scholarly journals Definition of Optimal Maize Seeding Rates Based on the Potential Yield of Management Zones

Agriculture ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 911
Author(s):  
Adriano Adelcino Anselmi ◽  
José Paulo Molin ◽  
Helizani Couto Bazame ◽  
Lucas de Paula Corrêdo
Keyword(s):  
Low Cost ◽  
Plant Population ◽  
Yield Potential ◽  
Specific Yield ◽  
Population Densities ◽  
Potential Yield ◽  
Site Specific ◽  
Management Zones ◽  
Soil Attributes ◽  
Maize Hybrids

The decision on crop population density should be a function of biotic and abiotic field parameters and optimize the site-specific yield potential, which can be a real challenge for farmers. The objective of this study was to investigate the yield of maize hybrids subjected to variable rate seeding (VRS) and in differentiated management zones (MZs). The experiment was conducted between 2013 and 2015 in a commercial field in the Central-West region of Brazil. First, MZ were delineated using the K-means algorithm with layers involving soil electrical conductivity, yield maps from previous years, and elevation. Seven maize hybrids at five seeding rates were evaluated in the context of each MZ and the cause-and-effect relationship with soil attributes was investigated. Optimal yields were obtained for crop population densities between 70,000 plants ha−1 and 80,000 plants ha−1. Hybrids which perform well under higher densities are key in achieving positive results using VRS. The plant population densities that resulted in maximum yields were obtained for densities at least 27% higher than the recommended seeding rates. The yield variance between MZs can be explained by the variance in soil attributes, while the yield variance within MZs can be explained by the variance in plant population densities. The study shows that on-farm experimentation can be key for obtaining information concerning yield potential. The management by VRS in different MZs is a low-cost technique that can reduce input application costs and optimize yield according to the site-specific potential of the field.

scholarly journals Balanced nutrient requirements for maize in the Northern Nigerian Savanna: Parameterization and validation of QUEFTS model

2019 ◽  
Author(s):  
Bello M. Shehu ◽  
Bassam A. Lawan ◽  
Jibrin M. Jibrin ◽  
Alpha Y. Kamara ◽  
Ibrahim B. Mohammed ◽  
...  
Keyword(s):  
Nutrient Uptake ◽  
Yield Potential ◽  
Nutrient Requirements ◽  
Potential Yield ◽  
Site Specific ◽  
Ecological Zones ◽  
Fertilizer Recommendations ◽  
Maize Grain ◽  
Nigerian Savanna ◽  
Agro Ecological Zones

AbstractEstablishing balanced nutrient requirements for maize (Zea mays L.) in the Northern Nigerian Savanna is paramount to develop site-specific fertilizer recommendations to increase maize yield, profits of farmers and avoid negative environmental impacts of fertilizer use. The model QUEFTS (QUantitative Evaluation of Fertility of Tropical Soils) was used to estimate balanced nitrogen (N), phosphorus (P) and potassium (K) requirements for maize production in the Northern Nigerian Savanna. Data from on-farm nutrient omission trials conducted in 2015 and 2016 rainy seasons in two agro-ecological zones in the Northern Nigerian Savanna (i.e. Northern Guinea Savanna “NGS” and Sudan Savanna “SS”) were used to parameterize and validate the QUEFTS model. The relations between indigenous soil N, P, and K supply and soil properties were not well described with the QUEFTS default equations and consequently new and better fitting equations were derived. The average fertilizer recovery fractions of N, P and K in the NGS were generally comparable with the QUEFTS default values, but lower recovery fractions of these nutrients were observed in the SS. The parameters of maximum accumulation (a) and dilution (d) in kg grain per kg nutrient for the QUEFTS model obtained were respectively 35 and 79 for N, 200 and 527 for P and 25 and 117 for K in the NGS zone and 32 and 79 for N, 164 and 528 for P and 24 and 136 for K in the SS zone. The model predicted a linear relationship between grain yield and above-ground nutrient uptake until yield reached about 50 to 60% of the yield potential. When the yield target reached 60% of the potential yield (i.e. 6.0 tonnes per hectare), the model showed above-ground nutrient uptake of 19.4, 3.3 and 23.0 kg N, P, and K, respectively, per one tonne of maize grain in the NGS, and 17.3, 5.3 and 26.2 kg N, P and K, respectively, per one tonne of maize grain in the SS. These results suggest an average NPK ratio in the plant dry matter of about 5.9:1:7.0 for maize in the NGS and 3.3:1:4.9 for maize in the SS. There was a close agreement between observed and parameterized QUEFTS predicted yields across the two agro-ecological zones (R2 = 0.70 for the NGS and 0.86 for the SS). We concluded that the QUEFTS model can be used for balanced nutrient requirement estimations and development of site-specific fertilizer recommendations for maize intensification in the Northern Nigerian Savanna.

scholarly journals OpenWeedLocator (OWL): an open-source, low-cost device for fallow weed detection

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Guy Coleman ◽  
William Salter ◽  
Michael Walsh
Keyword(s):  
Open Source ◽  
Weed Control ◽  
Technology Development ◽  
Low Cost ◽  
Yield Potential ◽  
Low Density ◽  
Weed Detection ◽  
Site Specific ◽  
South Wales ◽  
Control Community

AbstractThe use of a fallow phase is an important tool for maximizing crop yield potential in moisture limited agricultural environments, with a focus on removing weeds to optimize fallow efficiency. Repeated whole field herbicide treatments to control low-density weed populations is expensive and wasteful. Site-specific herbicide applications to low-density fallow weed populations is currently facilitated by proprietary, sensor-based spray booms. The use of image analysis for fallow weed detection is an opportunity to develop a system with potential for in-crop weed recognition. Here we present OpenWeedLocator (OWL), an open-source, low-cost and image-based device for fallow weed detection that improves accessibility to this technology for the weed control community. A comprehensive GitHub repository was developed, promoting community engagement with site-specific weed control methods. Validation of OWL as a low-cost tool was achieved using four, existing colour-based algorithms over seven fallow fields in New South Wales, Australia. The four algorithms were similarly effective in detecting weeds with average precision of 79% and recall of 52%. In individual transects up to 92% precision and 74% recall indicate the performance potential of OWL in fallow fields. OWL represents an opportunity to redefine the approach to weed detection by enabling community-driven technology development in agriculture.

scholarly journals Impacts of Spatial Zonation Schemes on Yield Potential Estimates at the Regional Scale

Agronomy ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 631 ◽  
Author(s):  
Hao Xu ◽  
Fen Huang ◽  
Wenjun Zuo ◽  
Yongchao Tian ◽  
Yan Zhu ◽  
...  
Keyword(s):  
Growth Models ◽  
Sunshine Duration ◽  
Regional Scale ◽  
Crop Growth ◽  
Yield Potential ◽  
Specific Yield ◽  
Site Specific ◽  
Spatial Zonation ◽  
Simulation Results ◽  
Crop Growth Models

Simulations based on site-specific crop growth models have been widely used to obtain regional yield potential estimates for food security assessments at the regional scale. By dividing a region into nonoverlapping basic spatial units using appropriate zonation schemes, the data required to run a crop growth model can be reduced, thereby improving the simulation efficiency. In this study, we explored the impacts of different zonation schemes on estimating the regional yield potential of the Chinese winter wheat area to obtain the most appropriate spatial zonation scheme of weather sites therein. Our simulated results suggest that the upscaled site-specific yield potential is affected by the zonation scheme and by the spatial distribution of sites. As such, the distribution of a small number of sites significantly affected the simulated regional yield potential under different zonation schemes, and the zonation scheme based on sunshine duration clustering zones could effectively guarantee the simulation accuracy at the regional scale. Using the most influential environmental variable of crop growth models for clustering can get the better zonation scheme to upscale the site-specific simulation results. In contrast, a large number of sites had little effect on the regional yield potential simulation results under the different zonation schemes.

Comparative Response of Conventional and Quality Protein Maize Hybrids to High Population Densities in the Southern Guinea Savanna of Nigeria

2013 ◽  
Vol 2 (1) ◽  
Author(s):  
O B Bello
Keyword(s):  
Grain Yield ◽  
Plant Density ◽  
Plant Population ◽  
Yield Potential ◽  
High Yield ◽  
Quality Protein Maize ◽  
Population Densities ◽  
Higher Plant ◽  
Guinea Savanna ◽  
Plant Densities

Optimum plant population is very important in enhancing high and stable grain yield especially in quality protein maize (QPM) production. A field trial was therefore conducted to compare the performance of six hybrids (three each of QPM and normal endosperm) at three population densities using a split-plot design at the sub-station of the Lower Niger River Basin Development Authority, Oke-Oyi, in the southern Guinea savanna zone of Nigeria during the 2010 and 2011 cropping seasons. Plant population -1 densities (53,333, 66,666, and 88,888 plants ha ) constituted the main plots and the six hybrids were assigned to the subplots, replicated three times. Our results showed a differential response of maize -1 hybrids to high densities, with plant populations above 53,333 plants ha reduced grain yield, and this is more pronounced in QPM than normal endosperm hybrids. This is contrary to the results observed in many other countries. This might be that the hybrids were selected in low yield potential area at low plant densities, and hence not tolerant to plant density stress. It may also be due to low yield potential of the experimental site, which does not allow yield increases at high plant densities. Though normal endosperm hybrids 0103-11 and 0103-15 as well as QPM Dada-ba were superior for grain yield among -1 the hybrids at 53,333 plants ha , hybrid 0103-11 was most outstanding. Therefore, genetic improvement of QPM and normal endosperm hybrids for superior stress tolerance and high yield could be enhanced by selection at higher plant population densities.

scholarly journals Estimation of Fractional Photosynthetically Active Radiation From a Canopy 3D Model; Case Study: Almond Yield Prediction

2021 ◽  
Vol 12 ◽  
Author(s):  
Xin Zhang ◽  
Alireza Pourreza ◽  
Kyle H. Cheung ◽  
German Zuniga-Ramirez ◽  
Bruce D. Lampinen ◽  
...  
Keyword(s):  
Photosynthetically Active Radiation ◽  
Low Cost ◽  
Temporal Analysis ◽  
Volume Index ◽  
Yield Potential ◽  
Tree Level ◽  
Potential Yield ◽  
Model Case ◽  
Active Radiation ◽  
Canopy Volume

Canopy-intercepted light, or photosynthetically active radiation, is fundamentally crucial for quantifying crop biomass development and yield potential. Fractional photosynthetically active radiation (PAR) (fPAR) is conventionally obtained by measuring the PAR both below and above the canopy using a mobile lightbar platform to predict the potential yield of nut crops. This study proposed a feasible and low-cost method for accurately estimating the canopy fPAR using aerial photogrammetry-based canopy three-dimensional models. We tested up to eight different varieties in three experimental almond orchards, including California's leading variety of ‘Nonpareil’. To extract various canopy profile features, such as canopy cover and canopy volume index, we developed a complete data collection and processing pipeline called Virtual Orchard (VO) in Python environment. Canopy fPAR estimated by VO throughout the season was compared against midday canopy fPAR measured by a mobile lightbar platform in midseason, achieving a strong correlation (R2) of 0.96. A low root mean square error (RMSE) of 2% for ‘Nonpareil’. Furthermore, we developed regression models for predicting actual almond yield using both measures, where VO estimation of canopy fPAR, as a stronger indicator, achieved a much better prediction (R2 = 0.84 and RMSE = 195 lb acre−1) than the lightbar (R2 = 0.70 and RMSE = 266 lb acre−1) for ‘Nonpareil’. Eight different new models for estimating potential yield were also developed using temporal analysis from May to August in 2019 by adjusting the ratio between fPAR and dry kernel yield previously found using a lightbar. Finally, we compared the two measures at two different spatial precision levels: per-row and per-block. fPAR estimated by VO at the per-tree level was also assessed. Results showed that VO estimated canopy fPAR performed better at each precision level than lightbar with up to 0.13 higher R2. The findings in this study serve as a fundamental link between aerial-based canopy fPAR and the actual yield of almonds.

RELATIVE ADVANTAGE OF HIGH YIELD POTENTIAL AT LOW-YIELDING ENVIRONMENTS FOR COMMERCIAL MAIZE HYBRIDS CROPPED IN ARGENTINA

2018 ◽  
Vol 55 (5) ◽  
pp. 692-706
Author(s):  
MARIANA ANTONIETTA ◽  
JUAN J. GUIAMET
Keyword(s):  
Agricultural Technology ◽  
Relative Advantage ◽  
Yield Potential ◽  
High Yield ◽  
Cross Tolerance ◽  
Maize Breeding ◽  
Potential Yield ◽  
Maize Hybrids ◽  
Better Than ◽  
High Yield Potential

SUMMARYAn extended assumption in maize breeding is that potential yield (Ymax) predicts yield (Y) under stress conditions (here, Ymin), justifying genotypic selection under moderately high-yielding environments. Moreover, it has been postulated that Y tolerance to stress is relatively independent on the main stress factor involved in Y reduction (cross-tolerance). We carried out an analysis of four datasets from Argentine Federated Farmers network (2010/11, 2011/12 and 2012/13, 11 locations and >20 hybrids) and the National Institute of Agricultural Technology (INTA) (12 locations, 13 hybrids). No consistent relation was detected between Ymax and Ymin (r2 < 0.14) in each dataset. Y stability assessed by the coefficient of variation positively related to Ymin (r2 > 0.68 across datasets) but not to Ymax. Depending on the dataset, 40–70% of the hybrids had a varying Y performance (from worse to better) compared with the average of all hybrids, with no consistent advantage of hybrids with high Ymax within the environmental range explored in the dataset. In order to assess the existence of cross-tolerance, INTA environments were divided into two groups: water-limited environments and environments exposed to other(s) type(s) of stress. While a relation was found between average yields (r2 = 0.64) of each hybrid in both environments, there was no relation for Y stability (r2 = 0.07). Taken together, our results suggest that: (i) a high Ymax is not a good indicator of high Y tolerance under stressful conditions; (ii) Y tolerance is related to high Y stability, which may or may not involve a Y penalty under high-yielding environments; (iii) around 50% of the genotypes have Y performance that is not consistently worse or better than the average throughout the range of environments explored and (iv) cross-tolerance to stress is a peculiar trait of some hybrids, but most of the hybrids analysed here do not show cross-tolerance.

Optimum plant population densities for lupin (Lupinus angustifolius L.) in the wheatbelt of Western Australia

1994 ◽  
Vol 34 (4) ◽  
pp. 491 ◽  
Author(s):  
RJ French ◽  
K McCarthy ◽  
WL Smart
Keyword(s):  
Western Australia ◽  
Plant Population ◽  
Lupinus Angustifolius ◽  
Yield Potential ◽  
Asymptotic Model ◽  
Population Densities ◽  
Data Set ◽  
Optimum Density ◽  
Wide Range ◽  
The Relationship

Lupin (Lupinus angustifolius L.) seed yields at various plant population densities were studied in 33 separate experiments throughout the wheatbelt of Western Australia between 1987 and 1990. The experiments were designed to test the hypotheses that optimum plant population densities for lupins vary between environments and between cultivars. Another objective was the development of a framework for sowing rate recommendations from a large data set derived from sowing rate experiments. Two types of equation were fitted to each data set by nonlinear regression: one described an asymptotic response, the other a response where yield reached a maximum but declined at higher densities. The second type of equation was used to describe a data set if the residual mean square was significantly lower than for the asymptotic equation. In all, 122 individual responses were fitted, of these only 13 were not adequately described by the asymptotic model. Optimum density was chosen according to an economic criterion (when marginal revenue from an increase in plant population density equalled marginal cost). This was equivalent to choosing the point where the slope of the response curve was 0.004 t.m2/ha.plant (equivalent to 0.4 g/plant). Optimum density ranged from 14 to 138 plants/m2 and was linearly related to yield potential, which we defined as either the asymptotic yield value, or the maximum yield for responses that did not approach an asymptote. Yield potential ranged from 0.13 to 4.1 t/ha. The relationship between optimum density and yield potential was the same for cvv. Danja, Gungurru, and Yorrel, and for a reduced branching breeding line (75A/329). It was also the same on soils classified as good or poor for lupins. We suggest that the relationship between optimum density and yield potential will be useful in determining target plant densities for lupins under a wide range of conditions in Western Australia, and that the techniques should prove useful in producing recommendations from density experiments in other agricultural regions.

To Eliminate Curtain Effect of FIB TEM Samples by a Combination of Sample Dicing and Backside Milling

2014 ◽  
Author(s):  
Jian-Shing Luo ◽  
Hsiu Ting Lee
Keyword(s):  
Sample Preparation ◽  
Focused Ion Beam ◽  
Preparation Method ◽  
Low Cost ◽  
Ion Beam ◽  
Sample Preparation Method ◽  
Site Specific ◽  
Dual Beam ◽  
Transmission Electron

Abstract Several methods are used to invert samples 180 deg in a dual beam focused ion beam (FIB) system for backside milling by a specific in-situ lift out system or stages. However, most of those methods occupied too much time on FIB systems or requires a specific in-situ lift out system. This paper provides a novel transmission electron microscopy (TEM) sample preparation method to eliminate the curtain effect completely by a combination of backside milling and sample dicing with low cost and less FIB time. The procedures of the TEM pre-thinned sample preparation method using a combination of sample dicing and backside milling are described step by step. From the analysis results, the method has applied successfully to eliminate the curtain effect of dual beam FIB TEM samples for both random and site specific addresses.

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.

scholarly journals Variable-rate in corn sowing for maximizing grain yield

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eder Eujácio da Silva ◽  
Fábio Henrique Rojo Baio ◽  
Daniel Fernando Kolling ◽  
Renato Schneider Júnior ◽  
Alex Rogers Aguiar Zanin ◽  
...  
Keyword(s):  
Grain Yield ◽  
Vegetative Growth ◽  
Maximum Yield ◽  
Influential Factors ◽  
Plant Population ◽  
Seeding Density ◽  
Corn Yield ◽  
Growth Indices ◽  
Experimental Conditions ◽  
Soil Attributes

AbstractSowing density is one of the most influential factors affecting corn yield. Here, we tested the hypothesis that, according to soil attributes, maximum corn productivity can be attained by varying the seed population. Specifically, our objectives were to identify the soil attributes that affect grain yield, in order to generate a model to define the optimum sowing rate as a function of the attributes identified, and determine which vegetative growth indices can be used to predict yield most accurately. The experiment was conducted in Chapadão do Céu-GO in 2018 and 2019 at two different locations. Corn was sown as the second crop after the soybean harvest. The hybrids used were AG 8700 PRO3 and FS 401 PW, which have similar characteristics and an average 135-day cropping cycle. Tested sowing rates were 50, 55, 60, and 65 thousand seeds ha−1. Soil attributes evaluated included pH, calcium, magnesium, phosphorus, potassium, organic matter, clay content, cation exchange capacity, and base saturation. Additionally, we measured the correlation between the different vegetative growth indices and yield. Linear correlations were obtained through Pearson’s correlation network, followed by path analysis for the selection of cause and effect variables, which formed the decision trees to estimate yield and seeding density. Magnesium and apparent electrical conductivity (ECa) were the most important soil attributes for determining sowing density. Thus, the plant population should be 56,000 plants ha−1 to attain maximum yield at ECa values > 7.44 mS m−1. In addition, the plant population should be 64,800 plants ha−1 at values < 7.44 mS m−1 when magnesium levels are greater than 0.13 g kg−1, and 57,210 plants ha−1 when magnesium content is lower. Trial validation showed that the decision tree effectively predicted optimum plant population under the local experimental conditions, where yield did not significantly differ among populations.

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