verkry met behulp van GMK-DA en KNN om trosse as skoon te klassifiseer, of as sjokoladeverbruining en wrywingsverbruining gebaseer op die spektra van die heel tafeldruiftrosse wat met die MATRIX-F-spektrometer geneem is. Die klassifikasiesyfer (KS), spesifisiteit en sensitiwiteit is gebruik om die modelle wat met behulp van GMK-DA saamgestel is, te evalueer en die kappa-telling is vir KNN gebruik. Die KS vir sjokoladeverbruining (25%) was beter as dié van wrywingsverbruining (46%) vir week 3 en week 4 vir beide klas 0 (afwesigheid van verbruining) en klas 1 (teenwoordigheid van verbruining). Beide die spesifisiteit en sensitiwiteit van klas 0 en klas 1 vir wrywingverbruining was nie so goed soos vir sjokoladeverbruining nie. Met KNN het die toetskappa-telling om tafeldruiftrosse as skoon of sjokoladeverbruining of wrywingsverbruining te klassifiseer, getoon dat sjokoladeverbruining tydens Week 3 en Week 4 en Week 5 en Week 6 met 'n matige ooreenstemming geklassifiseer kan word en dat wrywingsverbruining met matige ooreenstemming tydens Week 3 en Week 4 geklassifiseer kan word. Die implikasies van hierdie resultate vir die tafeldruifbedryf is van so 'n aard dat die bedryf nou verder kan gaan as om net metodes en tegnieke in die laboratorium te beoordeel, maar kan beweeg na implementering in die wingerd en die pakhuis. Die neem van baie vinniger besluite rakende die kwaliteit van die druiwe, dit wil sê in watter klas druiwe geplaas kan word en na watter uitvoermark druiwe gestuur kan word, is nou moontlik. Veel vinniger besluite rakende druiwekwaliteit en bestemming van uitvoer kan nou geneem word met behulp van 'n kombinasie van die MicroNIR-hand- en MATRIX-F-instrumente vir kwaliteitsmeting in situ en die modelle om interne (bv. TOVS) en eksterne (verbruining) kwaliteitseienskappe te voorspel.Doctora

Grapes and Wine

Grape and Wine is a collective book composed of 18 chapters that address different issues related to the technological and biotechnological management of vineyards and winemaking. It focuses on recent advances, hot topics and recurrent problems in the wine industry and aims to be helpful for the wine sector. Topics covered include pest control, pesticide management, the use of innovative technologies and biotechnologies such as non-thermal processes, gene editing and use of non-Saccharomyces, the management of instabilities such as protein haze and off-flavors such as light struck or TCAs, the use of big data technologies, and many other key concepts that make this book a powerful reference in grape and wine production. The chapters have been written by experts from universities and research centers of 9 countries, thus representing knowledge, research and know-how of many regions worldwide

Application of image processing methodologies for fruit detection and analysis

En aquesta memòria es presenten diversos treballs d'investigació centrats en l’automatització d’operacions agrícoles mitjançant l’aplicació de diverses tècniques de processament d’imatge. En primer lloc es presenta un mètode desenvolupat per detectar i comptar raïms mitjançant la localització de pics d'intensitat en superfícies esfèriques. En segon lloc es desenvolupa un sistema de recol•lecció automàtica de fruita mitjançant la combinació d'una càmera estereoscòpica de baix cost i un braç robòtic. En tercer lloc es proposa una aplicació en què es desenvolupa un mètode basat en l'ús de la informació de color per a la verificació d'una varietat de nectarines de forma automàtica i individual en una línia d’embalatge de fruita. Finalment s’han estudiat les correlacions entre els paràmetres de qualitat de la fruita i el espectre visible de la seva pell amb l’objectiu de controlar la seva qualitat de forma no destructiva durant el seu emmagatzematge.En esta memoria se presentan diversos trabajos de investigación centrados en la automatización de operaciones agrícolas mediante la aplicación de distintas técnicas de procesado de imágenes. En primer lugar se presenta un método desarrollado para detectar y contar uvas rojas mediante la identificación de picos de intensidad en las superficies esféricas. En segundo lugar se desarrolla un sistema de recolección automática de fruta mediante la combinación de una cámara estereoscópica de bajo coste y un brazo robótico. En tercer lugar se propone una aplicación en la que se desarrolla un método de procesamiento de imágenes basado en el uso de la información de color para la verificación de una variedad de nectarinas de forma automática e individual en una línea de envasado de fruta. Finalmente se han estudiado las correlaciones entre los parámetros de calidad de la fruta y el espectro visible de su piel con el fin de controlar su calidad de forma no destructiva durante el almacenamiento.This memory introduces several research works developed to automate agricultural tasks by applying image processing techniques. In the first place a new image processing method is proposed for detecting and counting red grapes by identifying specular reflection peaks from spherical surfaces. The proposal of the second application is to develop an automatic fruit harvesting system by combining a low cost stereovision camera and a robotic arm. The third application proposed is to develop a novel image processing method based on the use of color information to verify an in-line automatic and individual nectarine variety verification in a fruitpacking line. Finally, a study focused on assessing correlations between post-storage fruit quality indices and the visible spectra of the skin of the fruit is proposed in order to control fruit quality in a non-destructive way during the storage

Efectos combinados de la clorosis férrica y el estado hídrico del viñedo en la calidad de la uva y el vino cv. Tempranillo

Water deficit and iron nutritional deficiency (iron chlorosis) are environmental stress factors that frequently affect grapevine cultivation in the Mediterranean area. Studies on the impact of both factors, when acting simultaneously, are scarce. In this Thesis, the combined effects of the incidence of iron chlorosis and the water status of the vine on the quality and aromatic profile of the Tempranillo grape and wine have been evaluated, and the feasibility of measuring the foliar chlorophyll content in veraison (Chl) has been studied as an early indicator of the quality potential of the grapes under these conditions. In addition, this Thesis has investigated, for the first time, how moderate levels of iron deficiency in grapevines can affect the presence of volatile organic compounds in wines. During several campaigns a group of 20 subareas of non-irrigated vineyards (10 m × 10 m each), from not affected to moderately affected by iron chlorosis, was monitored in the Ribera del Duero Designation of Origin. The water status and nutritional stress levels of the vineyard, estimated from the leaf water potential before sunrise and the foliar chlorophyll content measured at veraison, were related to the values of vigor, yield and grape composition parameters, as well as with the chemical and organoleptic characteristics of the wine. Mild to moderate incidence of iron chlorosis had no significant effects on vine vigor, yield, or berry size, but increased concentrations of some specific terpenes, C13 norisoprenoids, volatile acids, and phenols in grapes. On the other hand, the water deficit tended to increase the color intensity and the extractable anthocyanin content of the grapes. It has been observed that iron deficiency stress lowers the pH of the wine and contributes to the improvement of sensory attributes as tonality, layer intensity, flavour intensity and persistence in the mouth. Increases in red color, astringency and wine persistence associated with the incidence of iron chlorosis were observed, although restricted in conditions of high water deficit. The results show that moderate stress due to iron deficiency increased the concentrations of volatile compounds associated with floral notes, such as 2-phenylacetaldehyde, 2-phenylethanol and 2-phenylethyl acetate, in wines, while reducing the presence of C6 alcohols, responsible for the herbaceous aroma. The highest total content of phenolic compounds was observed in the vineyard subzones with the best water status. In the most stressed subzones, both due to water deficit and iron deficiency, lower contents of C6 alcohols are observed than in the less stressed subzones. The results indicate that mild to moderate iron deficiency stress can have positive effects on chemical composition and sensory attributes of Tempranillo wine. Measurements of leaf chlorophyll content at veraison could be very useful to map quality potential in rainfed vineyards affected by iron deficiency.El déficit hídrico y la deficiencia nutricional de hierro (clorosis férrica) son factores de estrés ambiental que afectan frecuentemente al cultivo de la vid en la zona mediterránea. Los estudios sobre el impacto de ambos factores, cuando actúan simultáneamente, son escasos. En esta Tesis se han evaluado los efectos combinados de la incidencia de clorosis férrica y del estado hídrico de la vid sobre la calidad y el perfil aromático de la uva y del vino Tempranillo y se ha estudiado la viabilidad de la medida del contenido foliar de clorofila en el envero (Chl) como indicador precoz del potencial de calidad de las uvas en esas condiciones. Además, en esta Tesis se ha investigado, por primera vez, cómo niveles moderados de carencia de hierro en la vid pueden afectar a la presencia de compuestos orgánicos volátiles en los vinos. Para ello, se realizó un seguimiento durante varias campañas de 20 subzonas de viñedo de secano (10 m × 10 m cada una), desde no afectadas hasta moderadamente afectadas por clorosis férrica, en la Denominación de Origen Protegida Ribera del Duero. Los niveles de estrés hídrico y nutricional del viñedo, estimados a partir del potencial hídrico foliar antes del amanecer y el contenido de clorofila foliar medidos en el envero, se relacionaron con los valores de vigor, rendimiento y composición de la uva, así como con las características químicas y organolépticas del vino. La incidencia leve a moderada de clorosis férrica no tuvo efectos significativos sobre el vigor de la vid, el rendimiento o el tamaño de las uvas, pero aumentó las concentraciones de algunos terpenos específicos, norisoprenoides C13, ácidos y fenoles volátiles en la uva. Por su parte, el déficit hídrico tendió a incrementar la intensidad del color y el contenido de antocianinas extraíbles de las uvas. Se ha observado que el estrés por deficiencia de hierro disminuye el pH del vino y contribuye a la mejora de atributos sensoriales de tonalidad e intensidad de la capa, intensidad del sabor y persistencia en boca. Se observaron aumentos en el color rojo, en la astringencia y en la persistencia del vino asociados con la incidencia de clorosis férrica, aunque restringidos en condiciones de déficit hídrico elevado. Los resultados muestran que el estrés moderado por deficiencia de hierro aumentó en los vinos las concentraciones de compuestos volátiles asociados a notas florales, como el 2-fenilacetaldehído, el 2-feniletanol y el acetato de 2-feniletilo, al tiempo que redujo la presencia de los alcoholes C6, responsables del aroma herbáceo. El mayor contenido total de compuestos fenólicos se observó en las subzonas de viñedo con mejor estado hídrico. En las subzonas más estresadas, tanto por déficit hídrico como por carencia de hierro, se observan menores contenidos de alcoholes C6 que en las subzonas menos estresadas. Los resultados indican que el estrés por deficiencia de hierro de leve a moderado puede tener efectos positivos sobre los compuestos químicos y los atributos sensoriales del vino Tempranillo. Las mediciones del contenido de clorofila foliar en el envero podrían ser muy útiles para mapear el potencial de calidad en viñedos de secano afectados por deficiencia de hierro.Escuela de DoctoradoDoctorado en Enología, Viticultura y Sostenibilida

Continuous Plant-Based and Remote Sensing for Determination of Fruit Tree Water Status

Climate change poses significant challenges to agricultural productivity, making the efficient management of water resources essential for sustainable crop production. The assessment of plant water status is crucial for understanding plant physiological responses to water stress and optimizing water management practices in agriculture. Proximal and remote sensing techniques have emerged as powerful tools for the non-destructive, efficient, and spatially extensive monitoring of plant water status. This review aims to examine the recent advancements in proximal and remote sensing methodologies utilized for assessing the water status, consumption, and irrigation needs of fruit tree crops. Several proximal sensing tools have proved useful in the continuous estimation of tree water status but have strong limitations in terms of spatial variability. On the contrary, remote sensing technologies, although less precise in terms of water status estimates, can easily cover from medium to large areas with drone or satellite images. The integration of proximal and remote sensing would definitely improve plant water status assessment, resulting in higher accuracy by integrating temporal and spatial scales. This paper consists of three parts: the first part covers current plant-based proximal sensing tools, the second part covers remote sensing techniques, and the third part includes an update on the on the combined use of the two methodologies

Development of an effective and sustainable system to monitor fruit tree water status with precision devices

In recent years, sustainable water resource management has become a significant and debated issue in the agro-environmental context. Agriculture, as one of the major water-consuming sectors, plays a crucial role in water resource management. Indeed, global climate change is leading to a general temperature rising, with a consequent increase in drought phenomena. As a result, this leads to an overuse of water resources for irrigation. Therefore, understanding tree crop responses to water availability is becoming increasingly urgent, aiming to increase their water use efficiency.In this regard, one of the primary objectives of scientific research today is to optimize the use of water resources, minimizing inputs without compromising outputs. Water resource savings alone will lead to increased profits. In recent years, deficit irrigation methods, such as regulated deficit irrigation (RDI) and partial rootzone drying (PRD), have allowed farmers to save water while increasing profit by irrigating only during specific phenological stages or with reduced volumes on alternated sides of the rootzone, inducing the plant to activate physiological mechanisms (partial stomatal closure) useful for maximizing water use efficiency. However, real-time knowledge of fruit tree water requirements with consequent automation of precise irrigation applications would allow farmers to further increase water use efficiency. In this regard, last-generation sensors allow continuous data acquisition directly from the plant, greatly increasing the level of information. The combined use of plant-based proximal sensors can provide highly precise information about its water status. Furthermore, remote sensing technologies allow strategic use of proximal sensors, taking into account the spatial variability of the orchard.Based on these premises, the main objective of this dissertation was to develop an effective and sustainable system for monitoring the water status of fruit trees using proximal and remote sensing technologies. Firstly, the use of plant-based proximal and remote sensing technologies, as well as the combination of the two techniques, was reviewed. Subsequently, some techniques for assessing the water status of young olive trees placed in a growth chamber were tested. In the subsequent trial, fruit growth sensors (fruit gauges) were used to study responses of fruit growth from five different species (peach, mango, olive, orange, and loquat) to vapor pressure deficit. In the last trial, the combined use of proximal and remote sensing technologies was tested for estimating the water status of 'Calatina' olive trees under open field conditions