scholarly journals Impacts and management strategies for crop production in waterlogged or flooded soils: A review

2020 ◽  
Vol 112 (3) ◽  
pp. 1475-1501 ◽  
Author(s):  
Gurpreet Kaur ◽  
Gurbir Singh ◽  
Peter P. Motavalli ◽  
Kelly A. Nelson ◽  
John M. Orlowski ◽  
...  
Keyword(s):  
Crop Production ◽  
Management Strategies ◽  
Flooded Soils

scholarly journals Detection and Analysis of Degree of Maize Lodging Using UAV-RGB Image Multi-Feature Factors and Various Classification Methods

2021 ◽  
Vol 10 (5) ◽  
pp. 309
Author(s):  
Zixu Wang ◽  
Chenwei Nie ◽  
Hongwu Wang ◽  
Yong Ao ◽  
Xiuliang Jin ◽  
...  
Keyword(s):  
Crop Production ◽  
Accurate Determination ◽  
Management Strategies ◽  
Canopy Structure ◽  
Object Oriented ◽  
Texture Features ◽  
Sowing Date ◽  
Kappa Coefficient ◽  
Surface Model ◽  
Field Management

Maize (Zea mays L.), one of the most important agricultural crops in the world, which can be devastated by lodging, which can strike maize during its growing season. Maize lodging affects not only the yield but also the quality of its kernels. The identification of lodging is helpful to evaluate losses due to natural disasters, to screen lodging-resistant crop varieties, and to optimize field-management strategies. The accurate detection of crop lodging is inseparable from the accurate determination of the degree of lodging, which helps improve field management in the crop-production process. An approach was developed that fuses supervised and object-oriented classifications on spectrum, texture, and canopy structure data to determine the degree of lodging with high precision. The results showed that, combined with the original image, the change of the digital surface model, and texture features, the overall accuracy of the object-oriented classification method using random forest classifier was the best, which was 86.96% (kappa coefficient was 0.79). The best pixel-level supervised classification of the degree of maize lodging was 78.26% (kappa coefficient was 0.6). Based on the spatial distribution of degree of lodging as a function of crop variety, sowing date, densities, and different nitrogen treatments, this work determines how feature factors affect the degree of lodging. These results allow us to rapidly determine the degree of lodging of field maize, determine the optimal sowing date, optimal density and optimal fertilization method in field production.

scholarly journals Community seed network in an era of climate change: dynamics of maize diversity in Yucatán, Mexico

2021 ◽  
Author(s):  
Marianna Fenzi ◽  
Paul Rogé ◽  
Angel Cruz-Estrada ◽  
John Tuxill ◽  
Devra Jarvis
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Management Strategies ◽  
Farming Systems ◽  
Seed Systems ◽  
Farming Community ◽  
Climate Resilience ◽  
Maize Diversity ◽  
Climatic Period ◽  
Small Holder Farmers

AbstractLocal seed systems remain the fundamental source of seeds for many crops in developing countries. Climate resilience for small holder farmers continues to depend largely on locally available seeds of traditional crop varieties. High rainfall events can have as significant an impact on crop production as increased temperatures and drought. This article analyzes the dynamics of maize diversity over 3 years in a farming community of Yucatán state, Mexico, where elevated levels of precipitation forced farmers in 2012 to reduce maize diversity in their plots. We study how farmers maintained their agroecosystem resilience through seed networks, examining the drivers influencing maize diversity and seed provisioning in the year preceding and following the 2012 climatic disturbance (2011–2013). We found that, under these challenging circumstances, farmers focused their efforts on their most reliable landraces, disregarding hybrids. We show that farmers were able to recover and restore the diversity usually cultivated in the community in the year following the critical climate event. The maize dynamic assessed in this study demonstrates the importance of community level conservation of crop diversity. Understanding farmer management strategies of agrobiodiversity, especially during a challenging climatic period, is necessary to promote a more tailored response to climate change in traditional farming systems.

scholarly journals Some integrative management strategies to decrease doses of herbicides in agriculture

2017 ◽  
Vol 2 ◽  
pp. 31
Author(s):  
Salar Farhangi Abriz
Keyword(s):  
Water Quality ◽  
Food Safety ◽  
Nitrogen Content ◽  
Crop Production ◽  
Management Strategies ◽  
Agricultural Products ◽  
Main Target ◽  
Physicochemical Methods ◽  
Management Method ◽  
Integrative Management

<p>Over dose using of herbicides is one of the major problems in crops and horticulture productions. Human food safety and economical production of agricultural products are the main target of new agronomy and plant scientists. Integrative management is one of the new programs for reducing herbicide doses in agriculture. This program includes many physiological and physicochemical methods for controlling herbicide uses in farms and orchards. This article explain some of these methods such as using surfactants, water quality in spraying, using magnetic fields, controlling the nitrogen content of soil, using a suitable formulation and powerful cultivars and genotypes in agriculture and the effects of this reduction in herbicide doses on plants behavior and weeds controlling. According to this method integrative management can be beneficial in crop production and farmers must be using of this management method in their farms. </p>

scholarly journals Uses of different techniques for the production of sustainable soil and food

2020 ◽  
Vol 2 (4) ◽  
Author(s):  
Sahrish Khan ◽  
Abdul Waris
Keyword(s):  
Adverse Effect ◽  
Disease Management ◽  
Soil Fertility ◽  
Crop Production ◽  
Soil Structure ◽  
Low Cost ◽  
New Technology ◽  
Management Strategies ◽  
Soil Condition ◽  
Plant Disease Management

Due to increase in the population which is estimated that the human papulation will increased 9.7 billion in 2050. There is also increase the demands of the food productions. That’s why there is need to solve the problems regarding to the production of the food. Major problem of the food production is the shortage of the land due to the low and bad soil structure and quality of the soil. Soil erosion is one of the main issue which is caused  due to the used of different chemicals, pesticides and fertilizers which are mainly used for the  plant growth and protection but they are the main reasons of the production of the pollution in the soil. There is need of the different new technology for the improvement of the soil structure, quality, its fertility and decontamination of pollution from the soil which are eco-friendly to the environment and have no adverse effect. In this study the role of the different techniques in which genetic engineering, Nano technologies, soil and crop management strategies, integrated pest control management strategies, sustainable remediation techniques, microbial management strategies and the different management stairgates. All these techniques aim to the production of the plants and microbes which are effective against plant disease management. The aim of the use nano agrochemicals and nano sensors for sensing environmental and pathogen conditions against disease management. The aim of the paper to provide the production of the disease resistance plant and the provide balanced nutrients supplements to the soil for the improvement of the soil condition and its fertility. These techniques have economic importance due to the use of the nano agrochemicals which are low cost and have effective and reduce the use of the chemicals substances which have negative effect on the  soil fertility.. There are sustainable remediations techniques also discussed which are used for the decontamination of the soil pollution. In this study the main focus on the improve and increase soil fertility which enhance the growth of the plants as well the production of the crop production. The production of the stress and degradation resistance microbes which is important factor for the protection of the soil from degradation or contamination. All the techniques which are used in this paper have no adverse effect they are helpful in the tolerance of the stress conditions.

scholarly journals Risk Management Strategies to Reduce Net Income Variability for Farmers

1985 ◽  
Vol 17 (1) ◽  
pp. 117-130 ◽  
Author(s):  
Hamid Falatoonzadeh ◽  
J. Richard Conner ◽  
Rulon D. Pope
Keyword(s):  
Risk Management ◽  
Crop Production ◽  
Management Strategies ◽  
Farm Income ◽  
Net Income ◽  
Combination Strategy ◽  
Management Tools ◽  
Risk Management Strategies ◽  
Price Risks ◽  
The Many

AbstractThe most useful and practical strategy available for reducing variability of net farm income is ascertained. Of the many risk management tools presently available, five of the most commonly used are simultaneously incorporated in an empirically tested model. Quadratic programming provides the basis for decisionmaking in risk management wherein expected utility is assumed to be a function of the mean and variance of net income. Results demonstrate that farmers can reduce production and price risks when a combination strategy including a diversified crop production plan and participation in the futures market and the Federal Crop Insurance Program (FCIP) is implemented.

scholarly journals Weeds and Their Effect on the Performance of Maize and Finger Millet in Mid-Hills of Nepal

2014 ◽  
Vol 2 (3) ◽  
pp. 275-278 ◽  
Author(s):  
Tika Bahadur Karki ◽  
Shrawan K. Sah ◽  
Resam B. Thapa ◽  
Andrew J. McDonald ◽  
Adam S. Davis ◽  
...  
Keyword(s):  
Weed Management ◽  
Crop Production ◽  
Finger Millet ◽  
Crop Yields ◽  
Management Strategies ◽  
Cropping System ◽  
Weed Species ◽  
Ageratum Conyzoides ◽  
Alternative Crop ◽  
Weed Infestation

Relay cropping of maize with fingermillet (maize/fingermillet) is the predominant cropping system for sustaining food security situation in the hilly regions of Nepal. In this region weed pressure severely reduces crop yields. Basic information on weed species composition, biomass production and their effect on crop yields and economics are lacking for this region. This information will be necessary to develop effective weed management strategies for the future. In light of this an empirical study was carried out in two representatives mid hill districts of Parbat and Baglung during summer season of 2010/2011 in Nepal. A total of 10 major weed species with densities of 172 in Parbat and 311 per 0.25m2 area in Baglung were observed. The highest percentage of both relative and absolute densities were recorded for Ageratum conyzoides in Parbat and Polygonum chinensis in Baglung. Weed infestation under farmers practice of crop management reduced the grain yield of maize by 1.985 Mt ha-1 (117%) in Baglung and 1.760 Mt ha-1 (108%) in Parbat. Similarly, in finger millet it was 0.489 Mt ha-1 (63%) in Baglung and 0.403 Mt ha-1 in Parbat. Similarly, the combined yield of both the crops was also significantly reduced by 79.3% and 61.7% in Baglung and Parbat respectively. Hence, weeds are directly affecting the crop performance in the region. Therefore, there is an urgent need to develop an alternative crop production system in the hills. DOI: http://dx.doi.org/10.3126/ijasbt.v2i3.10790Int J Appl Sci Biotechnol, Vol. 2(3): 275-278  

scholarly journals Socio-ecological factors determine crop performance in agricultural systems

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Libère Nkurunziza ◽  
Christine A. Watson ◽  
Ingrid Öborn ◽  
Henrik G. Smith ◽  
Göran Bergkvist ◽  
...  
Keyword(s):  
Crop Production ◽  
Production Systems ◽  
Spring Barley ◽  
Management Strategies ◽  
Ecological Factors ◽  
Farming Systems ◽  
Agricultural System ◽  
Ecological Zones ◽  
Crop Performance ◽  
Latent Structures

AbstractAgricultural production systems are affected by complex interactions between social and ecological factors, which are often hard to integrate in a common analytical framework. We evaluated differences in crop production among farms by integrating components of several related research disciplines in a single socio-ecological analysis. Specifically, we evaluated spring barley (Hordeum vulgare, L.) performance on 34 farms (organic and conventional) in two agro-ecological zones to unravel the importance of ecological, crop and management factors in the performance of a standard crop. We used Projections to Latent Structures (PLS), a simple but robust analytical tool widely utilized in research disciplines dealing with complex systems (e.g. social sciences and chemometrics), but infrequently in agricultural sciences. We show that barley performance on organic farms was affected by previous management, landscape structure, and soil quality, in contrast to conventional farms where external inputs were the main factors affecting biomass and grain yield. This indicates that more complex management strategies are required in organic than in conventional farming systems. We conclude that the PLS method combining socio-ecological and biophysical factors provides improved understanding of the various interacting factors determining crop performance and can help identify where improvements in the agricultural system are most likely to be effective.

scholarly journals Benefits and Limitations of Decision Support Systems (DSS) with a Special Emphasis on Weeds

Agronomy ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 548 ◽  
Author(s):  
Panagiotis Kanatas ◽  
Ilias S. Travlos ◽  
Ioannis Gazoulis ◽  
Alexandros Tataridas ◽  
Anastasia Tsekoura ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Weed Management ◽  
Crop Production ◽  
Support Systems ◽  
Management Strategies ◽  
Farming Systems ◽  
Climatic Conditions ◽  
Management Options ◽  
The Right

Decision support systems (DSS) have the potential to support farmers to make the right decisions in weed management. DSSs can select the appropriate herbicides for a given field and suggest the minimum dose rates for an herbicide application that can result in optimum weed control. Given that the adoption of DSSs may lead to decreased herbicide inputs in crop production, their potential for creating eco-friendly and profitable weed management strategies is obvious and desirable for the re-designing of farming systems on a more sustainable basis. Nevertheless, it is difficult to stimulate farmers to use DSSs as it has been noticed that farmers have different expectations of decision-making tools depending on their farming styles and usual practices. The function of DSSs requires accurate assessments of weeds within a field as input data; however, capturing the data can be problematic. The development of future DSSs should target to enhance weed management tactics which are less reliant on herbicides. DSSs should also provide information regarding weed seedbank dynamics in the soil in order to suggest management options not only within a single period but also in a rotational view. More aspects ought to be taken into account and further research is needed in order to optimize the practical use of DSSs for supporting farmers regarding weed management issues in various crops and under various soil and climatic conditions.

scholarly journals Automation for Water and Nitrogen Deficit Stress Detection in Soilless Tomato Crops Based on Spectral Indices

Horticulturae ◽  
2018 ◽  
Vol 4 (4) ◽  
pp. 47 ◽  
Author(s):  
Angeliki Elvanidi ◽  
Nikolaos Katsoulas ◽  
Constantinos Kittas
Keyword(s):  
Crop Production ◽  
Control Strategies ◽  
Classification Tree ◽  
Management Strategies ◽  
Total Sample ◽  
Sensor Data ◽  
Limiting Factors ◽  
Tree Model ◽  
Environment Control ◽  
The Impact

Water and nitrogen deficit stress are some of the most important growth limiting factors in crop production. Several methods have been used to quantify the impact of water and nitrogen deficit stress on plant physiology. However, by performing machine learning with hyperspectral sensor data, crop physiology management systems are integrated into real artificial intelligence systems, providing richer recommendations and insights into implementing appropriate irrigation and environment control management strategies. In this study, the Classification Tree model was used to group complex hyperspectral datasets in order to provide remote visual results about plant water and nitrogen deficit stress. Soilless tomato crops are grown under varying water and nitrogen regimes. The model that we developed was trained using 75% of the total sample dataset, while the rest (25%) of the data were used to validate the model. The results showed that the combination of MSAVI, mrNDVI, and PRI had the potential to determine water and nitrogen deficit stress with 89.6% and 91.4% classification accuracy values for the training and testing samples, respectively. The results of the current study are promising for developing control strategies for sustainable greenhouse production.

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