Analysis of maize canopy development under water stress and incorporation into the ADEL-Maize model

2008 ◽  
Vol 35 (10) ◽  
pp. 925 ◽  
Author(s):  
Youhong Song ◽  
Colin Birch ◽  
Jim Hanan
Keyword(s):  
Water Stress ◽  
Crop Production ◽  
Extension Rate ◽  
Canopy Development ◽  
Independent Observations ◽  
Substantial Progress ◽  
Final Length ◽  
Architectural Development ◽  
Using Data ◽  
Non Destructive

Substantial progress in modelling crop architecture has been made under optimal watering conditions; however, crop production is often exposed to water stress. In this research, we develop methods for implementing the simulation of maize (Zea mays L.) canopy architectural development under water stress using data from a maize field trial in 2006–07. Data of leaf number, leaf and internode extension were collected using non-destructive and destructive sampling at 2–3 day intervals. Water stress reduced the extension rate of organs and, therefore, their final length, the reduction being greater as severity of water stress increased. The duration of extension of organs in most phytomers was not significantly affected by water stress. Also, the rate of extension during the linear phase responded linearly to fraction of extractable soil water. An existing 3-D architectural model ADEL-Maize was revised using relationships developed in this study to better incorporate effects of water stress on organ extension and production. Simulated canopy production under three water regimes was validated by comparing predicted final leaf and internode length, plant height and leaf area to independent observations. The analysis and simulation showed that maize organ extension and final length under water stress can be adequately represented by simple linear patterns that are easily integrated into models.

Real-Time Detection of Water Stress in Corn Using Image Processing and Deep Learning

2020 ◽  
Author(s):  
Mor Soffer ◽  
Naftali Lazarovitch ◽  
Ofer Hadar
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Water Stress ◽  
Crop Production ◽  
Irrigation Treatment ◽  
Agricultural Crop ◽  
Learning Techniques ◽  
Web Camera ◽  
Use Efficiency ◽  
Non Destructive

<p>Water limitation is one of the main environmental constraints that adversely affects agricultural crop production around the world. Precise and rapid detection of plant water stress is critical for increasing agricultural productivity and water use efficiency. Numerous studies conducted over the years have attempted to find effective ways to correctly recognize situations of water stress in order to determine irrigation regimes.</p><p>Water stress detection is currently done by various methods that are not ideal; these methods are often very expensive, destructive and cumbersome. Water stress in plants is also expressed at different visual levels. Image processing is alternative way to visually recognize water stress levels. Such analysis is non-destructive, inexpensive and allows to examine the spatial variability of stress level under field conditions.</p><p>In our study, we propose a new method for detecting water stress in corn using image processing and deep learning. For the purpose of collecting the images, we performed a three-months experiment, in which we took images of five different groups of corn. Each group had a different irrigation treatment, which led to five different levels of water stress. The images were collected using a web camera located approximately 2 m from the plants.</p><p>Stress classification was done by inserting processed images into a Convolutional Neural Network (CNN). Training the network was done using transfer-learning techniques in order to exploit the performance of an already trained CNN, for a fast and efficient training over the dataset. Testing the quality of classification was done using extra camera which took a different set of images.</p><p>Results were tested upon two sub-experiments - classification of three types of treatments and classification of five types of treatments; the results were 98% accuracy in classification into three types of treatments (well-watered, reduced-watered and draught stressed treatment), and 85% accuracy in classification into five different treatments. These initial results are definitely excellent and can certainly serve decision making for optimal irrigation. <strong> </strong></p>

Analysis of Crop Yield Prediction of Kharif & Rabi Jowar Crops Using Data Mining Techniques

2017 ◽  
Vol 7 (11) ◽  
pp. 79
Author(s):  
Sujata Mulik
Keyword(s):  
Data Mining ◽  
Crop Yield ◽  
Crop Production ◽  
Climatic Factors ◽  
Crop Productivity ◽  
Yield Prediction ◽  
Data Mining Techniques ◽  
Agriculture Sector ◽  
Using Data ◽  
Rabi Crops

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction.  The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops. 

scholarly journals A Comparison of Approaches to Regional Land-Use Capability Analysis for Agricultural Land-Planning

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 458
Author(s):  
Tara A. Ippolito ◽  
Jeffrey E. Herrick ◽  
Ekwe L. Dossa ◽  
Maman Garba ◽  
Mamadou Ouattara ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Planning ◽  
Crop Production ◽  
Agricultural Land ◽  
Arable Land ◽  
Agricultural Activity ◽  
Field Samples ◽  
Agricultural Potential ◽  
Fertility Data ◽  
Using Data

Smallholder agriculture is a major source of income and food for developing nations. With more frequent drought and increasing scarcity of arable land, more accurate land-use planning tools are needed to allocate land resources to support regional agricultural activity. To address this need, we created Land Capability Classification (LCC) system maps using data from two digital soil maps, which were compared with measurements from 1305 field sites in the Dosso region of Niger. Based on these, we developed 250 m gridded maps of LCC values across the region. Across the region, land is severely limited for agricultural use because of low available water-holding capacity (AWC) that limits dry season agricultural potential, especially without irrigation, and requires more frequent irrigation where supplemental water is available. If the AWC limitation is removed in the LCC algorithm (i.e., simulating the use of sufficient irrigation or a much higher and more evenly distributed rainfall), the dominant limitations become less severe and more spatially varied. Finally, we used additional soil fertility data from the field samples to illustrate the value of collecting contemporary data for dynamic soil properties that are critical for crop production, including soil organic carbon, phosphorus and nitrogen.

Sucrose accumulation in sugarcane is influenced by temperature and genotype through the carbon source - sink balance

2010 ◽  
Vol 61 (2) ◽  
pp. 111 ◽  
Author(s):  
N. G. Inman-Bamber ◽  
G. D. Bonnett ◽  
M. F. Spillman ◽  
M. H. Hewitt ◽  
D. Glassop
Keyword(s):  
Water Stress ◽  
Molecular Techniques ◽  
Clonal Variation ◽  
Sink Strength ◽  
Extension Rate ◽  
Cool Temperature ◽  
Sucrose Accumulation ◽  
Temperature Regimes ◽  
New Research ◽  
Source Sink

While substantial effort has been expended on molecular techniques in an attempt to break through the apparent ceiling for sucrose content (SC) in sugarcane stalks, molecular processes and genetics limiting sucrose accumulation remain unclear. Our own studies indicate that limiting expansive growth with water stress will enhance sucrose accumulation in both low- and high-sucrose clones. Sucrose accumulation was largely explained (72%) by an equation with terms for photosynthesis, plant extension rate (PER), and plant number. New research was conducted to determine if this simple model stands when using temperature rather than water stress to perturb the source–sink balance. We also applied a thinning treatment to test the proposal implicit in this equation that SC will increase if competition between plants for photo-assimilate is reduced. Four clones from a segregating population representing extremes in SC were planted in pots and subjected to warm and cool temperature regimes in a glasshouse facility. A thinning treatment was imposed on half the pots by removing all but 6 shoots per pot. Temperature as a means of reducing sink strength seemed initially to be more successful than water regime because PER was 43% lower in the cool than in the hot regime while photosynthesis was only 14% less. PER was a good indicator of dry matter allocation to expansive growth, limited by water stress but not by temperature, because stalks tended to thicken in low temperature. Thinning had little effect on any of the attributes measured. Nevertheless the clonal variation in plant numbers and the response of PER to temperature helped to explain at least 69% of the variation in sucrose accumulation observed in this experiment. Thus the earlier model for sucrose accumulation appeared to be valid for the effect on sucrose accumulation of both temperature and water stress on the source–sink balance. The next step is to include internodes in models of assimilate partitioning to help understand the limiting steps in sucrose accumulation from the basics of source–sink dynamics.

scholarly journals Phosphorus as a mitigator of the effects of water stress on the growth and photosynthetic capacity of tropical C4 grasses

2016 ◽  
Vol 38 (3) ◽  
pp. 363 ◽  
Author(s):  
Frank Akiyoshi Kuwahara ◽  
Gustavo Maia Souza ◽  
Kezia Aparecida Guidorizi ◽  
Ciniro Costa ◽  
Paulo Roberto de Lima Meirelles
Keyword(s):  
Water Stress ◽  
Crop Production ◽  
Photosynthetic Capacity ◽  
Panicum Maximum ◽  
P Deficiency ◽  
Tropical Grasses ◽  
Tropical Forage ◽  
Productive Potential ◽  
Urochloa Decumbens ◽  
Urochloa Brizantha

Water deficiency during the dry seasons influences the relationship between water and gas exchange in tropical grasses, reducing their productive potential. In addition, the phosphorus (P) deficiency Brazilian soils adds to the set of factors limiting crop production. In this context, the objective of this study was to evaluate the responses of different tropical forage species to phosphorus supplementation as mitigating the damage caused by water stress. Seeds of Urochloa brizantha cv. MG-4, Urochloa decumbens cv. Basilisk, Panicum maximum cv. Áries, Panicum maximum cv. Tanzânia and Paspalum atratum cv. Pojuca were germinated in pots containing 10 liters of red-yellow Acrisol type soil. Experiments were conducted by combining levels of phosphorus, 8,0 and 100,0 mg of P dm-3, with two irrigation regimes, 100 and 40% replacement of transpired water. The biometric parameters, photosynthetic capacity, leaf water potential and soil chemical characteristics were evaluated, and the data was submitted to analysis of variance (ANOVA, p < 0.05), and subsequently the means were compared using a Tukey test (p < 0.05). The results showed for tropical grasses grown under water stress, there is a clear mitigating effect of phosphorus supplementation, especially on the maintenance of biomass growth. 

scholarly journals "Listen to the Trees!" A tribute to the father of modern cavitation research, Professor John Milburn, on the 20th anniversary of his untimely death

2017 ◽  
Vol 4 ◽  
pp. e005
Author(s):  
Virginia Gai Williamson
Keyword(s):  
Water Stress ◽  
New England ◽  
Botany Department ◽  
Stress Studies ◽  
Glass Tubes ◽  
20Th Anniversary ◽  
Using Data ◽  
The Many ◽  
The University ◽  
Lateral Thinking

Over the last 35 years, the study of cavitation in plants has become an accepted and important component of the water stress studies performed by plant physiologists. Although the existence of cavitation had been known since Berthelot’s (1850) pioneering work on the tensile strength of water in glass tubes, the tensions at which it occurred in such systems were far more negative than were considered likely to occur in plants. It is to the late Professor John Milburn’s sharp observational powers, lateral thinking and problem-solving approach — illustrated by his pioneering detection of cavitation in plants — that we owe today’s field of cavitation research. John Milburn was constantly thinking of new ways to approach and solve plant physiological problems. In 1966, Milburn and Johnson published their seminal work on the occurrence of cavitation in plants, using data collected via a record player needle and an amplifier. After the invention of the Scholander pressure chamber (Scholander et al. 1965), it became possible to measure easily the xylem pressures at which plants cavitated. Milburn and McLaughlin (1974) found that such pressures were within the physiological ranges that plants experienced and so the phenomenon of cavitation in plants under stress became a fruitful field of research. Professor John Milburn was tragically killed in a flying accident in 1997. The premature loss of such a great scientist, aged only 60, was felt keenly in the Botany Department of the University of New England, Armidale, Australia, where he had been a Professor for 16 years, and also around the world. This article is a tribute to Professor John Milburn, encompassing several of his key discoveries (a rare recording of the sound of cavitation occurring in the audible range is included in this tribute), as well as some of the many aspects of the man. It is timely, on the 20th anniversary of his death, to remind ourselves that today’s experimental water stress research would be the poorer without John Milburn’s pioneering work.

scholarly journals Quantifying the Impacts of Compound Extremes on Agriculture and Irrigation Water Demand

2020 ◽  
Author(s):  
Iman Haqiqi ◽  
Danielle S. Grogan ◽  
Thomas W. Hertel ◽  
Wolfram Schlenker
Keyword(s):  
Heat Stress ◽  
Water Stress ◽  
Irrigation Water ◽  
Water Demand ◽  
Crop Production ◽  
Crop Yields ◽  
Fold Increase ◽  
The United States ◽  
Food Prices ◽  
Irrigation Water Demand

Abstract. Agricultural production and food prices are affected by hydroclimatic extremes. There has been a large literature measuring the impacts of individual extreme events (heat stress or water stress) on agricultural and human systems. Yet, we lack a comprehensive understanding of the significance and the magnitude of the impacts of compound extremes. Here, we combine a high-resolution weather product with fine-scale outputs of a hydrological model to construct functional indicators of compound hydroclimatic extremes for agriculture. Then, we measure the impacts of individual and compound extremes on crop yields focusing on the United States during the 1981–2015 period. Supported by statistical evidence, we confirm that wet heat is more damaging than dry heat for crops. We show that the average damage from heat stress has been up to four times more severe when combined with water stress; and the value of water experiences a four-fold increase on hot days. In a robust framework with only a few parameters of compound extremes, this paper also improves our understanding of the conditional marginal value (or damage) of water in crop production. This value is critically important for irrigation water demand and farmer decision-making – particularly in the context of supplemental irrigation and sub-surface drainage.

scholarly journals Weather Differentials and Discount Rate Impact on Farmers’ Net Revenue: Modeling Results from Ghanaian Data Focusing on Different Agro-Climatic Zones

2021 ◽  
pp. 2150012
Author(s):  
Isaac Dasmani ◽  
Samuel K. N. Dadzie
Keyword(s):  
Climate Change ◽  
Soil Fertility ◽  
Discount Rate ◽  
Crop Production ◽  
Critical Issue ◽  
Management Policy ◽  
Negative Effects ◽  
Climatic Zones ◽  
Net Revenue ◽  
Using Data

In most developing countries, climate variabilities and discount rate played an integral role in the decision-making of farmers, which mostly affect their net revenue. Our study employs Ricardian models to empirically verify this hypothesis using data collected from three major agro-climatic zones in Ghana. We particularly estimated the comparative effect of climate change variability, discount rate, and soil fertility; due to trade-off effect of certain farm practices in response to climate change across major climatic zones and also the fact that discount rate becomes an extremely critical issue in formulating and evaluating conservation and management policy to address climate change. The result indicates that discount rate has a positive and significant effect on the farmers’ net revenue. Further, effect of changes in temperature on food crop production and hence net revenue is more felt in the forest and savannah zones. On the other hand, an increase in rainfall has significant negative effects on crop net revenues and whole-farm net revenue, but a positive effect on net revenue of farmers in the savannah zone. We also found a significant increase in soil fertility to increase crop net revenues.

scholarly journals How much information can be obtained from tracking the position of the leading edge in a scratch assay?

2014 ◽  
Vol 11 (97) ◽  
pp. 20140325 ◽  
Author(s):  
Stuart T. Johnston ◽  
Matthew J. Simpson ◽  
D. L. Sean McElwain
Keyword(s):  
Cell Motility ◽  
Leading Edge ◽  
Automated Image Analysis ◽  
Cell Counting ◽  
Cell Labelling ◽  
Scratch Assay ◽  
Short Period ◽  
Using Data ◽  
Short Time ◽  
Non Destructive

Moving cell fronts are an essential feature of wound healing, development and disease. The rate at which a cell front moves is driven, in part, by the cell motility, quantified in terms of the cell diffusivity D , and the cell proliferation rate λ . Scratch assays are a commonly reported procedure used to investigate the motion of cell fronts where an initial cell monolayer is scratched, and the motion of the front is monitored over a short period of time, often less than 24 h. The simplest way of quantifying a scratch assay is to monitor the progression of the leading edge. Use of leading edge data is very convenient because, unlike other methods, it is non-destructive and does not require labelling, tracking or counting individual cells among the population. In this work, we study short-time leading edge data in a scratch assay using a discrete mathematical model and automated image analysis with the aim of investigating whether such data allow us to reliably identify D and λ . Using a naive calibration approach where we simply scan the relevant region of the ( D , λ ) parameter space, we show that there are many choices of D and λ for which our model produces indistinguishable short-time leading edge data. Therefore, without due care, it is impossible to estimate D and λ from this kind of data. To address this, we present a modified approach accounting for the fact that cell motility occurs over a much shorter time scale than proliferation. Using this information, we divide the duration of the experiment into two periods, and we estimate D using data from the first period, whereas we estimate λ using data from the second period. We confirm the accuracy of our approach using in silico data and a new set of in vitro data, which shows that our method recovers estimates of D and λ that are consistent with previously reported values except that that our approach is fast, inexpensive, non-destructive and avoids the need for cell labelling and cell counting.

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