Yields and the composition of roots of sugar beet varieties tolerant to the beet cyst nematode

Jaskulska, Iwona; Kamieniarz, Jarosław; Jaskulski, Dariusz

doi:10.5601/jelem.2016.21.4.1280

Cited by 2 publications

(2 citation statements)

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“…In contrast, the smallest number (30) was obtained for surfaces subjected to plow treatment; generally, this form of tillage is losing popularity for economic and environmental reasons: not only is it energy‐ and labor‐intensive, absorbing about 25%–40% of total work time, it may even use up to 50% of the fuel in the entire agrotechnical process. In addition, plowing may disrupt the development of many soil organisms and increase the rate of mineralization of organic matter (Jaskulski & Jaskulska, 2016).…”

Section: Resultsmentioning

confidence: 99%

Estimating Soil Surface Roughness With Models Based on the Information About Tillage Practises and Soil Parameters

Herodowicz‐Mleczak

Piekarczyk

Kaźmierowski

et al. 2022

J Adv Model Earth Syst

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The quantitative description of the soil surface roughness is necessary for effective monitoring of wind, water and tillage erosion, hydrological processes or greenhouse gas emissions. The aim of this work was to build soil roughness predictive models based on the type of tillage tool, the roughness indices and soil properties. The roughness formed by five tillage tools was determined. Two surface roughness indices: Height Standard Deviation (HSD) and T3D (Tortuosity index) were calculated from Digital Elevation Model. The both roughness indices demonstrated a significant correlation, however, they provided different information about soil roughness. The HSD describes roughness on the “macro,” while T3D refers to the “micro” scale. Hence, our findings show that a single index is not sufficient to describe the roughness of post‐treatment surface. The linear and random forest models were built to describe the relationships between the roughness indices, type of tillage tool and soil properties. The HSD analysis indicated that the type of tillage tools had the greatest impact on post‐treatment roughness. In contrast, T3D analysis found soil texture to have a significant effect, together with tillage tools. In all modeling scenarios, T3D was more accurately predicted than HSD by both the linear (R2 = 0.62 vs. R2 = 0.60) and random forest models (R2 = 0.58 vs. R2 = 0.55). Predictive soil surface roughness models can be applied effectively for estimating water retention in soil, the intensity and speed of surface water flow, soil erosion, the level of reflected shortwave solar radiation or soil properties by remote sensing techniques.

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Section: Resultsmentioning

confidence: 99%

Estimating Soil Surface Roughness With Models Based on the Information About Tillage Practises and Soil Parameters

Herodowicz‐Mleczak

Piekarczyk

Kaźmierowski

et al. 2022

J Adv Model Earth Syst

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“…Moreover, the results showed that the relative increase percentages due to fertilization (10 ton/fad) were 72.74, 68.72 and 68.90 % for the three seasons, respectively compared with 0 ton/fad organic fertilization. Harmony discoveries were made by (Jaskulska et al, 2017;Abofard et al, 2021 andYassin et al, 2021). Root fresh weight (L.E/fad): The results in Table (7) showed that root fresh weights (L.E/fad) were significantly affected by using different organic fertilization.…”

Section: Sugar Yield (Kg/fad)mentioning

confidence: 99%

Response assessment of some sugar beet (Beta vulgaris L.) cultivars to organic fertilizers treatments under South Sinai conditions

Abdelaziz

2023

Journal of Plant Production Sciences

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Sugar beet is considered the leading crop in the arid sugar field in Egypt, and the main goal of this study is to increase the production of sugar varieties in those areas with efficiency, especially since its cultivation is still the most suitable for the region. To achieve this goal, a research experiment was conducted in the development area in South Sinai Governorate for four varieties of sugar beets (Casupia -Salama -Sahar -Faten) with three applications of organic fertilization (0, 5, 10 tons/fad). The experiment was carried out in a split plot design, with a randomized complete block system with four replications, for three agricultural seasons (2019/2020, 2020/2021, and 2021/2022). Field data was taken for 16 morphological and productive characters of sugar beets as indicators to detect the level of productivity under the conditions of the ecosystem of the Al-Tur region in South Sinai. The results of the experiment resulted in the Salama variety being significantly superior to the other studied varieties by 8.5%. It also became clear that organic fertilization had a significant impact on facilitating the absorption of elements and reducing salt stress, considering that under organic fertilization rates, the Salama variety gave the highest productivity with organic fertilization at a rate of 10 ton/fad, and productivity increased by 167% over the variety, Casupia without using organic fertilization. Accordingly, the study recommended the need to use the Salama variety under organic fertilization conditions at a rate of 10 ton/fad, which contributes to improving sustainable sugar beet production in the Al-Tur region, South Sinai, Egypt, and places with comparable ecological characteristics.

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Yields and the composition of roots of sugar beet varieties tolerant to the beet cyst nematode

Cited by 2 publications

References 0 publications

Estimating Soil Surface Roughness With Models Based on the Information About Tillage Practises and Soil Parameters

Estimating Soil Surface Roughness With Models Based on the Information About Tillage Practises and Soil Parameters

Response assessment of some sugar beet (Beta vulgaris L.) cultivars to organic fertilizers treatments under South Sinai conditions

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