Modeling the effect of erosion on crop production

1987 ◽  
Vol 24 (4) ◽  
pp. 787-797 ◽  
Author(s):  
P. Todorovic ◽  
J. Gani

This paper is concerned with a model for the effect of erosion on crop production. Crop yield in the year n is given by X(n) = YnLn, where is a sequence of strictly positive i.i.d. random variables such that E{Y1} <∞, and is a Markov chain with stationary transition probabilities, independent of . When suitably normalized, leads to a martingale which converges to 0 almost everywhere (a.e.) as n → ∞. In addition, for large n, the distribution of Ln is approximately lognormal. The conditional expectations and probabilities of , given the past history of the process, are determined. Finally, the asymptotic behaviour of the total crop yield is discussed. It is established that under certain regularity conditions Sn converges a.e. to a finite-valued random variable S whose Laplace transform can be obtained as the solution of a Volterra-type linear integral equation.

1987 ◽  
Vol 24 (04) ◽  
pp. 787-797 ◽  
Author(s):  
P. Todorovic ◽  
J. Gani

This paper is concerned with a model for the effect of erosion on crop production. Crop yield in the year n is given by X(n) = YnLn, where is a sequence of strictly positive i.i.d. random variables such that E{Y 1} &lt;∞, and is a Markov chain with stationary transition probabilities, independent of . When suitably normalized, leads to a martingale which converges to 0 almost everywhere (a.e.) as n → ∞. In addition, for large n, the distribution of Ln is approximately lognormal. The conditional expectations and probabilities of , given the past history of the process, are determined. Finally, the asymptotic behaviour of the total crop yield is discussed. It is established that under certain regularity conditions Sn converges a.e. to a finite-valued random variable S whose Laplace transform can be obtained as the solution of a Volterra-type linear integral equation.


1992 ◽  
Vol 29 (4) ◽  
pp. 861-868 ◽  
Author(s):  
Y. H. Wang

In this paper, we consider kth-order two-state Markov chains {Xi} with stationary transition probabilities. For k = 1, we construct in detail an upper bound for the total variation d(Sn, Y) = Σx |𝐏(Sn = x) − 𝐏(Y = x)|, where Sn = X1 + · ··+ Xn and Y is a compound Poisson random variable. We also show that, under certain conditions, d(Sn, Y) converges to 0 as n tends to ∞. For k = 2, the corresponding results are given without derivation. For general k ≧ 3, a conjecture is proposed.


1992 ◽  
Vol 29 (04) ◽  
pp. 861-868 ◽  
Author(s):  
Y. H. Wang

In this paper, we consider kth-order two-state Markov chains {Xi } with stationary transition probabilities. For k = 1, we construct in detail an upper bound for the total variation d(Sn, Y) = Σ x |𝐏(Sn = x) − 𝐏(Y = x)|, where S n = X 1 + · ··+ Xn and Y is a compound Poisson random variable. We also show that, under certain conditions, d(Sn, Y) converges to 0 as n tends to ∞. For k = 2, the corresponding results are given without derivation. For general k ≧ 3, a conjecture is proposed.


Author(s):  
Sujata Mulik

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. 


2021 ◽  
Vol 11 (5) ◽  
pp. 2282
Author(s):  
Masudulla Khan ◽  
Azhar U. Khan ◽  
Mohd Abul Hasan ◽  
Krishna Kumar Yadav ◽  
Marina M. C. Pinto ◽  
...  

In the present era, the global need for food is increasing rapidly; nanomaterials are a useful tool for improving crop production and yield. The application of nanomaterials can improve plant growth parameters. Biotic stress is induced by many microbes in crops and causes disease and high yield loss. Every year, approximately 20–40% of crop yield is lost due to plant diseases caused by various pests and pathogens. Current plant disease or biotic stress management mainly relies on toxic fungicides and pesticides that are potentially harmful to the environment. Nanotechnology emerged as an alternative for the sustainable and eco-friendly management of biotic stress induced by pests and pathogens on crops. In this review article, we assess the role and impact of different nanoparticles in plant disease management, and this review explores the direction in which nanoparticles can be utilized for improving plant growth and crop yield.


2021 ◽  
Vol 13 (9) ◽  
pp. 1614
Author(s):  
Boyi Liang ◽  
Timothy A. Quine ◽  
Hongyan Liu ◽  
Elizabeth L. Cressey ◽  
Ian Bateman

To meet the sustainable development goals in rocky desertified regions like Guizhou Province in China, we should maximize the crop yield with minimal environmental costs. In this study, we first calculated the yield gap for 6 main crop species in Guizhou Province and evaluated the quantitative relationships between crop yield and influencing variables utilizing ensembled artificial neural networks. We also tested the influence of adjusting the quantity of local fertilization and irrigation on crop production in Guizhou Province. Results showed that the total yield of the selected crops had, on average, reached over 72.5% of the theoretical maximum yield. Increasing irrigation tended to be more consistently effective at increasing crop yield than additional fertilization. Conversely, appropriate reduction of fertilization may even benefit crop yield in some regions, simultaneously resulting in significantly higher fertilization efficiency with lower residuals in the environment. The total positive impact of continuous intensification of irrigation and fertilization on most crop species was limited. Therefore, local stakeholders are advised to consider other agricultural management measures to improve crop yield in this region.


2020 ◽  
Vol 2 ◽  
Author(s):  
Nathalie Colbach ◽  
Sandrine Petit ◽  
Bruno Chauvel ◽  
Violaine Deytieux ◽  
Martin Lechenet ◽  
...  

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.


Soil Research ◽  
2016 ◽  
Vol 54 (5) ◽  
pp. 604 ◽  
Author(s):  
G. D. Schwenke ◽  
B. M. Haigh

Summer crop production on slow-draining Vertosols in a sub-tropical climate has the potential for large emissions of soil nitrous oxide (N2O) from denitrification of applied nitrogen (N) fertiliser. While it is well established that applying N fertiliser will increase N2O emissions above background levels, previous research in temperate climates has shown that increasing N fertiliser rates can increase N2O emissions linearly, exponentially or not at all. Little such data exists for summer cropping in sub-tropical regions. In four field experiments at two locations across two summers, we assessed the impact of increasing N fertiliser rate on both soil N2O emissions and crop yield of grain sorghum (Sorghum bicolor L.) or sunflower (Helianthus annuus L.) in Vertosols of sub-tropical Australia. Rates of N fertiliser, applied as urea at sowing, included a nil application, an optimum N rate and a double-optimum rate. Daily N2O fluxes ranged from –3.8 to 2734g N2O-Nha–1day–1 and cumulative N2O emissions ranged from 96 to 6659g N2O-Nha–1 during crop growth. Emissions of N2O increased with increased N fertiliser rates at all experimental sites, but the rate of N loss was five times greater in wetter-than-average seasons than in drier conditions. For two of the four experiments, periods of intense rainfall resulted in N2O emission factors (EF, percent of applied N emitted) in the range of 1.2–3.2%. In contrast, the EFs for the two drier experiments were 0.41–0.56% with no effect of N fertiliser rate. Additional 15N mini-plots aimed to determine whether N fertiliser rate affected total N lost from the soil–plant system between sowing and harvest. Total 15N unaccounted was in the range of 28–45% of applied N and was presumed to be emitted as N2O+N2. At the drier site, the ratio of N2 (estimated by difference)to N2O (measured) lost was a constant 43%, whereas the ratio declined from 29% to 12% with increased N fertiliser rate for the wetter experiment. Choosing an N fertiliser rate aimed at optimum crop production mitigates potentially high environmental (N2O) and agronomic (N2+N2O) gaseous N losses from over-application, particularly in seasons with high intensity rainfall occurring soon after fertiliser application.


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