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Publications

NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.

2022

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Abstract

Modern apple orchard systems should guarantee homogeneity of fruit internal and external qualities and fruit maturity parameters. However, when orchards reach productive age, a variation of these parameters takes place and mostly it is related to uneven light distribution within the tree canopy. The aim of the study was to evaluate the canopy position’s effect on fruit internal and external quality parameters. This is the first study where all the main fruit quality and maturation parameters were evaluated on the same trees and were related to the light conditions and photosynthetic parameters. Four fruit positions were tested: top of the apple tree, lower inside part of the canopy, and east and west sides of the apple tree. Fruit quality variability was significant for fruit size, blush, colour indices, total sugar content, dry matter concentration, accumulation of secondary metabolites and radical scavenging activity. Fruit position in the canopy did not affect flesh firmness and fruit maturity parameters such as the starch index, Streif index and respiration rate. At the Lithuanian geographical location (55°60′ N), significantly, the highest fruit quality was achieved at the top of the apple tree. The tendency was established that apple fruits from the west side of the canopy have better fruit quality than from the east side and it could be related to better light conditions at the west side of the tree. Inside the canopy, fruits were distinguished only by the higher accumulation of triterpenic compounds and higher content of malic acid. Light is a main factor of fruit quality variation, thus all orchard management practices, including narrow two-dimensional tree canopies and reflecting ground covers which improve light penetration through the tree canopy, should be applied.

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Abstract

Satellite Rainfall Products (SRPs) are now in widespread use around the world as a better alternative for scarce observed rain gauge data. Upon proper analysis of the SRPs and observed rainfall data, SRP data can be used in many hydrological applications. This evaluation is very much necessary since, it had been found that their performances vary with different areas of interest. This research looks at the three prominent river basins; Malwathu, Deduru, and Kalu of Sri Lanka and evaluates six selected SRPs, namely, IMERG, TRMM 3B42, TRMM 3B42-RT, PERSIANN, PERSIANN-CCS, PERSIANN-CDR against 15+ years of observed rainfall data with the use of several indices. Four Continuous Evaluation Indices (CEI) such as Root Mean Square Error (RMSE), Percentage Bias (PBIAS), Pearson’s Correlation Coefficient (r), and Nash Sutcliffe Efficiency (NSE) were used to evaluate the accuracy of SRPs and four Categorical Indices (CI) namely, Probability of Detection (POD), Critical Success Index (CSI), False Alarm Ratio (FAR) and Proportion Correct (PC) was used to evaluate the detection and prediction accuracy of the SRPs. Then, the Mann–Kendall Test (MK test) was used to identify trends in the datasets and Theil’s and Sens Slope Estimator to quantify the trends observed. The study of categorical indicators yielded varying findings, with TRMM-3B42 performing well in the dry zone and IMERG doing well in the wet zone and intermediate zone of Sri Lanka. Regarding the CIs in the three basins, overall, IMERG was the most reliable. In general, all three basins had similar POD and PC findings. The SRPs, however, underperformed in the dry zone in terms of CSI and FAR. Similar findings were found in the CEI analysis, as IMERG gave top performance across the board for all four CEIs in the three basins. The three basins’ overall weakest performer was PERSIANN-CCS. The trend analysis revealed that there were very few significant trends in the observed data. Even when significant trends were apparent, the SRP projections seldom captured them. TRMM-3B42 RT had the best trend prediction performance. However, Sen’s slope analysis revealed that while the sense of the trend was properly anticipated, the amplitude of the prediction significantly differed from that of the observed data.