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MUNDAN, Durhasan, Reşit DEMİR, and Esma PAYDAŞ. "İvesi Koyunlarda Kontrol Günü Verimlerinden Yararlanarak Laktasyon Verimini Tahmin Etme Metotları." Journal of Advances in VetBio Science and Techniques 7, no. 2 (August 31, 2022): 153–60. http://dx.doi.org/10.31797/vetbio.1056967.
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The objective of this study was to determine the effect of various milk control methods on prediction accuracy of lactation milk yield for Awassi sheep. Different control methods (Sweden, Vogel, Holland I, Holland II, Trapeze I, Trapeze II and State Production Farm methods) and control periods (14th, 21st, 28th, 42nd and 56th day) used to determine lactation milk yield were compared. The data of the research was created within the scope of the "National Project of Small Ruminant Animal Breeding in the Hands of the People" in 2018 and a total of 3173 sheep records belonging to 31 enterprises were used. The actual lactation yield in the study was determined as 255.570.85 kg and the lactation length as 170.620.19 day. Correlation coefficients between the actual lactation yield and lactation yield calculated according to different control methods were found to be high and significant for all control periods and control methods (P<0.05, P<0.01, P<0.001). It gave the similar results to the actual lactation yield in the Vogel method calculated according to different control methods in a period of 28th days, in the Trapeze I method in a period of 28th and 42nd days, in the Trapeze II method in all periods (P>0.05). In the other control periods, all methods differed significantly from the actual lactation yield (P<0.05, P<0.01, P<0.001). As a result, it has been concluded that results close to the actual lactation yield will be obtained by using one of the Vogel or Trapeze I-II methods calculated by using the milk yields on the control day of Awassi sheep raised under Şanlıurfa conditions.
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Kulla, L., J. Tutka, and R. Marušák. "Forest yield index and its applicability to the assessment of future forest yields." Journal of Forest Science 55, No. 1 (February 3, 2009): 41–50. http://dx.doi.org/10.17221/45/2008-jfs.
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The paper suggests and examines a simplified relative indicator of forest production, with special regard to possibilities of its use in projecting future forests. Forest yield index (<I>I</I><sub>Y</sub>), based on an economic parameter “value of final cutting yield” was proposed, and examined in the model territory of Kysuce in north-western Slovakia. The current values of final cutting yield, dependent on tree species, site index and the length of rotation period served as a basis for the assessment of expected yields. The possibilities and limitations of index applicability in long-term strategic forest management decision-making are discussed, considering the uncertainty of ecological and economic conditions during the long forest production cycle, as well as the complexity of tree species growth and production in the mixed forests, uneven aged forests and forests under climate change.
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Kucharik, Christopher J., Tanjona Ramiadantsoa, Jien Zhang, and Anthony R. Ives. "Spatiotemporal trends in crop yields, yield variability, and yield gaps across the USA." Crop Science 60, no. 4 (May 28, 2020): 2085–101. http://dx.doi.org/10.1002/csc2.20089.
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Jubinski, Daniel, and Amy F. Lipton. "Equity volatility, bond yields, and yield spreads." Journal of Futures Markets 32, no. 5 (May 26, 2011): 480–503. http://dx.doi.org/10.1002/fut.20521.
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Yustisia, Yustisia, NP Sri Ratmini, J. Amirrullah, Y. Juwita, YPAP Hutabarat, and Atekan Atekan. "Yield Components and Efficiency Index of Maize Yield: Relationship to Yields in Tidal Fields." Jurnal Lahan Suboptimal : Journal of Suboptimal Lands 10, no. 2 (October 1, 2021): 140–49. http://dx.doi.org/10.36706/jlso.10.2.2021.522.
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Identification of the advantages of hybrid maize lines is needed to support the increased production and development of maize in tidal fields. This study aimed to identify the agronomic characters and yield components of hybrid maize lines/varieties and their relationship with high yield and efficient fertilization in tidal fields. The design used was a Split Plot with three replications. The Main Plot was a hybrid maize line/variety (L39/MR4, MGOLD/G8, G28/MGOLD, P27). The subplots were Composite Fertilizer with 2 measures, namely 600 kg/ha and 720 kg/ha. The fertilizers of Urea (50%), SP 36 and NPK (100%) were given at 10 days after planting (DAP). The remaining Urea was given at 30 DAP, 50% and 58.33% respectively in the Composite Fertilizer treatment of 600 kg/ha and 720 kg/ha. The technical culture applied was optimum tillage with the 70 cm x 25 cm spacing, the irrigation being carried out at D/DAP and 15 DAP, the optimal control on the weed and Plant Pest Organisms. The result showed that the number of rows/cobs was an alternative variable in identifying maize lines/varieties with high yield and efficient fertilization. This character was closely correlated with seed/ear weight (r = 0.94) and Grain Yield Efficiency Index/GYEI (r = 0.84). All Genotypes were nutrient efficient (GYEI > 1) except G28/MGOLD (IGYEI < 1). Another approach used to identify efficient fertilization lines/varieties was the variable percentage of yield reduction through regression equations with GYEI (y = - 0.0104 x + 1.0426). The character of high number of rows/cob could be used as genetic material in plant breeding programs. The lines/varieties as a component of efficient technology and high productivity would contribute to increase production and development of maize in tidal fields.
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NeSmith, D. S. "Plant Spacing Influences Watermelon Yield and Yield Components." HortScience 28, no. 9 (September 1993): 885–87. http://dx.doi.org/10.21273/hortsci.28.9.885.
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Watermelon [Citrullus lanatus (Thunb.) Matsum & Nakai] cultivars StarBrite and Crimson Sweet were grown during 1991 and 1992 in rows 1.5 m apart at plant spacings of 0.9, 1.5, or 2.2 m. Total fruit yield, marketable fruit yield, fruit-weight distribution, and estimated gross returns were determined for each spacing treatment. Total and marketable fruit yields were greater overall for `StarBrite' than for `Crimson Sweet'. Except for 1991 `Crimson Sweet' yields, marketable fruit yields per unit land area increased 29% to 34% as plant spacing decreased from 2.2 to 0.9 m. The yield component contributing the most to increased yields with high-density plantings was increased fruit count per unit land area. Average fruit weight responded only slightly to decreased plant spacing. Fruit-weight distribution on a relative frequency scale was stable regardless of plant spacing or production year. The potential for increasing gross returns per unit land area exists by increasing watermelon plant populations beyond the current Georgia recommendation of 2500 to 3000 plants/ha.
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Asthir, Bavita, Shashi Bala, and Navtej Singh Bains. "Effect of Terminal Heat Stress on Yield and Yield Attributes of Wheat." Indian Journal of Applied Research 4, no. 6 (October 1, 2011): 1–2. http://dx.doi.org/10.15373/2249555x/june2014/1.
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D. Malath, D. Malath, and P. Gomathinayagam P. Gomathinayagam. "Correlation Analysis for Yield and Yield Contributing Characters Involving in Aerobic Rice." International Journal of Scientific Research 2, no. 10 (June 1, 2012): 1–2. http://dx.doi.org/10.15373/22778179/oct2013/159.
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Y.A, NANJA REDDY, PRASAD T.G, and UDAYA KUMAR M. "GENOTYPIC VARIATION IN YIELD ATTRIBUTES AND YIELD OF RICE." Madras Agricultural Journal 82, April (1995): 310–13. http://dx.doi.org/10.29321/maj.10.a01196.
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Experiment was carried out to bring out the genotypic variations from a broad genetic base and to utilise the best attribute in achieving higher grain yields. The results indicated significant genotypic differences in yield attributes and yield. The association analysis showed a significant positive relationship of grain yield with productive tillers, filled grain number per panicle, 1000 grain weight and harvest index. Among the yield attributes productive tillers, filled grain number per panicle and harvest index contributed to a greater extent in achieving the productivity. This indicates, the selection of numerically high value for each yield attribute and incorporating in a single genotype may boost the grain yields significantly to a higher level. However, grain size is not a preferable character in consumer point of view. Therefore, selection of genotypes with large number of productive tillers and filled grain per panicle may be worthwhile.
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Assefa, Banchayehu Tessema, Jordan Chamberlin, Pytrik Reidsma, João Vasco Silva, and Martin K. van Ittersum. "Unravelling the variability and causes of smallholder maize yield gaps in Ethiopia." Food Security 12, no. 1 (December 2, 2019): 83–103. http://dx.doi.org/10.1007/s12571-019-00981-4.
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AbstractEthiopia has achieved the second highest maize yield in sub-Saharan Africa. Yet, farmers’ maize yields are still much lower than on-farm and on-station trial yields, and only ca. 20% of the estimated water-limited potential yield. This article provides a comprehensive national level analysis of the drivers of maize yields in Ethiopia, by decomposing yield gaps into efficiency, resource and technology components, and accounting for a broad set of detailed input and crop management choices. Stochastic frontier analysis was combined with concepts of production ecology to estimate and explain technically efficient yields, the efficiency yield gap and the resource yield gap. The technology yield gap was estimated based on water-limited potential yields from the Global Yield Gap Atlas. The relative magnitudes of the efficiency, resource and technology yield gaps differed across farming systems; they ranged from 15% (1.6 t/ha) to 21% (1.9 t/ha), 12% (1.3 t/ha) to 25% (2.3 t/ha) and 54% (4.8 t/ha) to 73% (7.8 t/ha), respectively. Factors that reduce the efficiency yield gap include: income from non-farm sources, value of productive assets, education and plot distance from home. The resource yield gap can be explained by sub-optimal input use, from a yield perspective. The technology yield gap comprised the largest share of the total yield gap, partly due to limited use of fertilizer and improved seeds. We conclude that targeted but integrated policy design and implementation is required to narrow the overall maize yield gap and improve food security.
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Abdalbagi, Salma I., and Maarouf I. Mohammed. "Assessing Ethanol Yield from Fermented Juice of Local and Exotic Sweet Sorghum Varieties Grown in Sudan." Journal of Horticulture and Plant Research 12 (March 2021): 11–17. http://dx.doi.org/10.18052/www.scipress.com/jhpr.12.11.
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An experiment was conducted in 2017 at Alwaha Project, Khartoum State to study the potential of ethanol yield from fermented juice of local and exotic sweet sorghums. 40 genotypes were arranged in RCB design. Juice yield, ethanol yield as percentage of fermented juice, actual and theoretical ethanol yields were studied. The Baker’s yeast (Saccharomyces cerevisiae) was used in the fermentation process. ANOVA tests, correlation and regression analysis of actual vs theoretical ethanol yield were performed. Significant differences were detected among genotypes for ethanol yields. High ethanol yields as percentage from fermented juice were obtained, but ethanol yield per hectare was relatively low due to low juice yields. The genotypes BlueRibbon and KensasCollies from exotic materials; 5AbjSG51 and S.154 Ab70 from local materials were identified as promising for ethanol production. Correlation between actual ethanol yield and Juice yield was positive and highly significant. Regression analysis indicated that theoretical ethanol yield was little bit overestimated. It was concluded that juice yield is more crucial than ethanol concentration in maximizing ethanol yield of sweet sorghum. More efforts are needed to develop high juice-yielding genotypes. Juice maximization can also be achieved by using efficient milling devices and optimizing cultural practices.
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Yuldasheva, Zulfiya Kamalovna, and Nargiza Khashimjanovna Ergasheva. "Effects Of Sowing Scheme On Yield Elements And Yield Of Oil Sunflower Varieties." American Journal of Agriculture and Biomedical Engineering 03, no. 01 (March 6, 2021): 1–5. http://dx.doi.org/10.37547/tajabe/volume03issue01-01.
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In this scientific article, new Buzuluk and Irtish fast-ripening and the local Dilbar varieties of sunflower from the All-Russian Scientific Research Institute of Oilseeds named after V.S. Pustovayt were planted in 70x20, 70x25, 70x30, 70x35 planting scheme, and among the varieties Buzuluk variety showed high results. Dilbar, Buzuluk varieties were found to have high yields in the 70x30 sowing scheme (27.5 and 32.6 ts/ha), and Irtish varieties in the 70x25 sowing scheme (25.6 ts/ha).
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Vinoth, P., E. Murugan, and M. Arumugam Pillai M. L. Mini. "Association Analysis for Yield and Yield Component Traits in Sesame Sesamum indicum L." International Journal of Trend in Scientific Research and Development Volume-2, Issue-5 (August 31, 2018): 745–47. http://dx.doi.org/10.31142/ijtsrd15894.
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Slafer, GA, and GC Kernich. "Have changes in yield (1900-1992) been accompanied by a decreased yield stability in Australian cereal production?" Australian Journal of Agricultural Research 47, no. 3 (1996): 323. http://dx.doi.org/10.1071/ar9960323.
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Regression analyses of the relationships between yield and time over the last century were conducted for wheat, barley, oats, maize, and rice at a national level and those for the three winter cereals in New South Wales (NSW), Victoria (Vic), South Australia (SA), Western Australia (WA), and Queensland (Qld). The fitted function accounts for the impact of agronomic improvement on yield and the residuals stand for the variability of yield beyond this impact. Another measure of the stability was obtained by considering the residuals as a proportion of actual yield ('relative residuals'). Crops varied greatly in their yields but there was no relationship between the coefficient of variation and average yield amongst these cereals. As expected, yields of all five crops are presently higher than early this century. The residuals and relative residuals for each crop were plotted against years. Residuals of wheat yields over time showed no increase or decrease during the century, but the relative residuals exhibited a clear trend towards an increased yield stability. Barley and oats showed sirnilar patterns to those of wheat. Residuals of maize yields increased with time, but relative residuals remained unchanged. Rice yields exhibited the largest residuals, but no trends with time. Yield stability, measured as a proportion of yield, has been clearly improved during this century. Yield trends for the winter cereals at a State level confirmed the results observed at a national level. In conclusion, yields of newer cultivars grown under modern management were higher and more stable, or at least not less stable, than those of crops grown early in the century. Across States and crops, there was no relationship between yield stability and yield.
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Wang, Chong, Jiangang Liu, Shuo Li, Ting Zhang, Xiaoyu Shi, Zhaohai Zeng, Yongdeng Lei, and Qingquan Chu. "Diagnosing the Climatic and Agronomic Dimensions of Rain-Fed Oat Yield Gaps and Their Restrictions in North and Northeast China." Sustainability 11, no. 7 (April 9, 2019): 2104. http://dx.doi.org/10.3390/su11072104.
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Confronted with the great challenges of globally growing populations and food shortages, society must achieve future food security by increasing grain output and narrowing the gap between potential yields and farmers’ actual yields. This study attempts to diagnose the climatic and agronomic dimensions of oat yield gaps and further to explore their restrictions. A conceptual framework was put forward to analyze the different dimensions of yield gaps and their limiting factors. We quantified the potential yield (Yp), attainable yield (Yt), experimental yield (Ye), and farmers’ actual yield (Ya) of oat, and evaluated three levels of yield gaps in a rain-fed cropping system in North and Northeast China (NC and NEC, respectively). The results showed that there were great differences in the spatial distributions of the four kinds of yields and three yield gaps. The average yield gap between Yt and Ye (YG-II) was greater than the yield gap between Yp and Yt (YG-I). The yield gap between Ye and Ya (YG-III) was the largest among the three yield gaps at most sites, which indicated that farmers have great potential to increase their crop yields. Due to non-controllable climatic conditions (e.g., light and temperature) for obtaining Yp, reducing YG-I is extremely difficult. Although YG-II could be narrowed through enriching soil nutrients, it is not easy to improve soil quality in the short term. In contrast, narrowing YG-III is the most feasible for farmers by means of introducing high-yield crop varieties and optimizing agronomic managements (e.g., properly adjusting sowing dates and planting density). This study figured out various dimensions of yield gaps and investigated their limiting factors, which should be helpful to increase farmers’ yields and regional crop production, as long as these restrictions are well addressed.
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Zymaroieva, Anastasiia, Tetiana Fedoniuk, Svitlana Matkovska, Olena Andreieva, and Victor Pazych. "Agroecological Determinants of Potato Spatiotemporal Yield Variation at the Landscape Level in the Central and Northern Ukraine." Grassroots Journal of Natural Resources 4, no. 2 (May 30, 2021): 34–47. http://dx.doi.org/10.33002/nr2581.6853.040203.
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Global food security largely depends on the crop yield increase, so the study of the yield-limiting factors of potato (the second bread) is a pressing issue today. This study determines the contribution of the agroecological factors, namely, bioclimatic variables, soil indicators, and factors of landscape diversity, to the variation in potato yields. Conducted in Polissya and Forest-steppe zones of Ukraine during 1991–2017, this study has not only addressed the relationship between ecological determinants and potato yields, but also considered crop yields as a dynamic system. The dynamics of potato yields from the mid-1990s to the present is described by a log-logistic model. There are statistically significant regression dependencies between potato yield parameters and agroecological factors. Potato yield is dependent on the diversity of landscape cover. The relationship between yield parameters and landscape-ecological diversity is non-linear, which determines the presence of optimal landscape structure for the highest potato yields. Among climatic factors, the continental climate is of the greatest importance for potato yield. The high sensitivity of potato yield parameters to soil indices was found, and mostly the soil texture components (silt content), which largely determines the potato yield spatial variation.
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Gravois, KA, and RS Helms. "Effect of uneven emergence on rice yield, milling yield, and yield components." Australian Journal of Experimental Agriculture 34, no. 7 (1994): 949. http://dx.doi.org/10.1071/ea9940949.
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Establishing a uniform rice (Oryza sativa L.) stand is an important beginning to managing a rice crop and attaining high yields. Most rice management practices in the United States are timed according to rice growth stages. Non-uniform rice stands, and subsequently non-uniform growth stages, present problems for the timely application of management practices for attaining high yields. Our objective was the determination of the effects of uneven emergence on rice yield, milling yield, and yield components. Experiments were conducted in 1988 and 1989 on a Hebert silt loam (Vertic Hapludoll) at the Southeast Branch Experiment Station near Rohwer, Arkansas. Uneven emergence was simulated by delayed (18 days from emergence) interseeding of rice to achieve 0, 20, 40, 60, and 80% uneven emergence. Each experiment was planted with the cultivars Lemont (semi-dwarf) and Tebonnet (tall) and was replicated 4 times. Rice yields for the uneven emergence treatment levels were significantly less than the rice yields seeded exclusively at PD1 (planting date 1), except for the uneven emergence levels 80-20 (80% planted at PD1 and 20% planted at PD2) and 60-40 for Tebonnet, and 60-40 in 1988 for Lemont. In 1989, there was a trend for head rice yields to decrease as uneven emergence levels increased. Average panicle density and number of grains per panicle for both Lemont and Tebonnet decreased with increasing uneven emergence, indicating a failure in the typical compensatory relationship between panicle density and grain per panicle. Lemont exhibited reduced average grain weights due to uneven emergence, especially at 80-20, 60-40, and 40-60 uneven emergence levels. Harvest indices were higher for PD1 than for PD2, except at 20-80 uneven emergence level. Essentially, the later emerging rice from the second planting acted much like a weed by competing against rather than contributing to rice yields. Late interseeding to enhance poor rice stands is unlikely to produce an economic return that could be expected from an adequate initial plant stand.
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Novy, Elissa M., and Nicholi Vorsa. "CRANBERRY VARIETY FRUIT YIELD AND YIELD COMPONENETS." HortScience 28, no. 4 (April 1993): 258E—258. http://dx.doi.org/10.21273/hortsci.28.4.258e.
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Accurate estimates of yield and yield components for parental selection would facilitate cranberry breeding efforts. A study was designed to obtain value estimates for traits related to yield. Ten commonly-cultivated varieties grown in a replicated planting, were evaluated in 1991 and 1992 for fruit yield per unit area (FY), average berry weight (BW) and number of berries per unit area, or berry concentration (BC). Averaged over all varieties, FY was significantly greater in 1992. BC was responsible for higher yields in 1992. Regression analysis revealed that BC accounted for more of the variation in FY than did BW in both years. BW accounted for some variation, however, in 1991 when FY was lower. Varieties differed significantly in FY, BW and BC. Hybrid varieties bad significantly greater FY and BW than wild selections. Variation for yield components exists among varieties tested, suggesting genetic gain is possible for yield with additional breeding efforts. In particular, greater fruit set should be emphasized as a breeding objective.
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Roell, Yannik E., Amélie Beucher, Per G. Møller, Mette B. Greve, and Mogens H. Greve. "Comparing a Random Forest Based Prediction of Winter Wheat Yield to Historical Yield Potential." Agronomy 10, no. 3 (March 14, 2020): 395. http://dx.doi.org/10.3390/agronomy10030395.
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Predicting wheat yield is crucial due to the importance of wheat across the world. When modeling yield, the difference between potential and actual yield consistently changes because of advances in technology. Considering historical yield potential would help determine spatiotemporal trends in agricultural development. Comparing current and historical yields in Denmark is possible because yield potential has been documented throughout history. However, the current national winter wheat yield map solely uses soil properties within the model. The aim of this study was to generate a new Danish winter wheat yield map and compare the results to historical yield potential. Utilizing random forest with soil, climate, and topography variables, a winter wheat yield map was generated from 876 field trials carried out from 1992 to 2018. The random forest model performed better than the model based only on soil. The updated national yield map was then compared to yield potential maps from 1688 and 1844. While historical time periods are characterized by numerous low yield potential areas and few highly productive areas, current yield is evenly distributed between low and high yields. Advances in technology and farm practices have exceeded historical yield predictions, mainly due to the use of fertilizer, irrigation, and drainage. Thus, modeling yield projections could be unreliable in the future as technology progresses.
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Olson, Stephen M., and Peter J. Stoffella. "Yield Stability Differences Among Collard Cultivars." HortScience 24, no. 3 (June 1989): 495–97. http://dx.doi.org/10.21273/hortsci.24.3.495.
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Abstract Eight collard (Brassica oleracea L. Acephala Group) cultivars were evaluated for phenotypic yield stability during 4 years in northern Florida. A cultivar, characterized as possessing stability, performed above average yield in both favorable and unfavorable environments, with minimal deviations between environments. Linear relationships between individual cultivar yields and environmental mean yields were used to statistically evaluate phenotypic stability. Cultivars with mean yields above the grand mean, regression coefficients ≤1, and coefficient of linear determination ≥50% were considered to have phenotypic stability. Using these statistical criteria, only ‘Blue Max’ was considered to have phenotypic yield stability; all other cultivars were considered to be unstable. Selection for improved collard yield adaptability could be performed using empirical formulas already developed.
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Pu, Luoman, Shuwen Zhang, Jiuchun Yang, Liping Chang, and Shuting Bai. "Spatio-Temporal Dynamics of Maize Potential Yield and Yield Gaps in Northeast China from 1990 to 2015." International Journal of Environmental Research and Public Health 16, no. 7 (April 4, 2019): 1211. http://dx.doi.org/10.3390/ijerph16071211.
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Maize yield has undergone obvious spatial and temporal changes in recent decades in Northeast China. Understanding how maize potential yield has changed over the past few decades and how large the gaps between potential and actual maize yields are is essential for increasing maize yield to meet increased food demand in Northeast China. In this study, the spatial and temporal dynamics of maize potential yield in Northeast China from 1990 to 2015 were simulated using the Global Agro-ecological Zones (GAEZ) model at the pixel level firstly. Then, the yield gaps between actual and potential yields were analyzed at city scale. The results were the following. (1) The maize potential yield decreased by about 500 kg/ha and the potential production remained at around 260 million tonnes during 1990–2000. From 2000 to 2015, the maize potential yield and production increased by approximately 1000 kg/ha and 80 million tonnes, respectively. (2) The maize potential yield decreased in most regions of Northeast China in the first decade, such as the center area (CA), south area (SA), southwest area (SWA), and small regions in northeast area (NEA), due to lower temperature and insufficient rainfall. The maize potential yield increased elsewhere. (3) The maize potential yield increased by more than 1000 kg/ha in the center area (CA) in the latter 15 years, which may be because of the climate warming and sufficient precipitation. The maize potential yield decreased elsewhere and Harbin in the center area (CA). (4) In 40 cities of Northeast China, the rates of actual yield to potential yield in 17 cities were higher than 80%. The actual yields only attained 50–80% of the potential yields in 20 cities. The gaps between actual and potential yields in Hegang and Dandong were very large, which need to be shrunk urgently. The results highlight the importance of coping with climate change actively, arranging crop structure reasonably, improving farmland use efficiency and ensuring food security in Northeast China.
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Kubešová, K., J. Balík, O. Sedlář, and L. Peklová. "The impact of nitrogen fertilizer injection on kernel yield and yield formation of maize." Plant, Soil and Environment 60, No. 1 (January 22, 2014): 1–7. http://dx.doi.org/10.17221/208/2013-pse.
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In field experiments over three vegetation periods (2010–2012) we studied impact of the CULTAN (controlled uptake long term ammonium nutrition) method on yield and yield parameters of kernel maize. The field experiments were conducted at three sites with different soil-climatic conditions. CULTAN treatments were fertilized once with the total amount of nitrogen using an injection machine (at the canopy height of 20 cm) and compared to conventional fertilization with calcium ammonium nitrate application at pre-sowing preparations. In all treatments the amount of nitrogen was the same, 140 kg N/ha. In 2010 at Humpolec site, CULTAN urea ammonium nitrate + inhibitor of nitrification treatment gave by 20.5% higher number of ears compared to CULTAN urea ammonium nitrate treatment. In 2011 at Ivanovice all CULTAN treatments reached statistically significantly higher number of kernels per ear. The higher 1000 kernel weight at CULTAN treatments was observed in 2012 at the Ivanovice site; a statistically significant difference between conventional and CULTAN urea ammonium nitrate + inhibitor of nitrification treatment was observed. Fertilization of maize with nitrogen using the CULTAN method under the conditions of the Czech Republic provides the same yield certainty as the conventional surface application and the CULTAN method of fertilization increases the yield certainty at delayed sowing. Harvest index was statistically significantly influenced by year, fertilization treatment and site.
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Zaid, Imdad Ullah, Hidayat-ur Rahman, Sajid Khan, Sana Ullah Khan, Ghulam Ullah, Monsif ur Rehman, Rafi Ullah, and Nazeer Ahmad. "Heterotic response of three-way cross maize hybrids for grain yield and yield components." Journal of Agricultural Science and Applications 03, no. 01 (March 31, 2014): 24–29. http://dx.doi.org/10.14511/jasa.2014.030105.
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Kwesiga, Julius, Kristina Grotelüschen, Kalimuthu Senthilkumar, Daniel Neuhoff, Thomas F. Döring, and Mathias Becker. "Rice Yield Gaps in Smallholder Systems of the Kilombero Floodplain in Tanzania." Agronomy 10, no. 8 (August 5, 2020): 1135. http://dx.doi.org/10.3390/agronomy10081135.
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To meet the growing rice demand in Africa, gaps between actual and attainable yields have to be reduced. In Tanzania, this particularly concerns smallholder rain-fed production systems in the floodplains. After quantifying the existing yield gaps, key contributing factors need to be analyzed to improve site-specific management. Field experiments were conducted for three years and in three pedo-hydrological environments (fringe, middle, and center positions) of the Kilombero floodplain to evaluate: (1) The grain yield under farmers’ management (actual yield), (2) yield with the best-recommended management (attainable yield), and (3) the non-limited yield simulated by the APSIM model (potential yield). In the field, we additionally assessed incremental effects of (1) field bunding and soil levelling, (2 and 3) additionally applying of 60 kg N ha−1, as urea or as farmyard manure (FYM), and (4 and 5) incorporating in-situ-grown leguminous green manures. Attainable yields were determined with mineral N application at 120 kg ha−1, additional PK fertilizer and supplemental irrigation. On average across years and positions, the potential, the attainable, and farmers’ actual yields were 11.5, 8.5, and 2.8 t ha−1 indicating a high total yield gap. About 16–38%, 11–20%, and 28–42% of this gap could be attributed to non-controllable yield-reducing (i.e., pest and diseases), yield-limiting (i.e., water and nutrient deficiencies), and yield-defining factors (i.e., poor soil and crop management), respectively. Results indicate a closure of the exploitable yield gap (differences between attainable and farmers’ actual yields) by up to 6.5 t ha−1 (nearly 60% of the potential yield). This exploitable yield gap was larger in 2016 than in 2017. Also, the gap was larger in the water-limited fringe and middle than in the frequently submerged center positions. Simple field bunds combined with land levelling could close 15–35% of the exploitable yield gap, depending on field positions and year. FYM or green manures were less effective than mineral N; however, in 2017 and in the wetter middle and center positions, they reduced the yield gap by >50%. We conclude that yield gaps in rainfed rice in Kilombero floodplain are large, but that a site- and system-specific adaptation of crop management can close much of the exploitable yield gap and increase grain yields by 0.7–4.8 t ha−1. Similar benefits may be obtained in other hydrologically variable floodplain environments of the region and beyond.
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Grant, C. A., and L. D. Bailey. "Interactions of zinc with banded and broadcast phosphorus fertilizer on the dry matter and seed yield of oilseed flax." Canadian Journal of Plant Science 73, no. 1 (January 1, 1993): 7–16. http://dx.doi.org/10.4141/cjps93-003.
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Field experiments at four sites over 3 yr evaluated the effect of banded and broadcast application of fertilizer P, with and without application of Zn on dry matter yield at flowering, and seed yield of flax. Application of P fertilizer increased dry matter yield and seed yield on a number of soils even when crop growth and yield were restricted by extremely dry conditions. Banded P was more effective than broadcast or residual P in increasing flax yields. Increases in yield due to Zn application were infrequent and showed no definite relation to soil Zn or P. Increases in yields with Zn application generally occurred only where P had been broadcast that season or the year before, while decreases in yields with Zn occurred more frequently where P had been banded. The results showed that increases in flax yields in response to Zn application are most likely to occur where P fertilizer is broadcast at relatively high levels or on soils with a history of heavy P application. Key words: P placement, P, Zn, flax, yield, Zn-P interaction
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Obasi, M. O. "Yield and Yield Component Analysis in Groundbean." East African Agricultural and Forestry Journal 58, no. 1-2 (July 1992): 13–18. http://dx.doi.org/10.1080/00128325.1992.11663153.
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Bonn, D., and M. M. Denn. "Yield Stress Fluids Slowly Yield to Analysis." Science 324, no. 5933 (June 11, 2009): 1401–2. http://dx.doi.org/10.1126/science.1174217.
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Gao, Yakun, Yinli Bi, Shaopeng Ma, Yanxu Zhang, Yun Guo, Yang Zhou, Shihao Xu, and Peter Christie. "Yields of Buckwheat and Alfalfa in an Intercropping System Inoculated with Dark Septate Endophytes in a Coal Mining Subsidence Dryland Area." Agronomy 12, no. 11 (November 16, 2022): 2860. http://dx.doi.org/10.3390/agronomy12112860.
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Coal mining subsidence areas in north Shaanxi province in north China are commonly low-fertility drylands, and intercropping is a popular method locally of maximizing crop yields. Inoculation with dark septate endophytes (DSE) can increase the yields of conventional crops grown in monoculture, but the effects of DSE on the growth and yield of intercropped plants are unknown. Here, a field experiment was conducted in a coal mining subsidence area on the loess plateau in 2020 and 2021. The two crops were buckwheat and alfalfa, with four treatments for each crop: sole cropping control, sole cropping with DSE inoculation, intercropping control, and intercropping with DSE inoculation. The yields, land equivalent ratios, DSE colonization rates, and yield components of buckwheat and alfalfa were compared in the different treatments. Stepwise regression and path analysis was conducted to identify the factors that determined crop yields. Yields of intercropped buckwheat and alfalfa with DSE inoculation increased in two consecutive years compared with sole cropping control, with yields increasing in 2020 by 117 and 86%, respectively. In 2021, the yield of buckwheat in intercropping with DSE inoculation did not increase significantly, but the yield of alfalfa increased by 120% compared with the sole cropping control. Buckwheat-alfalfa intercropping has the advantage of increasing the yield. DSE inoculation significantly increased the yield of buckwheat-alfalfa intercropping in 2020, but there was no yield advantage in 2021. The yield components of buckwheat and alfalfa showed inconsistent differences among experimental treatments. Stepwise regression and path analysis shows that the DSE colonization rate played an important role in the yield, which was an increased in buckwheat and alfalfa in 2020 and 2021. DSE affected the buckwheat yield indirectly by increasing the grain weight per plant, plant phosphorus uptake, and plant nitrogen content. DSE indirectly affected alfalfa yields by increasing plant nitrogen uptake and plant height. DSE may therefore have some potential to increase yields in buckwheat-alfalfa intercropping systems in coal mining subsidence areas.
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Ahmad, R., N. Ahmad, J. C. Stark, and A. Tanveer. "Gram Yield and Yield Components of Spring Wheat Genotypes at Different Moisture Regimes." Journal of Agricultural and Marine Sciences [JAMS] 3, no. 2 (June 1, 1998): 13. http://dx.doi.org/10.24200/jams.vol3iss2pp13-19.
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Yield and developmental characteristics of crop genotypes grown at different levels of water availability are often used to select genotypes that are adapted to variable moisture environments. Field studies were conducted at Aberdeen. Idaho, USA in 1992 and 1993 to evaluate the effects of varying moisture supply on grain yield and yield components of spring wheat genotypes. In both years, 12 spring wheat (Triticum aestivum L.) genotypes were grown under three irrigation levels (well-watered. moderate water-stress and severe water-stress) imposed during the periods from mid-tillering to anthesis with a line source sprinkler irrigation system. Grain yield and yield components (spikes m-2, spikelets spike-1, kernels spikelet-1, kernels spike-1, and kernel weight) were used to evaluate the genotypic response to water stress. Overall, water stress caused a reduction in grain yield and yield components. Genotypes exhibited a large year-to-year variation in their ranks for grain yield. Medium-tall growing genotypes (IDO 367. lDO 369 and Rick) generally produced high yields under water stress conditions in 1992 (relatively dry year), while short -medium genotypes (WPB 926. Yecora Rojo and Pondera) produced high yields under water stress conditions in 1993 (relatively wet year). Chris and Serra were the lowest yielding genotypes under water stress conditions in both years. Under moderate stress conditions. 100 367 and Yecora Rojo had consistently high yields. Genotypic yield differences under water stress conditions were primarily related to the differences in the numbers of spikes m". Therefore, a tendency for high plasticity for Spikes per unit area could be used to select wheat genotypes for improved drought tolerance.
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Villanueva-Mosqueda, Eduardo, and Michael J. Havey. "Genetic Analyses of Seed Yield in Onion." Journal of the American Society for Horticultural Science 126, no. 5 (September 2001): 575–78. http://dx.doi.org/10.21273/jashs.126.5.575.
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Development of two-way onion (Allium cepa L.) hybrids is difficult due to poor seed yields on inbred female parents. Seed yield of onion is affected by inbreeding depression and the seed-production environment. A standard diallel was used to estimate combining abilities for seed yield among seven inbred onion lines. Males and hybrids differed significantly (P < 0.05) for seed yields. Combinations of relatively high-by-high seed-yielding inbred parents were not always the best combinations; combinations of medium-by-medium or medium-by-high seed yielders also produced good F1 seed yielders. For the seven inbred lines, significant correlations (P < 0.05) were observed between mean seed yield per bulb and scape height. Parent-offspring regressions revealed no significant relationship between seed yields of randomly selected, open-pollinated bulbs and their S1 families. Results indicate that relative seed yields of individual bulbs after self-pollination cannot be used to predict seed yields of progeny families. However, the seed yield of inbred lines of onion may reflect the potential seed yield of F1 male-sterile lines.
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Smith, Malcolm W., Mark D. Hoult, and Jeremy D. Bright. "Rootstock Affects Yield, Yield Efficiency, and Harvest Rate of 'Kensington Pride' Mango." HortScience 38, no. 2 (April 2003): 273–76. http://dx.doi.org/10.21273/hortsci.38.2.273.
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Low yields and high harvesting costs are long-standing problems in mango (Mangifera indica L.) cultivation. In an effort to increase productivity in the scion 'Kensington Pride' we examined the impact of nine different rootstocks over a 10-year period. Rootstock effects on fruit production were significant in most seasons, and cumulative yields (nine seasons of cropping) for the best treatment ('Sg. Siput') exceeded those of the poorest treatment ('Sabre') by 141%. Yield efficiencies (expressed on both a trunk cross-sectional area and canopy silhouette area basis) were also significantly affected by rootstock. Rootstock effects on yield and yield efficiency were generally consistent across seasons, despite large seasonal variations in yield. Harvest rates were also influenced by rootstock, and were poorly correlated with tree size. These results demonstrate possibilities for manipulating mango scion productivity through rootstock genotype.
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Adjebeng-Danquah, Joseph, Kwabena Acheremu, Emmanuel Boache Chamba, Issah Alidu Abukari, Ayishetu Sumaila, Richard Yaw Agyare, Isaac Kodzo Amegbor, et al. "Genotypic variability and genetic parameters for root yield, dry matter and related traits of cassava in the Guinea Savannah ecological zone of Ghana." Archives of Agriculture and Environmental Science 8, no. 3 (September 25, 2023): 310–18. http://dx.doi.org/10.26832/24566632.2023.080306.
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The aim of this study was to assess the agronomic performance and genetic parameters governing storage root yield and related traits in cassava genotypes in order to identify superior genotypes. The study involved 18 elite cassava genotypes which were arranged in a randomized complete block design with three replications and assessed for storage root yield and yield components (12 months after planting) in the Guinea savannah ecology of Ghana for three seasons. Analysis of variance indicated significant (p < 0.05) genotype and year main effects for fresh and dry root yields, dry matter content, starch yield and harvest index. Genotype × year effect was significant (p < 0.05) for fresh root yield, dry root yield and starch yield. Estimates of the variance components revealed greater genotypic influence for starch yield, fresh and dry root yields implying the potential for genetic gain with selection for these traits among the genotypes. Relatively high (69 %) broad sense heritability estimate was observed for dry storage root yield indicating the depth of genetic influence. Path coefficient analysis revealed a direct positive effect of dry matter content on dry storage root yield whilst dry storage root yield had direct positive effect on starch yield suggesting the possibility of indirect selection for starch yield through dry storage root yield. The study revealed ample genotypic variability among the cassava genotypes to warrant selection. Four genotypes, IBA 070134, IBA 419, IBA 950289 and IBA 980581 were identified for high and stable fresh and dry root yields for multilocational testing.
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Mustatfa, Shnrwe Bakir, and Rozhgar Mustafa Ahmed. "Influence of various fertilizer types on yield and component traits of black cumin." Journal of Kerbala for Agricultural Sciences 10, no. 3 (September 12, 2023): 172–83. http://dx.doi.org/10.59658/jkas.v10i3.1250.
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Two experiments were conducted in the autumn season of 2019-2020 to investigate the impact of two species belonging to the Nigella genus under various fertilization conditions. Both experiments followed the Randomized Complete Block Design (RCBD) and were replicated three times at the Qlyasan and Kanipanka location. The results of the average of both locations, it was observed that N. sativa outperformed N. arvensis in terms of seed yield, fixed oil yield and essential oil yield, achieving 607, 138, and 8 kg ha-1, respectively. Notably, when a 2% organic manure application was utilized, higher seed yield, fixed oil yield, and essential oil yield were achieved at 659, 160, and 9 kg ha-1, respectively. The most favorable outcomes of 676 kg ha-1 for seed yield, 174 kg ha-1 for fixed oil yield, and 10 kg ha-1 for essential oil yield were attained through a combination of N. sativa and the application of 2% organic manure fertilization. Comparatively, the Kanipanka location demonstrated greater results than the Qlyasan location, with seed yields of 621 kg ha-1, fixed oil yields of 137 kg ha-1, and essential oil yields of 8 kg ha-1.
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Bekele, Bewket Getachew. "Review on Yield Gap Analysis: Modeling of Achievable Yields at Farm Level." European Journal of Agriculture and Forestry Research 10, no. 2 (February 15, 2022): 21–27. http://dx.doi.org/10.37745/ejafr.2013/vol9n22127.
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In the present context, ‘model’ is expressed as a computer program that can be repeatedly run several times for computing several designed mathematical or statistical expressions (equations) governing crop growth-environment relations, given appropriate input data. The experiment station yields obtained under a rainfed situation without any nutrient deficiency mostly considered as the potential yields of rainfed crops. Actual yields are obtained by recording crop yields of farmers in the region under investigation and achievable yield is between actual and potential yield. Actual yields are compared with the potential yields to estimate yield gaps of crops for that area and others which have the same agro-ecology. Achievable yield is determined by factors like availability of moisture and nutrients, Precipitation and irrigation as input, Soil profile water holding characteristics, Plant water balance (transpiration, water uptake), Soil water balance (evaporation, infiltration, runoff, flow, drainage) and Nitrogen fertilizer applications as input, Soil nitrogen conditions, Plant nitrogen balance (uptake, fixation, mobilization), Soil nitrogen balance (mineralization, immobilization, nitrification, denitrification). Generally, modeling Achievable yield of farm depend on water and nutrient data of the area and Actual yield is determined by factors like weeds, insect pests, diseases and pollutants.
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Ferrari, Thomas E. "Use Yield Ratios to Evaluate Effects of Supplemental Pollination on Crop Production." HortScience 33, no. 3 (June 1998): 492b—492. http://dx.doi.org/10.21273/hortsci.33.3.492b.
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The environment caused large fluctuations in almond yields from year-to-year, which confounded analysis of pollination treatments performed in the field. Following the practice of supplemental pollination, there was insufficient improvement in yield to indicate that extra pollen applied to honey bees affected nut production. However, when yield for a cultivar exposed to extra pollen was compared to an untreated, reference cultivar grown in the same field, a statistically significant increase in yield was detected. Coefficients of variation for yield ratios averaged 54% lower than for yields alone in each of eight orchards examined. Converting annual yields to yield ratios mitigated the effects of the environment on analysis of production data.
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Strašil, Z., and Z. Vorlíček. "The effect of nitrogen fertilization, sowing rates and site on yields and yield components of selected varieties of safflower (Carthamus tinctorius L.)." Plant, Soil and Environment 48, No. 7 (December 21, 2011): 307–11. http://dx.doi.org/10.17221/4368-pse.
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Field trials were conducted at two sites Troubsko near Brno and Prague-Ruzyně in 1996–1999 with three varieties of safflower (Gila, CW-74, Sironaria). Three rates of nitrogen fertilization were used: N0 = no fertilization, N<sub>1</sub> = 40 kg/ha, N<sub>2</sub> = 80 kg/ha. Sowing rates were 50 and 70 germinable seeds per m2. The average values of oil content were highest in seeds of CW-74 variety (27.2%). Gila had on average the lowest oil content (24.5%). Linoleic acid was dominant in all three safflower varieties. Variation in content of linoleic acid in different years was not so high as in oil content. The highest average content of linoleic acid was found in Gila variety (81.2%), the lowest in Sironaria (77.4%). At Ruzyně average seed yield on dry basis was 2.7 t/ha and average straw yield was 7.56 t/ha. At Troubsko seed yield was 2.56 t/ha and straw yield was 3.69 t/ha (by 50% lower than at Ruzyně). The effect of year of growing and site on seed yields and on other parameters was highly significant. N fertilization increased safflower seed yield at Troubsko site only, where the dose of 40 kg/ha N increased the yield by 0.08 t/ha on average of years and the dose of 80 kg/ha N increased the seed yield by 0.2 t/ha in comparison with no nitrogen fertilization treatments. Increased N rates and especially higher plant density resulted in an increase in straw yields. Neither were thousand seed weight nor number of flower heads influenced significantly by different N rates or the above-mentioned differences in plant density.
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SARDANA, VIRENDER, and SHAMSHER SINGH NARWAL. "Influence of time of sowing and last cut for fodder on the fodder and seed yields of Egyptian clover." Journal of Agricultural Science 134, no. 3 (May 2000): 285–91. http://dx.doi.org/10.1017/s0021859699007583.
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Field investigations were conducted during the winter seasons of 1992/93 and 1993/94 to find the optimum sowing time and time of last fodder cut for the fodder and seed production of Egyptian clover (Trifolium alexandrinum L.). The delay in sowing from 1 October to 15 November decreased the green and dry fodder yields but increased the seed yields. Total green and dry fodder yields (of all cuttings) for 1 or 15 October sowings were significantly higher than the 15 November sowing in both years and 1 November sowing in 1992/93. Increase in seed yield from the 15 November sowing was greater than from the 1 and 15 October sowings. Straw yields followed similar trends. Delay in the last cut for fodder, however, increased green and dry fodder yields but decreased the seed yield. The percentage increase in dry fodder yield with each successive delay in last cut for fodder was higher than that of green fodder yield. The 11 April cutting date of fodder produced the highest green and dry fodder yields but the lowest seed yield. Two years mean data showed that the 2 March cutting date of last fodder gave the highest seed yield. It is concluded that higher seed yield of Egyptian clover can be produced by sowing on 15 November and giving the last fodder cutting on 2 March.
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Zymaroieva, A., and Y. Nykytiuk. "Agroecological drivers of winter rye (Secale cereale) yield spatio-temporal variation." Agrology 6, no. 4 (November 14, 2023): 86–91. http://dx.doi.org/10.32819/021114.
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The study of yield-limiting factors of rye, a typical European cereal, is a crucial concern today as it significantly impacts global food safety. The objecive of the study was to determine the contribution of agroecological factors, namely bioclimatic variables, soil parameters, and landscape diversity, to the variation of rye yields in the central and northern regions of Ukraine, which is one of the world’s five largest producers of this crop. A symmetric log-logistic model was used to describe the dynamics of rye yields, and the parameters of this model can be used to analyze the spatial dynamics of yields, in particular, such characteristic points of the yield model as: the lower limit of the response (the lowest yield level); the upper limit (the highest yield level); the slope of the response curve in the vicinity of the inflection point, which shows the rate of yield change over time, ED50 – the time required to reach half of the maximum yield growth. In the preliminary principal component analysis, we identified 4 climate principal components and 6 soil principal components. Landscape diversity was assessed based on the Shannon index and distance to the protected areas. The results of the regression analysis revealed a statistically significant relationship between the parameters of rye yield and the identified environmental drivers. Among the rye yield parameters, the highest sensitivity to environmental factors was the upper yield limit (70%), and the lowest was the rate of yield increase (25%). Only the highest rate of yield growth demonstrated liner dependence on the Shannon index. Among the soil factors, the most influential for rye yields was the particle size distribution and especially the sand content. The rye yield parameters were primarily influenced by the variability of the temperature regime throughout extreme periods of the year and contrast in the temperature conditions. The yield parameters of rye were contingent upon the diversity of the landscape cover. The correlation between almost all yield characteristics and landscape-ecological diversity was not linear, leading to the identification of an optimal level of diversity in natural protected areas which results in the best rye yields.
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Raza, Sohail, and Shahzad Munir. "The Impact of U.S. Quantitative Easing (QE) Announcements on Indian Government Bond Yields." Asian Journal of Economics, Business and Accounting 23, no. 19 (August 22, 2023): 179–206. http://dx.doi.org/10.9734/ajeba/2023/v23i191083.
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This study investigates the impact of U.S. Quantitative Easing (QE) announcements on Indian Treasury yields. Two outstanding channels of spillover effects on bond yields documented in the existing literature are signalingchannel and portfolio balance channel. This study decomposes Indian Treasury yields into yield expectationsand risk premia to measure spillover effects of U.S. QE announcements. The impact on yield expectationmeasures signaling effect while the impact on risk premia measures portfolio balance effect. It is observed that FOMC announcements of Federal Reserve’s Quantitative Easing (QE) policy treated as shocks to Indian government bond yields. To investigate the announcement effects on Indian government Bond yields, event study methodology is used to capture the change in the bond yields, yield expectation and risk premia of Indian bond market around that time especially during the first round of Quantitative Easing (QE1) policy announcement periods in one-day and two-day window period. To support event study results regression analysis method is implemented and found robust evidence supporting larger signaling effect than the portfolio balance effect. At last, this study uses Dynamic Nelson-Siegel (DNS) yield curve model to compute the relationship between the U.S. and Indian Bond market. DNS model involves two-step estimation using VAR regression on Indian government bond yields with U.S. 10-year Treasury yield changes as an exogenous variable. The statistical result of DNS estimation shows that U.S. 10-year Treasury yield change affects the Indian long-term bond yield during the financial crisis period.
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Trueblood, Michael A., and Carlos Arnade. "Crop Yield Convergence: How Russia's Yield Performance Has Compared to Global Yield Leaders." Comparative Economic Studies 43, no. 2 (July 2001): 59–81. http://dx.doi.org/10.1057/ces.2001.8.
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Chaudhari, Pravin Nagibhai, Pratik Sanjaybhai Kapadiya, Mahesh Ramnivas Gadariya, Pranav Mayankbhai Gamit, and Bhagavanji Dayabhai Savaliya. "Test-day and other milk recording options for prediction of lactation milk yield in Jaffarabadi (Bubalus bubalis) buffaloes." Buffalo Bulletin 42, no. 3 (September 30, 2023): 397. http://dx.doi.org/10.56825/bufbu.2023.4234646.
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Generally, standard lactation milk yield is predicted based on test-day records collected at monthly intervals. Test-day milk production at different time intervals other than monthly intervals can be used to predict lactation milk yield of field bovines in field conditions. With the same possibility, this study was carried out to predict lactation milk yield in Jaffarabadi buffaloes from various test-day milk yield data retrieved for different time intervals. A total of 1,15,339 daily milk yield records in 176 lactations of 1st to 6th parity of 30 Jaffarabadi buffaloes lactating at the Cattle Breeding Farm, Kamdhenu University, Junagadh, Gujarat over a period of 28 years (1991 to 2018) were used for the study. Single monthly test-day milk yield recorded on 125th, 155th or 185th day i.e., 5th, 6th and 7th monthly test day yield alone provided only 50% reliability in determining the standard lactation milk yield. Daily peak yield alone was also found to be a poor predictor for lactation yield. Prediction equations using combination of consecutive two monthly test day yields from 4th to 10th monthly test day were found reliable source for prediction of lactation milk yield providing accuracy up to 82.19% whereas, daily peak yield in combination with single monthly test day yield at mid and late lactation was also predicted lactation milk yield with accuracies up to 72.23%. Milk production recorded at weekly interval could also be used to approximate milk production using the equation 15.35+6.91 × Sum of all weekly test-day yields, with precision of 98.93% or milk production recorded at fortnightly interval by the equation 18.04+14.65 × Sum of fortnightly test-day yields, with precision of 97.14%.
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Qiao, Shengchao, Han Wang, I. Colin Prentice, and Sandy P. Harrison. "Optimality-based modelling of climate impacts on global potential wheat yield." Environmental Research Letters 16, no. 11 (October 22, 2021): 114013. http://dx.doi.org/10.1088/1748-9326/ac2e38.
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Abstract Evaluation of potential crop yields is important for global food security assessment because it represents the biophysical ‘ceiling’ determined by variety, climate and ambient CO2. Statistical approaches have limitations when assessing future potential yields, while large differences between results obtained using process-based models reflect uncertainties in model parameterisations. Here we simulate the potential yield of wheat across the present-day wheat-growing areas, using a new global model that couples a parameter-sparse, optimality-based representation of gross primary production (GPP) to empirical functions relating GPP, biomass production and yield. The model reconciles the transparency and parsimony of statistical models with a mechanistic grounding in the standard model of C3 photosynthesis, and seamlessly integrates photosynthetic acclimation and CO2 fertilization effects. The model accurately predicted the CO2 response observed in FACE experiments, and captured the magnitude and spatial pattern of EARTHSTAT ‘attainable yield’ data in 2000 CE better than process-based models in ISIMIP. Global simulations of potential yield during 1981–2016 were analysed in parallel with global historical data on actual yield, in order to test the hypothesis that environmental effects on modelled potential yields would also be shown in observed actual yields. Higher temperatures are thereby shown to have negatively affected (potential and actual) yields over much of the world. Greater solar radiation is associated with higher yields in humid regions, but lower yields in semi-arid regions. Greater precipitation is associated with higher yields in semi-arid regions. The effect of rising CO2 is reflected in increasing actual yield, but trends in actual yield are stronger than the CO2 effect in many regions, presumably because they also include effects of crop breeding and improved management. We present this hybrid modelling approach as a useful addition to the toolkit for assessing global environmental change impacts on the growth and yield of arable crops.
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Anderson, WK. "Some relationships between plant population, yield components and grain yield of wheat in a Mediterranean environment." Australian Journal of Agricultural Research 37, no. 3 (1986): 219. http://dx.doi.org/10.1071/ar9860219.
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Eight spring bread wheat cultivars (Triticum aestivum L.), differing widely in their nominal yield component characteristics, were tested under rain-fed conditions for three years at sowing densities ranging from 50 to 800 seeds m-2. The objectives of the experiments were to estimate the relationship between grain yield and particular yield components, the expression of plant type (yield components) in relation to plant density, and the plant population x cultivar interaction for grain yield over a range of seasons in a given environment. The 'optimum' plant population (at maximum grain yield) varied over 30-220 plants m-2, depending on season and cultivar. In general, variation in the 'optimum' population was greater between seasons for a given cultivar than between cultivars within seasons. The relationship between grain yield and yield components was examined at the 'optimum' population rather than at an arbitrary population at which grain yield may have been suboptimal for some cultivars or seasons. Grain yields at the optimum populations for the various cultivar x season combinations were positively related to culms m-2, spikes m-2 and seeds m-2. They were not clearly related to culm mortality (%). When averaged across seasons, cultivar grain yields were positively related to harvest index, but the general relationship was not so clear when seasons and cultivars were examined individually. Spike size (seeds spike-I or spike weight) and seed size were also not clearly related to grain yield at the 'optimum' population, and it was thus postulated that the production and survival of large numbers of culms, which in turn led to large numbers of seeds per unit area, were the source of large grain yields. Some interactions were found between yield components and plant population for some cultivars that could have implications for plant breeders selecting at low plant densities. The implications for crop ideotypes of the individual plant characters at the 'optimum' population are also discussed. Interactions between cultivars and plant populations implied that some cultivars required different populations to achieve maximum yields in some seasons. There was a tendency for larger yields to be achieved from cultivar x season combinations where the optimum population was larger, which suggested that commercial seed rates should be re-examined when changes to plant types or yield levels are made.
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Yang, Rui, Matthew Tom Harrison, and Xiaoyan Wang. "Current State and Limiting Factors of Wheat Yield at the Farm Level in Hubei Province." Agronomy 13, no. 8 (July 31, 2023): 2043. http://dx.doi.org/10.3390/agronomy13082043.
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Longitudinal wheat yields in China have declined in recent times due to climate change, more frequent natural disasters, and suboptimal agronomic management. To date, it has been unclear which factors have predominated yield penalties realised hitherto in Hubei Province. This study aimed to identify key factors limiting wheat production across systems and agroecological regions, and provide a basis for increasing crop production while engendering food security. Survey data from 791 households in Hubei Province were analyzed using descriptive statistics and logistic regression. Significant spatial heterogeneity in average wheat yields was observed, with the Jianghan Plain region having significantly lower yields compared with the northwest region (yield gap: 1125 kg·hm−2). Dryland wheat had higher average yields than rice-rotation wheat (yield gap: 134 to 575 kg·hm−2). Socioeconomic factors, cultivation management measures, and environmental factors contributed differently to yield differences. Input costs and economic benefits were key social factors influencing wheat production. Variation in management were mainly attributed to planting methods, while soil fertility and climatic factors limited yields in some regions. In the northwest, low soil fertility and susceptibility to drought and high temperatures had greater influence on yields. In the Jianghan Plain, soil waterlogging and erosion were key challenges. Waterlogging increased the probability of low yields by 8.6 times, while severe soil erosion increased probability of yield loss by a factor of almost five. Low-yield farms in the Jianghan Plain were 21% higher than those in the northwest. Extreme weather events also contributed to low yields in the Jianghan Plain. We note significant potential for increasing farm-level wheat production in Hubei Province, with large existing differences across agro-ecological regions and planting modes. Differences in cultivation practices was a major driving factor of yield gaps between planting modes, while soil fertility and meteorological disasters drive regional yield differences. These results have implications for those aspiring to narrow the yield gap across regions and increase production of cereal crops.
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White, Ethel M. "Straw and grain production in spring barley cultivars." Journal of Agricultural Science 108, no. 2 (April 1987): 293–98. http://dx.doi.org/10.1017/s0021859600079284.
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SummaryGrain and straw yields of a range of spring barley cultivars were assessed in field experiments conducted from 1981 to 1983 in Northern Ireland. Mean straw yields varied between 2·75 t/ha in Inga and 1·94 t/ha in Golden Promise over the 3-year period. Both grain and straw yields varied from year to year, with straw production being more consistent for individual cultivars than grain yield. High grain yields were not associated with high straw yields, straw to grain ratios varying between 0·72 in Midas and 0·51 in Corgi. Neither grain yield nor straw length were good predictors of straw yield of cultivars. The role for and assessment of straw yield in cultivar evaluation is discussed.
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Rook, A. J., J. D. Sutton, and J. France. "Prediction of the yields of milk constituents in dairy cows offered silage ad libitum and concentrates at a flat rate." Animal Science 54, no. 3 (June 1992): 313–22. http://dx.doi.org/10.1017/s0003356100020766.
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AbstractIndividually recorded milk yields, yields and concentrations of milk components, food intakes and live weights of multiparous dairy cows given silage ad libitum and concentrates at a flat rate in weeks 4 to 13 of lactation and data for silage and concentrate composition from experiments conducted at four sites, were used to obtain simple correlations and multiple linear regressions of yields and concentrations of milk constituents on other variables.Simple correlations between yields and concentrations and other variables were low. Yield terms were most highly correlated with intake terms. Milk fat concentration was most highly correlated with silage fibre concentration. Milk protein concentration was most highly correlated with digestible energy intake. The best multiple regression models including time effects accounted proportionately for 0·35 of the variation in fat yield, 0·51 in protein yield, 0·55 in lactose yield, 0·39 in total milk yield, 0·19 in fat concentration, 043 in protein concentration and 0·19 in lactose concentration. Most of these models included terms for silage intake and cow live weight which are not generally available on farms. More practical models including fewer independent variates were therefore produced. These models accounted proportionately for 0·33 of the variation in fat yield, 048 in protein yield, 0·50 in lactose yield, 0·32 in total milk yield, 0·19 in fat concentration, 0·40 in protein concentration and 0·17 in lactose concentration.
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Chu, Lin, Chong Huang, Qingsheng Liu, Chongfa Cai, and Gaohuan Liu. "Spatial Heterogeneity of Winter Wheat Yield and Its Determinants in the Yellow River Delta, China." Sustainability 12, no. 1 (December 23, 2019): 135. http://dx.doi.org/10.3390/su12010135.
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Understanding spatial differences of crop yields and quantitatively exploring the relationship between crop yields and influencing factors are of great significance in increasing regional crop yields, promoting sustainable development of regional agriculture and ensuring regional food security. This study investigates spatial heterogeneity of winter wheat yield and its determinants in the Yellow River Delta (YRD) region. The spatial pattern of winter wheat in 2015 was mapped through time series similarity analysis. Winter wheat yield was estimated by integrating phenological information into yield model, and cross-validation was performed using actual yield data. The geographical detector method was used to analyze determinants influencing winter wheat yield. This study concluded that the overall classification accuracy for winter wheat is 88.09%. The estimated yield agreed with actual yield, with R2 value of 0.74 and root mean square error (RMSE) of 1.02 t ha−1. Cumulative temperature, soil salinity and their interactions were key determinants affecting winter wheat yield. Several measures are recommended to ensure sustainable crop production in the YRD region, including improving irrigation and drainage systems to reduce soil salinity, selecting salt-tolerant winter wheat varieties, and improving agronomy techniques to extend effective cumulative temperature.
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M, Roja, Gumma M. K., and Reddy M. D. "Evaluation of the DSSAT model for maize yield estimate under different irrigation regimes." Ecology, Environment and Conservation 29 (2023): S250—S254. http://dx.doi.org/10.53550/eec.2023.v29i01s.039.
Full textAbstract:
This study has been designed to evaluate the performance of DSSAT model for yield estimation of maize under different irrigation levels and methods. Experiment has been conducted during rabi 2015-16 in water Technology Centre, Rajendranagar. Observed yields were compared with the models simulated yields. From the results it has been revealed that drip irrigation scheduled at 1.0 Epan produced higher growth, yield, and yield attributes than the other surface and drip irrigation treatments, while surface irrigation scheduled at 0.6 IW/CPE produced lower growth, yield, and yield attributes than the other treatments. Model results were also in quite agreement with the observed results where the maximum and minimum prediction errors in grain yields with DSSAT was 0.40 % and 14.86 %. Correlation coefficient of 0.98 and 0.97 was observed for water productivity and grain yield. From this study it can be concluded that DSSAT can be used for yield estimation in maize under different irrigation regimes with minimal error. Model should be used after proper calibration for better results.
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Pu, Luoman, Junnan Jiang, Menglu Ma, and Duan Huang. "Gaps between Rice Actual and Potential Yields Based on the VPM and GAEZ Models in Heilongjiang Province, China." Agriculture 14, no. 2 (February 8, 2024): 277. http://dx.doi.org/10.3390/agriculture14020277.
Full textAbstract:
Heilongjiang Province is a significant region for grain production and serves as a crucial commodity grain production base in China. In recent years, due to the threat of declining cropland quality and quantity, coupled with the increasingly prominent demand for grain, there is an urgent need to enhance rice yields in Heilongjiang Province. It is imperative to accurately identify the gaps between actual and potential grain yields and effectively implement yield-enhancing measures in regions with significant yield gaps. This study aimed to determine the rice reproductive periods of Heilongjiang Province for 2000, 2010, and 2020, estimate the rice actual yields using the Vegetation Photosynthesis Model (VPM), simulate the rice potential yields based on the Global Agro-Ecological Zones (GAEZ) Model, and then identify the rice yield gaps at the pixel level by calculating the rice absolute yield gap (AYG) and relative yield gap (RYG). Additionally, yield-enhancing measures were proposed for regions with significant yield gaps. The results were as follows. (1) The rice reproductive periods of Heilongjiang Province for 2000, 2010, and 2020 were determined as days 153~249, days 145~249, and days 137~249. (2) The mean rice actual yield and potential yields decreased by 1222 and 5941 kg ha−1 during the 2000–2020 period, respectively, and the total actual and potential production increased by 3.75 and 1.70 million tons in Heilongjiang Province, respectively. (3) The rice AYG and RYG in the Sanjiang Plain region, such as Jixi City, Hegang City, and Jiamusi City were relatively large compared to other regions for the three years, and the rice yield gaps continued to decrease during the 2000–2020 period. (4) With regard to the Sanjiang Plain region with a large rice yield gap, this study proposes measures to narrow the rice yield gap by establishing ecological protection forests on cropland, transforming low- and middle-yielding fields, increasing agricultural science and technology inputs, selecting better rice cultivars, etc., which are important for ensuring food security.
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Cai, Chengzhi, Hongyan Yang, Lin Zhang, and Wenfang Cao. "Potential Yield of World Rice under Global Warming Based on the ARIMA-TR Model." Atmosphere 13, no. 8 (August 22, 2022): 1336. http://dx.doi.org/10.3390/atmos13081336.
Full textAbstract:
As one of two most important cereals in the world, and with the continuous increase in population and demand for food consumption worldwide, rice has been attracting researchers’ attention for improving its potential yield in the future, particularly as it relates to climate change. However, what will be the potential limit of world rice yield in the future, and how does global warming affect the yield of world rice? Therefore, analyzing the potential yield of world rice affected by global warming is of great significance to direct crop production worldwide in the future. However, by far, most modeled estimations of rice yield are based on the principle of production function from static biological dimension and at local or regional levels, whereas few are based on a time series model from a dynamic evolutionary angle and on global scale. Thus, in this paper, both average and top (national) yields of world rice by 2030 are projected creatively using the Auto-regressive Integrated Moving Average and Trend Regression (ARIMA-TR) model and based on historic yields since 1961; in addition, the impact of global warming on the yields of world rice is analyzed using a binary regression model in which global mean temperature is treated as the independent variable whereas the yield is expressed as the dependent variable. Our study concludes that between 2021 and 2030, the average yield of world rice is projected to be from 4835 kg/ha to 5195 kg/ha, the top yield from 10,127 kg/ha to 10,269 kg/ha, or the average yield ranging from 47.74% to 50.59% of the top yield. From 1961 to 2020, through to2030, global warming will exert a negative impact on the average yield of world rice less than that of the top yield, which partly drives the gap between these two yields and gradually narrowed; for world rice by 2030, the opportunities for improving global production should be dependent on both high and low yield countries as the average yield is approaching the turning point of an S-shaped curve in the long-term trend. These insights provide the academic circle with innovative comprehension of world rice yield and its biological evolution for global food security relating to global warming in the future.