The Effect of Harvesting Time on Olive Fruits and Oils Quality Parameters of Tortiglione and Dritta Olive Cultivars

2021 ◽  
pp. 2000382
Author(s):  
Flamminii Federica ◽  
Marone Elettra ◽  
Neri Lilia ◽  
Pollastri Luciano ◽  
Cichelli Angelo ◽  
...  
Keyword(s):  
Quality Parameters ◽  
Harvesting Time ◽  
Olive Cultivars

Yield and Seed quality of barley (Hordeum vulgare L.) as affected by variety, nitrogen level and harvesting time

2014 ◽  
Vol 2 (2) ◽  
pp. 93-100
Author(s):  
Shahnaj Yesmina ◽  
Moushumi Akhtarb ◽  
Belal Hossain
Keyword(s):  
Grain Yield ◽  
Seed Weight ◽  
Seed Quality ◽  
Quality Parameters ◽  
Nitrogen Level ◽  
Yield Attributes ◽  
Harvesting Time ◽  
Nitrogen Levels ◽  
Vigour Index

The experiment was conducted to find out the effect of variety, nitrogen level and harvesting time on yield and seed quality of barley. The treatments used in the experiment consisted of two varieties viz. BARI Barley 4 and BARI Barley 5, three harvesting time viz. 35, 40 and 45 Days after Anthesis (DAA) and nitrogen levels viz. 0, 70, 85 and 100 kg N ha-1 . The experiment was laid out in a spilt- spilt-plot design with three replications assigning the variety to the main plot, harvesting time to the sub-plots and nitrogen level to the sub-sub plots. Variety had significant effects on the all yield attributes except fertile seeds spike-1 . Seed quality parameters viz. normal seeds spike-1 , deformed seeds spike-1 , germination (%) and vigour index were statistically significant. The variety BARI Barley 5 produced higher grain yield and seed quality than BARI Barley 4. Grain yield from BARI Barley 5 and BARI Barley 4 were 4.59 t ha-1 and 4.24 t ha-1 , respectively. Significantly, the highest 1000-seed weight (46.90 g) was produced by BARI Barley 5 than (37.90 g) BARI Barley 4. The result revealed that harvesting time had significant effect on yield and yield attributes and seed quality parameters. Seed yield was highest (4.65 t ha-1 ) when the crop harvested at 40 DAA and it was increased linearly from 35 DAA. Maximum quality seed and 1000-seed weight (43.20 g) was obtained when the crop harvested at 40 DAA. All the yields, yield attributes and seed quality parameters were significantly influenced by nitrogen levels. The highest grain yield (5.14 t ha-1 ) was obtained when BARI Barley 5 variety was fertilized by 100 kg N ha-1 and the lowest (3.14 t ha-1 ) was obtained from control treatments. Normal seeds spike-1 , vigour index, germination (%) were better at 85 kg N ha-1 in variety of BARI Barley 5 than BARI Barley 4. So it can be concluded that BARI Barley 5 showed better result when fertilized with 100 kg N ha-1 and harvested at 40 DAA for getting maximum yield and 85 kg N ha-1 and harvested at 40 DAA for getting better quality seed.

scholarly journals Determination of Optimum Harvesting Time for Periphyton Production on Artificial Substrates

2013 ◽  
Vol 23 (1-2) ◽  
pp. 51-62
Author(s):  
T Zaman ◽  
MMM Alam
Keyword(s):  
Water Quality ◽  
Mass Production ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Artificial Substrates ◽  
Secchi Disc ◽  
Harvesting Time ◽  
Physico Chemical ◽  
Chemical Water

The experiment was conducted in two cement made cisterns for a four-week period. Important physico-chemical water quality parameters and harvesting time in periphyton production were studied. During the study period, four groups of phytoplankton and two groups of zooplankton were observed. Among phytoplankton, Chlorophyceae was the most dominant having 62% Chlorella followed by Bacillariophyceae having 15% Navicula and 12% Cyclotella, Cyanophyceae having 5% Oscillatoria and 2% Anabaena and Euglenophyceae having 2% Euglena and 1% Phacus. The grand averages of periphyton mass production were 0.569 (± 0.242) mg DM/cm2 in C-1. There was highly significant (p<0.05) variation (F = 14.692) between C-1 and C-2 in respect of periphyton production. Cistern-1 was identified as more productive due to its favourable water quality parameters, i.e., water temperature of 24.6 to 28.3 ºC, Secchi disc reading of 18 to 33 cm, dissolved oxygen of 4.67 to 9.55 mg/L, pH of 9.12 to 10.18, NO3-N of 3.58 to 10.90 mg/L, NH3-N of 0.26 to 0.40 mg/L, PO4-P of 7.5 to 3.4 mg/L, conductivity 0.412 to 0.719 Ms. Third addition of substrate, that means 18- 19th day was identified as the optimum harvesting time of periphyton production.DOI: http://dx.doi.org/10.3329/pa.v23i1-2.16565Progress. Agric. 23(1 & 2): 51 – 62, 2012

scholarly journals Characterisation of Monovarietal Olive Oils Obtained from Croatian cvs. Drobnica and Buza during the Ripening Period

Foods ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 188 ◽  
Author(s):  
Jasminka Giacometti ◽  
Čedomila Milin ◽  
Fabio Giacometti ◽  
Zlatko Ciganj
Keyword(s):  
Antioxidant Activity ◽  
Phenolic Content ◽  
Total Phenolic ◽  
Optimal Harvesting ◽  
Crop Season ◽  
Northern Adriatic ◽  
Harvesting Time ◽  
Olive Oils ◽  
Ripening Stages ◽  
Olive Cultivars

The aim of this study was the monitoring of the chemical composition of olive oil at different ripening stages to determine the appropriate harvesting time during any given crop season in the northern Adriatic region. For this purpose, from September to November, two Croatian olive cultivars (Drobnica and Buza) were taken from two different olive orchards and for the respective olive oils, prepared on a laboratory scale, the major saponifiable, unsaponifiable and phenolic compounds were determined. Based on the chemical analyses performed, the optimal harvesting time has been set in October for both cultivars. Buza had a higher oleic acid, but lower total sterols, squalene and total alkanols. Compared to the local cultivars, the studied cultivars had a high total phenolic content and antioxidant activity. The antioxidant activity and concentrations of total phenols correlated with α-tocopherol in oil samples taken during the ripening progress. Finally, trace minerals detected in Buza and Drobnica oil differed, which can be an indicator of oxidative stability and authenticity of oils.

Effect of Harvest Time on Quality of Sugar Cane Cultivars

2013 ◽  
Vol 824 ◽  
pp. 293-300 ◽  
Author(s):  
T. Yirsaw ◽  
K. Woldetsadik ◽  
T.S. Workneh
Keyword(s):  
Block Design ◽  
Quality Parameters ◽  
Sugar Yield ◽  
Juice Quality ◽  
Harvest Time ◽  
Harvesting Time ◽  
Sugarcane Varieties ◽  
Randomized Complete Block Design ◽  
Stalk Diameter

Three commercial sugarcane varieties such as NCO-334, B52-298 and N14 were grown at Finchaa Cane Plantation, Ethiopia to determine the optimum harvest age for cane and sugar yields. Treatments consisted of factorial combination of varieties and five levels of harvest age were arranged in Randomized Complete Block Design with three replications. The varieties differed in stalk diameter and weight, and millable stalk number. Improvements in internodes number, stalk diameter and weight were increased with harvest age whereas internodes length and millable stalk number decreased with delay in harvesting. Varieties produced better juice quality in canes harvested at 17 months. NCO-334 attained its peak superior quality at the age of 15 months. This preliminary data on some indicator quality parameters imply that NCO-334 could be harvested at 15 months age in order to maximize sugar yield. However, more experiments are required to confirm the effect of harvesting time and variety on cane and sugar yield. Therefore, more research on detecting other quality parameters focusing on cane and sugar yield is recommended.

scholarly journals ASSESSMENT OF RGB AND HYPERSPECTRAL UAV REMOTE SENSING FOR GRASS QUANTITY AND QUALITY ESTIMATION

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 489-494 ◽  
Author(s):  
R. A. Oliveira ◽  
R. Näsi ◽  
O. Niemeläinen ◽  
L. Nyholm ◽  
K. Alhonoja ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Quality Parameters ◽  
Flying Height ◽  
Harvesting Time ◽  
Spectral Bands ◽  
Primary Growth ◽  
Dry Biomass ◽  
Reference Measurements ◽  
Orientation Parameters ◽  
D Value

<p><strong>Abstract.</strong> The information on the grass quantity and quality is needed for several times in a growing season for making optimal decisions about the harvesting time and the fertiliser rate, especially in northern countries, where grass swards quality declines and yield increases rapidly in the primary growth. We studied the potential of UAV-based photogrammetry and spectral imaging in grass quality and quantity estimation. To study this, a trial site with large variation in the quantity and quality parameters was established by using different nitrogen fertilizer application rates and harvesting dates. UAV-based remote sensing datasets were captured four times during the primary growth season in June 2017 and agricultural reference measurements including dry biomass and quality parameters, such as the digestibility (D-value) were collected simultaneously. The datasets were captured using a flying height of 50&amp;thinsp;m which provided a GSD of 0.7&amp;thinsp;cm for the photogrammetric imagery and 5&amp;thinsp;cm for the hyperspectral imagery. A rigorous photogrammetric workflow was carried out for all data sets aiming to determine the image exterior orientation parameters, camera interior orientation parameters, 3D point clouds and orthomosaics. The quantitative radiometric calibration included sensor corrections, atmospheric correction, and correction for the radiometric non-uniformities caused by illumination variations, BRDF correction and the absolute reflectance transformation. Random forest (RF) and multilinear regression (MLR) estimators were trained using spectral bands, vegetation indices and 3D features, extracted from the remote sensing datasets, and insitu reference measurements. From the FPI hyperspectral data, the 35 spectral bands and 11 spectral indices were used. The 3D features were extracted from the canopy height model (CHM) generated using RGB data. The most accurate results were obtained in the second measurement day (15th June) which was near to the optimal harvesting time and generally RF outperformed MLR slightly. When assessed with the leave-one-out-estimation, the best root mean squared error (RMSE%) were 8.9% for the dry biomass using 3D features. The best D-value estimation using RF algorithm (RMSE%&amp;thinsp;=&amp;thinsp;0.87%) was obtained using spectral features. Using the estimators, we then calculated grass quality and quantity maps covering the entire test site to compare different techniques and to evaluate the variability in the field. The results showed that the low-cost drone remote sensing gave excellent precision both for biomass and quality parameter estimation if accurately calibrated, offering an excellent tool for efficient and accurate management of silage grass production.</p>

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