We describe the yield and quality of apples from a 0.8 ha apple orchard located in northern Greece over two growing seasons and consider the potential for site-specific management. The orchard has two apple cultivars: Red Chief (main cultivar) and Fuji (pollinator). Yield was measured by weighing all fruit harvested from groups of five adjacent trees and the position of the central tree was recorded by GPS. Apple quality at harvest was evaluated from samples of the two cultivars in both years for which fruit mass, flesh firmness, soluble solids content, juice pH and acidity of the juice were determined. The variation in tree flowering was also measured in the spring of the second season using a stereological sampling procedure. The results showed considerable variability in the number of tree flowers, yield and quality across the orchard for both cultivars. The number of flowers was strongly correlated with the final yield. These data could potentially be used to plan precise thinning and for early prediction of yield; the latter is important for marketing the fruit. Several quality characteristics, including fruit juice soluble solids content and acid content were negatively correlated with yield. The general patterns of spatial variation in several variables suggested that changes in topography and aspect had important effects on apple yield and quality.
To investigate if latent manganese (Mn) deficiency leads to increased transpiration, barley plants were grown for 10 weeks in hydroponics with daily additions of Mn in the low nM range. The Mn-starved plants did not exhibit visual leaf symptoms of Mn deficiency, but Chl a fluorescence measurements revealed that the quantum yield efficiency of PSII (F(v)/F(m)) was reduced from 0.83 in Mn-sufficient control plants to below 0.5 in Mn-starved plants. Leaf Mn concentrations declined from 30 to 7 microg Mn g(-1) dry weight in control and Mn-starved plants, respectively. Mn-starved plants had up to four-fold higher transpiration than control plants. Stomatal closure and opening upon light/dark transitions took place at the same rate in both Mn treatments, but the nocturnal leaf conductance for water vapour was still twice as high in Mn-starved plants compared with the control. The observed increase in transpiration was substantiated by (13)C-isotope discrimination analysis and gravimetric measurement of the water consumption, showing significantly lower water use efficiency in Mn-starved plants. The extractable wax content of leaves of Mn-starved plants was approximately 40% lower than that in control plants, and it is concluded that the increased leaf conductance and higher transpirational water loss are correlated with a reduction in the epicuticular wax layer under Mn deficiency.
Early forecasting of fruit orchard yield is important for market planning and for growers and exporters to plan labour, bins, storage and purchase of packing materials. Large variations in tree yield pose a challenge for accurate yield estimation. We evaluated a three-level systematic sampling procedure for unbiased estimation of fruit number for yield forecasts. In the Spring of 2009 we estimated the total number of fruit in several rows of each of 14 commercial fruit orchards growing apple (11 groves), kiwifruit (two groves), and table grapes (one grove) in central Chile. Survey times were 10-100 min for apples (depending on vigour), 85 min for the table grapes, and 85 and 150 min for the kiwifruit. During harvest in the Fall, the fruit were counted to obtain the true number. Yields ranged from lows of several thousand (grape bunches), to highs of more than 40 000 fruit (apples, kiwifruit). Absolute true errors (defined as the absolute difference between the estimate and the true value, divided by the true value) were less than 5% in six orchards, between 5 and 10% in a further five orchards and 13% in one orchard. In two apple orchards we obtained absolute true errors of about 20%. Error analysis based on systematic sub-sampling across each sampling stage was used to determine how to distribute sampling effort to achieve a total coefficient of error of 10%. We discuss the extension of the procedure for yield estimation at the full orchard scale for any target precision.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.