Water is the most important factor affecting fruit production and quality. Under the threat of climate change, making irrigation effective and efficient is a pivotal issue. This study reports preliminary results on the use of the recently developed, plant-based IPL index for detecting leaf photo-assimilation and scheduling irrigation. This index considers leaf fluorescence variables, RuBisCo activity, leaf and air temperature, which are easy and quick to measure. This rapidity allows a high number of measurements, strengthening the representativeness of data. The trial was carried out on pear 'Abbé Fetel' grafted on quince 'Adam' rootstock and trained as slender spindle. 100 (T100), 50 (T50), 25 (T25) and 0% (T0) of the estimated evapotranspiration were supplied during the whole season. A "Dynamic" (DYN) treatment was added to the static ones, in which water was provided according to the IPL values. When IPL for DYN was lower than that for T100 irrigation was supplied, restoring IPL to values similar to those of T100. Results suggested that IPL was a reliable tool for managing irrigation. DYN reached the same productivity of T100 (45.1 t ha-1, 41 tonnes of which with a diameter >65 mm) but using 56% less water than T100; irrigation water productivity (WPI) was 61 g of fruit fresh matter per liter of water supplied (g L-1) versus 24 g L-1 of T100. Crop water productivity was 13.3 and 9.63 g L-1 in DYN and T100, respectively, when also rain water supply was considered. Although further tests on other species and sites should be performed, these first results suggest that the IPL index could be a promising tool for easy, effective plant stress detection and irrigation scheduling

A plant-based index for plant water status detection and irrigation scheduling in pear 'Abbé Fetel': first results on the use of the IPL index

Losciale P.;
2022-01-01

Abstract

Water is the most important factor affecting fruit production and quality. Under the threat of climate change, making irrigation effective and efficient is a pivotal issue. This study reports preliminary results on the use of the recently developed, plant-based IPL index for detecting leaf photo-assimilation and scheduling irrigation. This index considers leaf fluorescence variables, RuBisCo activity, leaf and air temperature, which are easy and quick to measure. This rapidity allows a high number of measurements, strengthening the representativeness of data. The trial was carried out on pear 'Abbé Fetel' grafted on quince 'Adam' rootstock and trained as slender spindle. 100 (T100), 50 (T50), 25 (T25) and 0% (T0) of the estimated evapotranspiration were supplied during the whole season. A "Dynamic" (DYN) treatment was added to the static ones, in which water was provided according to the IPL values. When IPL for DYN was lower than that for T100 irrigation was supplied, restoring IPL to values similar to those of T100. Results suggested that IPL was a reliable tool for managing irrigation. DYN reached the same productivity of T100 (45.1 t ha-1, 41 tonnes of which with a diameter >65 mm) but using 56% less water than T100; irrigation water productivity (WPI) was 61 g of fruit fresh matter per liter of water supplied (g L-1) versus 24 g L-1 of T100. Crop water productivity was 13.3 and 9.63 g L-1 in DYN and T100, respectively, when also rain water supply was considered. Although further tests on other species and sites should be performed, these first results suggest that the IPL index could be a promising tool for easy, effective plant stress detection and irrigation scheduling
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/401886
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact