scholarly journals ASSESSMENT OF CROP YIELD AND RAINFALL SIMULATION IN NASARAWA TOWN NASARAWA STATE NIGERIA

2020 ◽  
Vol 4 (2) ◽  
pp. 75-78
Author(s):  
Ibrahim Sufiyan ◽  
K.D. Mohammed ◽  
Magaji J.I
Keyword(s):  
Crop Yield ◽  
Growth Curve ◽  
Technology Use ◽  
Crop Production ◽  
Crop Yields ◽  
Rainfall Simulation ◽  
Linear Quadratic ◽  
Growth Curve Models ◽  
Use Of Time ◽  
To Come

Recent technology use simulation to predict the amount and total crop production and yield in a particular piece of land. Crop yield is termed as the growth of crop per unit area. This study calculates the crop yield for 20 years and uses simulation to produce 18 years of crop yields at different locations in Nasarawa Local Government Area of Nasarawa State Nigeria. the study applies the use of time series analysis of both Linear, quadratic and growth curve models to ascertain the crop yield. The result indicates that there is a high amount of rainfall in the preceding year from 2020 -2038 with a rainfall trend of more than 2200mm- 2300mm per annum. The crop yield simulation shows a higher growth curve with a bumper harvest in the next years to come.

scholarly journals The Pitfalls of Relating Weeds, Herbicide Use, and Crop Yield: Don't Fall Into the Trap! A Critical Review

2020 ◽  
Vol 2 ◽  
Author(s):  
Nathalie Colbach ◽  
Sandrine Petit ◽  
Bruno Chauvel ◽  
Violaine Deytieux ◽  
Martin Lechenet ◽  
...  
Keyword(s):  
Crop Yield ◽  
Weed Management ◽  
Crop Production ◽  
Yield Loss ◽  
Crop Yields ◽  
Cropping Systems ◽  
Crop Productivity ◽  
Arable Farming ◽  
Herbicide Use ◽  
The Impact

The growing recognition of the environmental and health issues associated to pesticide use requires to investigate how to manage weeds with less or no herbicides in arable farming while maintaining crop productivity. The questions of weed harmfulness, herbicide efficacy, the effects of herbicide use on crop yields, and the effect of reducing herbicides on crop production have been addressed over the years but results and interpretations often appear contradictory. In this paper, we critically analyze studies that have focused on the herbicide use, weeds and crop yield nexus. We identified many inconsistencies in the published results and demonstrate that these often stem from differences in the methodologies used and in the choice of the conceptual model that links the three items. Our main findings are: (1) although our review confirms that herbicide reduction increases weed infestation if not compensated by other cultural techniques, there are many shortcomings in the different methods used to assess the impact of weeds on crop production; (2) Reducing herbicide use rarely results in increased crop yield loss due to weeds if farmers compensate low herbicide use by other efficient cultural practices; (3) There is a need for comprehensive studies describing the effect of cropping systems on crop production that explicitly include weeds and disentangle the impact of herbicides from the effect of other practices on weeds and on crop production. We propose a framework that presents all the links and feed-backs that must be considered when analyzing the herbicide-weed-crop yield nexus. We then provide a number of methodological recommendations for future studies. We conclude that, since weeds are causing yield loss, reduced herbicide use and maintained crop productivity necessarily requires a redesign of cropping systems. These new systems should include both agronomic and biodiversity-based levers acting in concert to deliver sustainable weed management.

scholarly journals A multi-model analysis of teleconnected crop yield variability in a range of cropping systems

2019 ◽  
Author(s):  
Matias Heino ◽  
Joseph H. A. Guillaume ◽  
Christoph Müller ◽  
Toshichika Iizumi ◽  
Matti Kummu
Keyword(s):  
Crop Yield ◽  
Crop Production ◽  
Food System ◽  
Crop Yields ◽  
Southern Oscillation ◽  
Yield Variability ◽  
Management Scenarios ◽  
Yield Data ◽  
Climate Oscillations ◽  
Crop Models

Abstract. Climate oscillations are periodically fluctuating oceanic and atmospheric phenomena, which are related to variations in weather patterns and crop yields worldwide. In terms of crop production, the most widespread impacts have been observed for the El Niño Southern Oscillation (ENSO), which has been found to impact crop yields in all continents that produce crops, while two other climate oscillations – the Indian Ocean Dipole (IOD) and the North Atlantic Oscillation (NAO) – have been shown to impact crop production especially in Australia and Europe, respectively. In this study, we analyse the impacts of ENSO, IOD and NAO on the growing conditions of maize, rice, soybean and wheat at the global scale, by utilizing crop yield data from an ensemble of global gridded crop models simulated for a range of crop management scenarios. Our results show that simulated crop yield variability is correlated to climate oscillations to a wide extent (up to almost half of all maize and wheat harvested areas for ENSO) and in several important crop producing areas, e.g. in North America (ENSO, wheat), Australia (IOD & ENSO, wheat) and northern South America (ENSO, soybean). Further, our analyses show that higher sensitivity to these oscillations can be observed for rainfed, and fully fertilized scenarios, while the sensitivity tends to be lower if crops are fully irrigated. Since, the development of ENSO, IOD and NAO can be reliably forecasted in advance, a better understanding about the relationship between crop production and these climate oscillations can improve the resilience of the global food system to climate related shocks.

scholarly journals Spatial and temporal variability of crop yield and some Rhodic Hapludox properties under no-tillage

2010 ◽  
Vol 34 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Osvaldo Guedes Filho ◽  
Sidney Rosa Vieira ◽  
Márcio Koiti Chiba ◽  
César Hideo Nagumo ◽  
Sônia Carmela Falci Dechen
Keyword(s):  
Physical Properties ◽  
Soil Properties ◽  
Crop Yield ◽  
Crop Production ◽  
Crop Yields ◽  
Chemical Properties ◽  
Temporal Variations ◽  
Northern Region ◽  
Spatial And Temporal Variability ◽  
No Tillage

Soil properties are closely related with crop production and spite of the measures implemented, spatial variation has been repeatedly observed and described. Identifying and describing spatial variations of soil properties and their effects on crop yield can be a powerful decision-making tool in specific land management systems. The objective of this research was to characterize the spatial and temporal variations in crop yield and chemical and physical properties of a Rhodic Hapludox soil under no-tillage. The studied area of 3.42 ha had been cultivated since 1985 under no-tillage crop rotation in summer and winter. Yield and soil property were sampled in a regular 10 x 10 m grid, with 302 sample points. Yields of several crops were analyzed (soybean, maize, triticale, hyacinth bean and castor bean) as well as soil chemical (pH, Soil Organic Matter (SOM), P, Ca2+, Mg2+, H + Al, B, Fe, Mn, Zn, CEC, sum of bases (SB), and base saturation (V %)) and soil physical properties (saturated hydraulic conductivity, texture, density, total porosity, and mechanical penetration resistance). Data were analyzed using geostatistical analysis procedures and maps based on interpolation by kriging. Great variation in crop yields was observed in the years evaluated. The yield values in the Northern region of the study area were high in some years. Crop yields and some physical and soil chemical properties were spatially correlated.

Closing Yield Gaps: Consequences for the Global Food Supply, Environmental Quality & Food Security

Daedalus ◽  
2015 ◽  
Vol 144 (4) ◽  
pp. 45-56 ◽  
Author(s):  
Nathaniel D. Mueller ◽  
Seth Binder
Keyword(s):  
Food Security ◽  
Crop Yield ◽  
Food Supply ◽  
Crop Production ◽  
Crop Yields ◽  
Agricultural Landscapes ◽  
Environmental Benefits ◽  
Potential Contribution ◽  
Yield Gap ◽  
Yield Gaps

The social, economic, and environmental costs of feeding a burgeoning and increasingly affluent human population will depend, in part, on how we increase crop production on under-yielding agricultural landscapes, and by how much. Such areas have a “yield gap” between the crop yields they achieve and the crop yields that could be achieved under more intensive management. Crop yield gaps have received increased attention in recent years due to concerns over land scarcity, stagnating crop yield trends in some important agricultural areas, and large projected increases in food demand. Recent analyses of global data sets and results from field trials have improved our understanding of where yield gaps exist and their potential contribution to increasing the food supply. Achieving yield gap closure is a complex task: while agronomic approaches to closing yield gaps are generally well-known, a variety of social, political, and economic factors allow them to persist. The degree to which closing yield gaps will lead to greater food security and environmental benefits remains unclear, and will be strongly influenced by the particular strategies adopted.

scholarly journals Contributions of Climate and Soil Properties to Wheat and Maize Yield Based on Long-Term Fertilization Experiments

Plants ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2002
Author(s):  
Shengbao Wei ◽  
Anchun Peng ◽  
Xiaomin Huang ◽  
Aixing Deng ◽  
Changqing Chen ◽  
...  
Keyword(s):  
Soil Properties ◽  
Crop Yield ◽  
Crop Production ◽  
Field Experiments ◽  
Crop Yields ◽  
Climatic Factors ◽  
Maize Yield ◽  
Positive Interactions ◽  
Climate Factors ◽  
Average Contribution

Identifying the contributions of climate factors and soil fertility to crop yield is significant for the assessment of climate change impacts on crop production. Three 20-year field experiments were conducted in major Chinese wheat-maize cropping areas. Over the 20-year period, crop yield and soil properties showed significantly dissimilar variation trends under similar climate changes at each experimental site. The correlation between climatic factors and crop yield varied greatly among the fertilization regimes and experimental sites. Across all the fertilization regimes and the experimental sites, the average contribution rates of soil properties to wheat and maize yield were 45.7% and 53.2%, respectively, without considering climate factors, and 40.4% and 36.6%, respectively, when considering climate factors. The contributions of soil properties to wheat and maize yield variation when considering climate factors were significantly lower than those without considering climate factors. Across all experimental sites and all fertilization regimes, the mean contribution rates of climate factors to wheat and maize yield were 29.5% and 33.0%, respectively. The contribution rates of the interaction of climate and soil to wheat and maize yield were 3.7% and −0.9%, respectively. Under balanced fertilization treatments (NPK and NPKM), the change in the contribution rate of soil properties to wheat or maize yield was not obvious, and the average contribution rates of the interaction of climate and soil to wheat and maize yield were positive, at 14.8% and 9.5%, respectively. In contrast, under unbalanced fertilization treatments (CK and N), the contribution rates of soil properties to wheat or maize yield decreased, and the average contribution rates of the interaction of climate and soil were negative, at −7.4% and −11.2%, respectively. The above results indicate that climate and soil synergistically affected crop yields and that, with the optimization of the fertilization regime, positive interactions gradually emerged.

scholarly journals REVIEW ON KNOWLEDGE GAP IN Brachiaria GRASS RESEARCH AND UTILIZATION: ETHIOPIAN PERSPECTIVE

2021 ◽  
Vol 10 (1) ◽  
pp. 9-26
Author(s):  
Wubetie ADNEW ◽  
Bimrew ASMARE ◽  
Yeshambel MEKURIAW
Keyword(s):  
Food Security ◽  
Crop Yield ◽  
Crop Production ◽  
Crop Yields ◽  
Livestock Production ◽  
Agricultural System ◽  
Research Knowledge ◽  
Feed Resources ◽  
Livestock Feed ◽  
The Tropics

Still food security has not been attained fully in many tropical African countries including Ethiopia. However, the issue of food security achievement has been able to realize due to various setbacks among which low productivity of crops and livestock take the lion share. Among the various constraints the parasitic weed Striga, and Stemborer pests are responsible for lower crop yields in the region. Regarding livestock feed, shortage in terms of quantity and quality are the major impediment to the livestock sector. To achieve food security, increasing crop yield and livestock production is vital in Ethiopia and other tropical countries. Crop yields can be enhanced through the control of weeds using biological systems to increase food crop yield apart from chemical inputs. In case of livestock, full production and reproduction potential of animals can be met through fulfilling nutritional requirements of livestock. The major livestock feed resources in Ethiopia are natural pasture and crop residues. Both feed resources; however, are poor in nutritional value and they are listed as low maintenance feed category. Therefore, it is vital to intensify integrated crop- livestock production systems for sustainable economy and environment. Introducing forage grasses in the crop production system has been practiced in the tropics as push pull technology. In Ethiopia, Brachiaria grass is an emerging forage for integrated agricultural production that has been getting considerable recognition as an option to overcome the pests in crop production in the tropics due to its high adaptive and yielding as well as climate smart forages. In the country, Brachiaria is recently introduced by different organization in different agro-ecology of the country mainly as push-pull integrated agricultural system and considering its fodder potential for the livestock feed. Therefore, this review paper aimed to looking for the available research knowledge in Ethiopia and somewhere else in the glob for better utilization of Brachiaria grass in the integrated agricultural system. All available information regarding the research and utilization of Brachiaria grass were reviewed in the published papers. The review reveal that Brachiaria has many advantages over other grass species in terms of adaptation to drought and low fertility soils, ability to sequester carbon; increase nitrogen use efficiency through biological nitrification inhibition (BNI) and arrest greenhouse gas emissions. The knowledge has been established in quantifying the multiple contributions of Brachiaria grass inclusion as push pull technology in different parts of the world (South America, Kenya, Rwanda). Limited report showed that cut-and-carry system is the utilization practice of brachiaria grass grown the push pull integration. The potential of improved Brachiaria grass in Ethiopia to address the challenge of livestock feed scarcity and other environmental managements; however, remain unexploited/limited which calls researchers to work on. The review concluded that B. cultivars could have a significant contribution on both animal and cereal production in the tropics but limited research and utilization in Ethiopia.

scholarly journals A multi-model analysis of teleconnected crop yield variability in a range of cropping systems

2020 ◽  
Vol 11 (1) ◽  
pp. 113-128 ◽  
Author(s):  
Matias Heino ◽  
Joseph H. A. Guillaume ◽  
Christoph Müller ◽  
Toshichika Iizumi ◽  
Matti Kummu
Keyword(s):  
Crop Yield ◽  
Crop Production ◽  
Food System ◽  
Crop Yields ◽  
Southern Oscillation ◽  
Yield Variability ◽  
Management Scenarios ◽  
Yield Data ◽  
Climate Oscillations ◽  
Crop Models

Abstract. Climate oscillations are periodically fluctuating oceanic and atmospheric phenomena, which are related to variations in weather patterns and crop yields worldwide. In terms of crop production, the most widespread impacts have been observed for the El Niño–Southern Oscillation (ENSO), which has been found to impact crop yields on all continents that produce crops, while two other climate oscillations – the Indian Ocean Dipole (IOD) and the North Atlantic Oscillation (NAO) – have been shown to especially impact crop production in Australia and Europe, respectively. In this study, we analyse the impacts of ENSO, IOD, and NAO on the growing conditions of maize, rice, soybean, and wheat at the global scale by utilising crop yield data from an ensemble of global gridded crop models simulated for a range of crop management scenarios. Our results show that, while accounting for their potential co-variation, climate oscillations are correlated with simulated crop yield variability to a wide extent (half of all maize and wheat harvested areas for ENSO) and in several important crop-producing areas, e.g. in North America (ENSO, wheat), Australia (IOD and ENSO, wheat), and northern South America (ENSO, soybean). Further, our analyses show that higher sensitivity to these oscillations can be observed for rainfed and fully fertilised scenarios, while the sensitivity tends to be lower if crops were to be fully irrigated. Since the development of ENSO, IOD, and NAO can potentially be forecasted well in advance, a better understanding about the relationship between crop production and these climate oscillations can improve the resilience of the global food system to climate-related shocks.

scholarly journals Lean optimization model for managing the yield of pima cotton (gossipier Barba dense) in small- and medium-sized farms in the Peruvian coast areas

2018 ◽  
Vol 7 (3) ◽  
pp. 1718
Author(s):  
Claudia Rojas ◽  
Grimaldo Quispe ◽  
Carlos Raymundo
Keyword(s):  
Production Process ◽  
Crop Yield ◽  
Optimization Model ◽  
Lean Manufacturing ◽  
Crop Production ◽  
Crop Yields ◽  
Model Simulation ◽  
Cotton Crop ◽  
Pima Cotton ◽  
Peruvian Coast

This study proposes a lean manufacturing-based optimization model to standardize “Pima cotton” crop yields in the Peruvian coast areas toward the north of Piura as the study area. The study also discusses how Pima cotton is grown in the Peruvian cost areas. This is represented in 2 stages: diagnosis and development of the cotton crop model. The diagnosis stage consists of 3 steps, and the development stage consists of 2 steps. The interrelation of each stage has been identified with the lean manufacturing principle for the improvement of crop yield. Results showed that to increase current crop yield in Piura to 172 bushels/ha as well as determine the quantities of resources and raw materials required considering a standardized crop production process. The limitations of the research depend on the climatic conditions in Peru. The main contribution of this research is to propose a model using which farmers may produce Pima cotton by utilizing the indicators proposed to increase the process control. In addition, the paper proposes a standardized crop production process that farmers must follow, supported by a mathematical model simulation.  

scholarly journals Evaluation of Machine Learning Algorithms for Crop Yield Prediction

2019 ◽  
Vol 8 (6) ◽  
pp. 4082-4086 ◽  
Keyword(s):  
Machine Learning ◽  
Decision Tree ◽  
Crop Yield ◽  
Crop Production ◽  
Crop Yields ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Training Dataset ◽  
Support Vector ◽  
K Nearest Neighbor

Agriculture plays a significant role in the growth of the national economy. It relay on weather and other environmental aspects. Some of the factors on which agriculture is dependent are Soil, climate, flooding, fertilizers, temperature, precipitation, crops, insecticides and herb. The crop yield is dependent on these factors and hence difficult to predict. To know the status of crop production, in this work we perform descriptive study on agricultural data using various machine learning techniques. Crop yield estimates include estimating crop yields from available historical data such as precipitation data, soil data, and historic crop yields. This prediction will help farmers to predict crop yield before farming. Here we are utilizing three datasets like as clay dataset, precipitation dataset, and production dataset of Karnataka state, then we structure an assembled data sets and on this dataset we employ three different algorithms to get the genuine assessed yield and the precision of three different methods. K-Nearest Neighbor(KNN), Support Vector Machine(SVM), and Decision tree algorithms are applied on the training dataset and are tested with the test dataset, and the implementation of these algorithms is done using python programming and spyder tool. The performance comparison of algorithms is shown using mean absolute error, cross validation and accuracy and it is found that Decision tree is giving accuracy of 99% with very less mean square error(MSE). The proposed model can exhibit the precise expense of assessed crop yield and it is mark like as LOW, MID, and HIGH.

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