scholarly journals Plant Yield Efficiency by Homeostasis as Selection Tool at Ultra-Low Density. A Comparative Study with Common Stability Measures in Maize

Agronomy ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 1203
Author(s):  
Evaggelia Sinapidou ◽  
Chrysanthi Pankou ◽  
Fotakis Gekas ◽  
Iosif Sistanis ◽  
Constantinos Tzantarmas ◽  
...  
Keyword(s):  
Plant Density ◽  
Phenotypic Expression ◽  
Yield Potential ◽  
Low Density ◽  
Potential Yield ◽  
Plant Yield ◽  
Yield Efficiency ◽  
Parametric Statistics ◽  
Resource Deficit ◽  
Field Experimentation

The study pertains to field experimentation testing seven maize (Zea mays L.) hybrids at four densities, across five locations under normal (NIR) and low-input (LIR) regimes. The main objective was to assess the prognostic value of plant yield efficiency by homeostasis (PYEH) for breeding purposes at ultra-low plant density to predict hybrid yield potential and stability. PYEH comprises plant yield efficiency (PYE) that reflects the ability of individual plants to exploit resources, and plant yield homeostasis (PYH) that indicates the crop’s ability to evade acquired plant-to-plant variability. The same hybrids were also evaluated for stability by commonly used parametric and non-parametric statistics based on data at low (LCD) and high crop densities (HCD). Hybrid stability focused on potential yield loss due to erratic optimum density (OD). Most methods produced conflicting results regarding hybrid ranking for yield and stability especially at LCD. In contrast, PYEH consistently highlighted high-yielding and stable hybrids, potentially able to reach the attainable crop yield (ACY) inter-seasonally irrespective of crop spacing. Low density is common practice under resource-deficit conditions, so crop adaptation to crop spacing is a viable option to overcome erratic OD that constitutes a root source of crop instability in rainfed maize. The results were further supportive of breeding at ultra-low density to facilitate the identification and selection of superior genotypes, since such conditions promote phenotypic expression and differentiation, and ensure repeatability across diverse environments.

scholarly journals Prediction of potential and attainable yield of wheat : A case study on yield gap

MAUSAM ◽  
2022 ◽  
Vol 53 (1) ◽  
pp. 45-52
Author(s):  
R. K. MALL ◽  
M. K. SRIVASTAVA
Keyword(s):  
Simulation Models ◽  
Yield Potential ◽  
Wheat Crop ◽  
Yield Gap ◽  
Potential Yield ◽  
Potential Productivity ◽  
Field Experimentation ◽  
Attainable Yield

This study reports the role of field experimentation and system simulation in better quantifying the productivity of wheat crop, and examine how knowledge on potential productivity can improve the efficiency of the production system. When knowledge from field experimentation is utilised into crop weather simulation models, gap between actual, attainable and potential yield for a given environment can be determined and opportunities for yield improvement can be assessed. Results show that while actual district average yields show increasing trend, decreasing trend is noticed in potential and attainable yield. While the total and management yield gap is decreasing over time, research yield gap does not show any trend, it is nearly stagnant from early eighties to late nineties. The study reported here presents the advantage of simulation models to determine the yield gap against a variable annual yield potential for a agro-climatic region.

The effect of improved potential yield per plant on crop yield potential and optimum plant density in maize hybrids

2001 ◽  
Vol 137 (3) ◽  
pp. 299-305 ◽  
Author(s):  
I. S. TOKATLIDIS
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Crop Yield ◽  
Plant Density ◽  
Linear Regression Analysis ◽  
Yield Potential ◽  
Technological Education ◽  
Potential Yield ◽  
Natural Logarithm ◽  
Plant Densities

Honeycomb selection in the F2 generation of maize (Zea mays L.) hybrid PR 3183, based on line performance per se in the absence of competition, led to recycled hybrids with improved potential yield per plant (mean yield per plant in the absence of competition). In the present study six S6×S6 recycled hybrids and two commercial single-cross hybrids (PR 3183 and B73×Mo17) were tested at three plant densities (25000, 41667 and 83333 plants/ha), in two locations (Technological Education Institute farm of Florina, Greece and University farm of Thessaloniki, Greece), for 2 years (1998, 1999). The study was undertaken to assess indirectly the potential yield per plant (p), the crop yield potential (Ymax), and the optimum plant density (Dopt) of the hybrids. Estimate of p and Ymax were obtained through linear regression analysis of yield per plant (Yp) on plant density (D), expressed by the equation Yp = p−qD, with Ymax being equal to (1/4)p2q−1. Optimum plant density was assessed through linear regression analysis of natural logarithm of yield per plant on plant density, expressed by the equation ln(Yp) = α−bD, with Dopt being equal to 1/b. The recycled hybrids had higher estimated potential yield per plant (p), than the two check hybrids, with p values being positively correlated with yield per plant of hybrids obtained experimentally in the absence of competition. Results indicated that the higher potential yield per plant decreases the optimum plant density, and renders the hybrids less density-dependent.

Evaluation of castorbean samples by economically - valuable traits

2018 ◽  
pp. 39-48
Keyword(s):  
Ricinoleic Acid ◽  
Castor Bean ◽  
Castor Oil ◽  
Oil Content ◽  
Climatic Conditions ◽  
Second Order ◽  
Yield Potential ◽  
Technological Parameters ◽  
Potential Yield ◽  
Ricinolic Acid

Castor oil (Ricinus communus L.) is an important commercial product. The climatic conditions of Ukraine determine the possibility of growing the castor as an annual crop. At the Institute of Oilseeds NAAS studied castor collection. The aim of the work was the selection of the most promising samples of castor oil, combining a large yield potential in a narrow range of vertical distribution for optimal technological parameters of mechanical harvesting with a high content of oil in seeds and ricinolic acid in oil. In the experience of 2015-2016, the manifestation of morphological features of 17 castor bean samples was studied. The height of plants, individual samples among themselves differed more than twice. Long-brush samples of ЕР118, К374, М203, К159 are distinguished on the basis of the length of the brush. The shortest brush was observed in sample K1008. The length of the productive brush in the studied samples is from 10.7 to 32.9 cm. Most castor bean samples under favorable conditions form brushes of the second and higher orders. According to this parameter, samples of Ep118 and selection No. 38 with four inflorescences of the second order are of the greatest interest. The largest brushes of the second order are similar in size to the brushes of the first order were observed in the samples: К1127, К810, К153. The adaptability of harvesting castor beads requires that the brushes of the first and second order coincide in height with each other, since the harvester can take a maximum of 60 cm. For the sum of the productive brushes of the first and second orders, the greatest potential yield will be provided by samples K159 and K1127. Among the studied collection stands out the small seed sample K159 and the large seed samples - PRL41 and K80. The average oil content in the seeds of the collection was from 52 to 61.4%. Sample38 had the highest oil content. The content of ricinolic acid in the collection was from 70.9 to 82.9%. Samples were isolated: К134, К1008, PRL41, К430 with the content of ricinoleic acid more than 80%. The results of the study of all parameters make it possible to isolate valuable technological samples. Sample K1064 with a high technological potential of productivity, with a seed oil content of 57.2%, has a not very high content of ricinoleic acid of 74.3%. Sample K1127 with an oil content of 58.6%, a mass of 1000 seeds of 265 g, a high potential of productive brushes has a wide variation in the arrangement of brushes. Sample K134 with a oil content of 57.1%, ricinoleic acid content of 80.7% has small second-order brushes and can be used as a single-cysts in a thicker seeding.

Effect of plant density and vegetative branch retention on within-plant yield distribution and maturity performance of cotton

2010 ◽  
Vol 18 (4) ◽  
pp. 792-798 ◽  
Author(s):  
He-Zhong DONG ◽  
Zhen-Huai LI ◽  
Zhen LUO ◽  
He-Quan LU ◽  
Wei TANG ◽  
...  
Keyword(s):  
Plant Density ◽  
Plant Yield ◽  
Yield Distribution

scholarly journals A Review of Industrial Crop Yield Performances on Unfavorable Soil Types

Agronomy ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 2382
Author(s):  
Jana Reinhardt ◽  
Pia Hilgert ◽  
Moritz Von Cossel
Keyword(s):  
Agricultural Land ◽  
Field Trials ◽  
Yield Potential ◽  
Soil Types ◽  
Potential Yield ◽  
Indirect Land Use Change ◽  
Industrial Crop ◽  
Large Yield ◽  
Marginal Agricultural Land ◽  
The Impact

Industrial crop cultivation on marginal agricultural land limits indirect land-use change effects that pose a threat to food security. This review compiles results from 91 published crop-specific field trial datasets spanning 12 relevant industrial crops and discusses their suitability for cultivation on unfavorable soil types (USTs). It was shown that the perennial species Miscanthus (Miscanthus Andersson) and reed canary grass (Phalaris arundinacea L.) performed well on USTs with both high clay and/or high sand contents. Information on stoniness (particles sizes > 2 mm), where mentioned, was limited. It was found to have only a small impact on biological yield potential, though it was not possible to assess the impact on mechanization as would be used at a commercial scale. For soils with extreme clay or sand contents, half of the crops showed moderate suitability. The large yield variations within and between crops revealed large knowledge gaps in the combined effects of crop type and agronomy on USTs. Therefore, more field trials are needed on diverse USTs in different climates with better equipment and more consistent measurements to improve the accuracy of potential yield predictions spatially and temporally. Additionally, larger trials are needed to optimize cultivation and harvesting.

scholarly journals Model Simulasi dan Visualisasi Prediksi Potensi Hasil dan Produksi Kedelai di Jawa Timur

2016 ◽  
Vol 34 (3) ◽  
pp. 195
Author(s):  
Bambang S. Koentjoro ◽  
Imas S. Sitanggang ◽  
Abdul Karim Makarim
Keyword(s):  
Simulation Model ◽  
Systems Approach ◽  
Yield Potential ◽  
Soybean Plant ◽  
Climatic Data ◽  
Observation Data ◽  
Potential Yield ◽  
Soybean Yield ◽  
Soybean Production ◽  
Growth Simulator

<p>The prediction of national soybean yield and production could be improved its accuracy by integrating a simulation model and Geographic Information Systems (GIS). The objective of this research was to integrate a simulation model with a GIS, to predict the potential yield and production of soybean in the soybean production centers of East Java. This study was conducted from December 2013 till May 2014. The approach used in this study was a systems approach using a simulation model as solution to the problem. The model is SUCROS.SIM (Simple Universal Crops Growth Simulator), which was written using Powersim software and Spreadsheet in order to be fully integrated with GIS. The initial phase of the integration process between SUCROS.SIM and GIS are as follows (a) model validation, using input data of soybean plant assimilate partitioning, (b) climatic data (solar radiation, maximum and minimum temperatures) collected from the climatological station (BMKG) Karangploso Malang and (c) observation data of soybean yields of two varieties (Wilis and Argomulyo) at Muneng Experiment Station. It was found that the coefficients of determination of simulation model of soybean yield potential (R2) range from 0.945-0.992 and RMSE (Root Mean Square Error) values range from 0.11 to 0.25 t/ha. The average of soybean yield potential and production in 2012 at soybean production centers of East Java were 1.94 t/ha and 293,459 ton, respectively. The conclusion is SUCROS.SIM valid to be integrated with GIS.</p>

scholarly journals PENENTUAN WAKTU TANAM PADI SAWAH DI KABUPATEN SANGIHE DENGAN MENGGUNAKAN MODEL SIMULASI SHIERARY RICE

EUGENIA ◽  
2015 ◽  
Vol 21 (3) ◽  
Author(s):  
Farida Fattah ◽  
J. E.X. Rogi ◽  
Mariam M. Toding
Keyword(s):  
Cost Savings ◽  
Simulation Models ◽  
Field Capacity ◽  
Paddy Rice ◽  
Yield Potential ◽  
Potential Yield ◽  
Planting Time ◽  
The North ◽  
Humidity Field

ABSTRACT   Decline in rice production in Sangihe Island partly due to climate change and the implementation of a less precise planting time. Rice Shierary  model was used to predict the timing of planting paddy and has advantages in time and cost savings. This study aims to determine the exact time of planting in paddy rice crops in the district of South Manganitu, North Tabukan and Tamako, as well as to determine whether the results of the simulation model Shierary Rice together with the results obtained from the Central Bureau of Statistic Sangihe Islands. Input model consists of solar radiation, rainfall, temperature and humidity, field capacity, permanent wilting point, varieties, irrigation, nitrogen fertilization, longitude and latitude of the study area. While the output was paddy rice yield potential. It can be concluded that (a) the appropriate planting time of paddy in the South Manganitu namely in June with a potential yield of 4.25 tonha-1 and March with a potential yield of 3.88 tonha-1. (b) the appropriate planting time of paddy in the  North Tabukan namely in June with a potential yield of 4.27 tonha-1 and March with a potential yield of 3.62 tonha-1. (c) the appropriate planting time of paddy in Tamako ie in March with a potential yield of 3.58 tonha-1 and February with a potential yield of 3.28 tonha-1. (d) the yield of rice field paddy with the determination of planting time by using the model of Shierary Rice nearing/line with productivity results which obtained by the Central Statistics Agency (BPS) Sangihe Islands. Keywords: planting, paddy, simulation models, Shierary Rice

The effect of plant spacing, nitrogen fertilizer and irrigation on the appearance of symptoms and spread of virus yellows in sugar-beet crops

1974 ◽  
Vol 82 (1) ◽  
pp. 53-60 ◽  
Author(s):  
G. D. Heathcote
Keyword(s):  
Sugar Beet ◽  
Plant Density ◽  
N Fertilizer ◽  
Growth And Yield ◽  
Plant Spacing ◽  
Virus Diseases ◽  
Potential Yield ◽  
Virus Incidence ◽  
Beet Yellows Virus ◽  
Yellowing Virus

SUMMARYSatisfactory comparisons of the incidence of virus yellows in sugar-beet fields or experimental plots with different amounts of N fertilizer can be made from visual symptoms early in the growing season, but not later because dressings of N fertilizer may then mask or delay the appearance of symptoms. Sugar-beet plants in the field infected with beet mild yellowing virus (BMYV) are less likely to show symptoms than those with beet yellows virus (BYV), and plants with BMYV in the glasshouse often fail to show clear symptoms.Crop yield will be affected by the spread of viruses and colonization of plants by aphids, which in turn are affected by such factors as plant density, nitrogen supply and irrigation. The presence or absence of virus diseases and of aphids should therefore be considered during studies on the effects of these agronomic factors on the growth and yield of sugar beet. Where ample rather than little N fertilizer is used a small increase in the percentage of plants infected with yellows can be expected, and aphids will be more numerous, if plants are not treated with insecticide. Irrigation may also increase yellows incidence (e.g. from 16% to 20% of plants at Broom's Barn in 1967), but any loss of potential yield from increased virus incidence will be small compared with that gained from the use of fertilizer or irrigation. However, plant density can appreciably affect yellows incidence. For example, at Broom's Barn in 1972, 51% of plants in crops with 17500 plants/ha contracted BMYV but only 15 % of plants in crops with 126500 plants/ha. The less dense crop lost 3–4% more of its potential yield due to yellows than the dense crop; this represents a difference due to virus of about 0·25 t sugar/ha.

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