• Journal of Biosystems Engineering
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• v.24 no.2
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• pp.135-144
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• 1999

An yield monitoring system plays a key role in precision farming. An yield monitoring system and a DGPS were implemented to a widely used domestic combine for yield mapping of a small sized paddy field, and yield mapping algorithms were investigated in this study. The yield variation in the 0.1ha rice paddy field was measured by installing a yield flow sensor and a grain moisture sensor at the end of the clean grain elevator discharging grains into a grain tank. Yield map of the test filed was drawn in a point map and a linear interpolated map based on the result of the field test. The size of a unit yield grid in yield mapping was determined based on the combine traveling speed, effective harvesting width and data storing period. It was possible to construct the yield map of a small sized paddy field.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.10a
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• pp.277-280
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• 2009

This paper deals with the performance evaluation of Barlat's and BBC yield criteria by the directional variation prediction of the yield stresses and the R-values. for the evaluation of yield criteria, three kinds of Aluminum alloys and two kinds of steels were selected and their material properties are from Stoughton and Yoon's work. The experimental data required for the parameter evaluation included the uniaxial yield stresses and R-values (width-to-thickness strain ratio in uniaxial tension) measured in rolling direction, diaganol direction and the transverse direction, the equibiaxial yield stress and the R-value of equibiaxial tension. The optimization method, the Downhill Simplex method, was selected for the coefficient identification of Barlat91, Barlat97 and Barlat2000 yield criteria. Yield surface shapes, yield stress and R-value directionalities of Barlat's and BBC yield criteria were investigated and compared with the experimental data. Barlat2000 and BBC yield criteria were extremely qualified for the shape of the yield surface and the directionality of the yield stresses and the R-values.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.31 no.3
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• pp.318-325
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• 1986

The studies were performed to obtain the basic informations on the influence of weather condition for grain yield and yield components in barley. The data of Olbori tested in 9 sites for 12 years were used in the studies. Milled grain yield was decreased in paddy field after rice harvested comparing to the upland condition, and yield potential was differed by test sites with the most stable yield in Gyeongnam. The coefficients of variation analyzed for milled grain yield by years were 12.2-42.6% with the differences between high-yield and low-yield year. Heading date was earlier in high-yield year and southern part compared to the low-yield year and middle part of the Korean peninsular showing the negative correlation between grain yield and heading date. High-yield year showed longer in culm length, shorter in spike length, almost same in number of grains per spike, and lower in 1,000grain weight compared to the low-yield year. Correlation analyzed between number of spikes and grain yield showed positive relationship. Temperatures affected to the grain yield analyzed by high in vegitative growth stage, low in alternative growth stage, and almost same in reproductive growth stage in high-yield year comparing to the low-yield year, however no remarkable differences of temperatures affected were detected in over wintering stage between high-yield and low-yield year. Precipitation amount in high-yield year was lesser in sowing time, more in seedling time, and lesser in over wintering time than those of the low-yield year. Correlation between rainfall amount in the early of April and grain yield showed significant negative correlation with the remarkable affects to the grain yield. Sunshine hours in high-yield year were longer in sowing time, shorter in over wintering time, and after the over wintering time to harvesting time was longer than those of the low-yie-ld year.

• Transactions of Materials Processing
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• v.31 no.4
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• pp.214-228
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• 2022

The yield criterion, or called yield function, plays an important role in the study of plastic working of a sheet because it governs the plastic deformation properties of the sheet during plastic forming process. In this paper, we propose a novel anisotropic yield function useful for describing the plastic behavior of various anisotropic sheets. The proposed yield function includes the anisotropic version of the second stress invariant J₂ and the third stress invariant J₃. The anisotropic yield function newly proposed in this study is as follows. F(J₂)+ αG(J₃)+ βH (J₂ × J₃) = k^m The proposed yield function well explains the anisotropic plastic behavior of various sheets by introducing the parameters α and β, and also exhibits both symmetrical and asymmetrical yield surfaces. The parameters included in the proposed model are determined through an optimization algorithm from uniaxial and biaxial experimental data under proportional loading path. In this study, the validity of the proposed anisotropic yield function was verified by comparing the yield surface shape, normalized uniaxial yield stress value, and Lankford's anisotropic coefficient R-value derived with the experimental results. Application for the proposed anisotropic yield function to aluminum sheet shows symmetrical yielding behavior and to pure titanium sheet shows asymmetric yielding behavior, it was shown that the yield curve and yield behavior of various types of sheet materials can be predicted reasonably by using the proposed new yield anisotropic function.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.5
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• pp.102-109
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• 1985

A new yield maximization procedure by investigating method of the multidimensional Monte Carlo integration is presented. And then maximum yield is obtained by the new modified weight selection algorithm applied to objective function of MOSFET NAND GATE Also this yield maximization procedure can be applied to nonconvex objective function.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.354-354
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• 2017

Rice grain yield is determined by crop dry matter production that is sensitive to temperature. Our objective was to determine whether the difference in temperature between years had an impact on the relationship between yield components and grain yield. Field experiments were conducted under machine transplanting cultivation by using yield data of two japonica rice varieties, Odaebyeo (early maturing) and Nampyeong (mid-late maturing), in 2013 to 2016 in Suwon, Korea. Plant height, dry weight, and yield components were examined by analysis of variance, correlation. The milled rice yield of the two varieties were the highest in 2016, however the lowest yields were observed in the different years. In 2016, Odaebyeo produced $0.96t\;ha^{-1}$ greater milled rice yield than in 2015, and Nampyeong produced $1.11t\;ha^{-1}$ greater yield than in 2013. The correlation analysis indicated that spikelet per panicle (R = 0.53) was associated with grain yield of Odaebyeo. In Nampyeong, biomass at heading date (R = 0.74), 1000-grain weight (R = 0.71), spikelet per panicle (R = 0.58), and panicle number per $m^2$ were associated with grain yield. Sink size (spikelet number per $m^2$) of the two varieties responded to accumulative temperature from transplanting to panicle initiation stage. In this experiment, optimal accumulative temperature before panicle initiation has effect on increased spikelet number and/or number of panicle that were mainly responsible for yield difference. Rice production research to increase grain yield should consider all yield components, but increased emphasis on biomass production before heading is also necessary as well as grain ripening conditions.

• Transactions of Materials Processing
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• v.31 no.6
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• pp.351-364
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• 2022

The yield criterion, or called yield function, plays an important role in the study of plastic working of a sheet because it governs the plastic deformation properties of the sheet during plastic forming process. In this paper, we propose a modified version of previous anisotropic yield function (Trans. Mater. Process., 31(4) 2022, pp. 214-228) based on J2 and J3 stress invariants. The proposed anisotropic yield model has the 6th-order of stress components. The modified version of the anisotropic yield function in this study is as follows. f(J₂⁰,J₃⁰) ≡ (J₂⁰)³ + α(J₃⁰)² + β(J₂⁰)^3/2 × (J₃⁰) = k⁶ The proposed anisotropic yield function well explains the anisotropic plastic behavior of various sheets such as aluminum, high strength steel, magnesium alloy sheets etc. by introducing the parameters α and β, and also exhibits both symmetrical and asymmetrical yield surfaces. The parameters included in the proposed model are determined through an optimization algorithm from uniaxial and biaxial experimental data under proportional loading path. In this study, the validity of the proposed anisotropic yield function was verified by comparing the yield surface shape, normalized uniaxial yield stress value, and Lankford's anisotropic coefficient R-value derived with the experimental results. Application for the proposed anisotropic yield function to AA6016-T4 aluminum and DP980 sheets shows symmetrical yielding behavior and to AZ31B magnesium shows asymmetric yielding behavior, it was shown that the yield locus and yielding behavior of various types of sheet materials can be predicted reasonably by using the proposed anisotropic yield function.

• Journal of Environmental Science International
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• v.16 no.12
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• pp.1319-1324
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• 2007

A tank model in conjunction with Kalman filter is developed for prediction of sediment yield from an upland watershed in Northwestern Mississippi. The state vector of the system model represents the parameters of the tank model. The initial values of the state vector were estimated by trial and error. The sediment yield of each tank is computed by multiplying the total sediment yield by the sediment yield coefficient. The sediment concentration of the first tank is computed from its storage and the sediment concentration distribution(SCD); the sediment concentration of the next lower tank is obtained by its storage and the sediment infiltration of the upper tank; and so on. The sediment yield computed by the tank model using Kalman filter was in good agreement with the observed sediment yield and was more accurate than the sediment yield computed by the tank model.

• International Journal of Industrial Entomology and Biomaterials
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• v.4 no.2
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• pp.143-147
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• 2002

Studies on the interrelationship between biological yield and harvest index, and their association with shoot rearing were carried out in 9 promising mulberry genotypes, which indicated significant variations among genotypes. Biological yield had close association with leaf yield components indicating that they are inter-related for higher productivity in mulberry, Biological yield revealed highly significant positive correlation with important leaf yield components. However height of the longest branch showed negative correlation with biological yield. Genotypes with higher biological yield associated with low ratio of stem weight to leaf weight and high Harvest index on dry weight basis are to be selected for shoot rearing. Biological yield recorded on fresh weight basis had less impact on the present study in comparison to dry weight basis.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.4
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• pp.614-621
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• 2012

Although there is a broad dispute over genetically modified foods on safety, the worldwide adoption of transgenic crops is rapidly increasing. The objectives of this study were to identify trends in the effects of transgenic on crop yields and examine the effect of agricultural variables including crop type, biotech trait, tillage system, and yield environment on corn and soybean yield. A meta-analysis from the 34 peer-reviewed scientific literatures was conducted to compare the crop yield between transgenic crops and conventional varieties. Results showed that the yield of transgenic corn and soybean was strongly dependent on growing conditions. Transgenic hybrids had higher yield potential in the low crop yield environments such as high weeds and/or insect infestation, low soil water, and cool temperature conditions, while transgenic crops did not have yield advantages in high yield environments. The results from this study suggest that producers should consider the potential yield environmental conditions and possible yield reductions when producers choose crop hybrids in their fields.