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Estimating Field-Level Rotations as Dynamic Cycles
Abstract
Crop rotation systems are an important part of agricultural production for managing pests, diseases, and soil fertility. Recent interest in sustainable agriculture focuses on low input-use practices which require knowledge of the underlying dynamics of production and rotation systems. Policies to limit chemical application depending on proximity to waterways and flood management require field-level data and analysis. Additionally, many supply estimates of crop production omit the dynamic effects of crop rotations. We estimate a dynamic programming model of crop rotation which incorporates yield and cost intertemporal effects in addition to field-specific factors including salinity and soil quality. Using an Optimal Matching algorithm from the Bioinformatics literature, we determine empirically observed rotations using a geo-referenced panel dataset of 14,000 fields over 13 years. We estimate the production parameters which satisfy the Euler equations of the field-level rotation problem and solve an empirically observed four-crop rotation.
... In contrast, orchard areas consistently increased from 2018/2019 to 2020/2021, which was attributed to new olive plantations reported by farmers over the past 5 years. The crop rotations observed were described in the literature as arising from complex interactions between socioeconomic factors, agroecosystem processes, pest management, and policy and regulation (MacEwan & Howitt, 2019). ...
Due to Mediterranean climatic conditions, traditional pluvial agrosystems are widespread along the southern Mediterranean shore and were previously thought to have minimal impact on surface water resources due to low agricultural input levels. However, current pesticide applications are now considered to contribute significantly to the contamination of surface water resources, which may result in severe impacts on biodiversity and the environment. This study examined the presence and mobility risk of pesticides in the surface waters of the Lebna watershed in northeastern Tunisia, a rainfed Mediterranean agricultural region. Water samples were collected from eight hilly reservoirs and the Lebna dam over three farming seasons (2017–2018, 2019–2020, and 2020–2021) and analyzed for 469 pesticide active ingredients (PAIs). According to the field questionnaire, local farmers used 44 PAIs, including 15 herbicides, 21 fungicides, and 8 insecticides. Seventeen pesticide molecules were detected, with glyphosate (1.73 µg L⁻¹) and 2,4-D (0.23 µg L⁻¹) being the most prevalent. Despite toxicity indexes, which classify a threat of pesticides as low to moderate, their concentrations may now exceed European standards for drinking water and endanger aquatic life. According to the Pesticide Impact Rating Index (PIRI), PAIs can be organized into three mobility risk categories: medium to high for 2,4-D and glyphosate, low for five PAIs, and very low for 13 undetected PAIs. This work provides the first assessment of pesticide contamination in surface waters of the Cap Bon region, raising concerns about water quality in a low-input agrochemical system and increasing interest in similar contexts.
... Sowing the same crop for years results in soil erosion and also reduces the fertility of the soil. So the rotation of crops is necessary for high yielding [53]. Growing one crop absorbs the nutrients from the soil, growing different crops in the next season will return the nutrients to the soil which reduces the soil erosion. ...
Recently, technologies like Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and the Internet of Things (IoT) have emerged rapidly in various domains. It has also emerged in the field of agriculture. In agriculture, certain activities are difficult for a farmer to do manually, such as initial stage disease identification, soil control, yield prediction, etc. Thus, the use of emerging technologies in agriculture is quite useful in so many aspects. In this paper, an extensive survey is done by reviewing papers that have applications of AI, ML, DL, and IoT in agriculture. This survey examined the different applications of these technologies and the various methods that can be used to increase productivity in agriculture. The main objective of this paper is to explore the applications of the above mentioned technologies in various fields of agriculture. This survey explored how these technologies could be used to solve some of the major issues such as Crop quality, overuse of fertilizers and pesticides, disease detection in plants, etc. This research work provides a valuable reference to researchers to understand the major issues faced by the farmers and the role of the above emerging technologies in implementing smart agriculture in the existing literature.
Optimal crop choice and fertilizer applications depend on the stochastic dynamics of commodity prices, fertilizer prices, and the agronomic effects of rotation versus monoculture. The efficient decision rule accounts for real option values associated with maintaining land disposition in an environment with highly uncertain future prices and irreversible past planting decisions. We parameterize a baseline model for a representative acre in Iowa and compare the model's predictions and profits to relatively naive, shorter horizon decision rules, and a field managed with optimal fertilizer applications conditional on corn and soybeans always being rotated. We also examine the effects of a permanently larger premium on corn prices relative to soybean prices, which has been observed in locations near recently established ethanol plants. We then compare the various decision rules to actual crop choices in a panel of over 6,500 Iowa plots during 1979–2007. As compared to less forward-looking objectives, we find the agronomic benefits of rotations coupled with real option values can lead to a more inelastic response of planting decisions to both transitory and permanent price changes. Always rotating, regardless of prices, is close to optimal, but so are shorter-horizon objectives. One implication is that reduced corn monoculture and fertilizer application rates might be implemented with modest incentive payments of $4 per acre or less.
Key words
Crop rotations, Dynamic programming, option value, supply response, uncertainty
Key words
Q11 Q12
Three independent approaches were applied to estimate annual evapotranspiration (ET) for the Imperial Irrigation District of Southern California for the 1998 water year (October 1997 to September 1998). These approaches included remote sensing (Surface Energy Balance Algorithm for Land, SEBAL ®), a district-wide water balance with ET as the closure term, and a dual crop coefficient approach based on the procedures of FAO Irrigation and Drainage Paper No. 56 with refinements to account for field-specific irrigation frequency. Differences between annual ET from each independent ET estimation approach are evaluated relative to estimated confidence intervals.
Inagricultural production, a stylized fact known as the rotationeffect says crop rotations generate higher yields or productivitythan identical crops grown in isolated monocultures. This paperdevelops a dynamic data envelopment analysis (DEA) model of cropproduction that accounts for the rotation effect. The model isapplied to data from an experimental farm in Pennsylvania toinvestigate the role soil capital plays in observed productivitygrowth and the rotation effect.
An attempt is made to determine the logically consistent rules for selecting a vector from any feasible set defined by linear constraints, when either all n-vectors or those with positive components or the probability vectors are permissible. Some basic postulates are satisfied if and only if the selection rule is to minimize a certain function which, if a "prior guess" is available, is a measure of distance from the prior guess. Two further natural postulates restrict the permissible distances to the author's f-divergences and Bregman's divergences, respectively. As corollaries, axiomatic characterizations of the methods of least squares and minimum discrimination information are arrived at. Alternatively, the latter are also characterized by a postulate of composition consistency. As a special case, a derivation of the method of maximum entropy from a small set of natural axioms is obtained.
We describe a general strategy to analyze sequence data and introduce SQ-Ados, a bundle of Stata programs implementing the proposed strategy. The programs include several tools for describing and visualizing sequences as well as a Mata library to perform optimal matching using the Needleman – Wunsch algorithm. With these programs Stata becomes the first statistical package to offer a complete set of tools for sequence analysis. Copyright 2006 by StataCorp LP.
Maximum entropy is presented as a universal method of finding a “best” positive distribution constrained by incomplete data. The generalised entropy ∑(f - m - f log(f/m))) is the only form which selects acceptable distributions f in particular cases. It holds even if f is not normalised, so that maximum entropy applies directly to physical distributions other than probabilities. Furthermore, maximum entropy should also be used to select “best” parameters if the underlying model m has such freedom.
Many farming situations involve crop rotations. This has led to many farm linear programming models which explicitly include
crop rotation considerations. However, for the most part crop rotations have been modeled using explicit predetermined rotations.
An attempt is made to relax this requirement, allowing the model to determine freely the optimal long-run rotation. The approach
is tested on a Northeastern Oregon farm. Data are developed using regression analysis of historical cropping records. Risk-neutral
and risk-averse formulations are tested. The model develops a plausible set of rotations and does not require the rotations
to be predetermined.
Bell System Technical Journal, also pp. 623-656 (October)
An inversion procedure which provides the most conservative inference for an unknown function in terms of partial data is discussed on the basis of information theoretic considerations. The method is based on the procedure of maximal entropy, but is not limited to the estimation of unknown probabilities. Rather, inductive inferences can be drawn regarding the values of general (if necessary, dimension-bearing) variables. The solution of an inversion problem using data linear in the unknown function is discussed in detail and explicit results are obtained. For every class of problems with common symmetry properties, the general algorithm can be reduced to a more direct procedure. When the data consist of average values for an unknown distribution, the general approach is in the spirit of the Darwin-Fowler method, while the reduced route is the procedure of maximal entropy ('method of most probable distribution') as usually employed in statistical mechanics. Other classes of problems discussed include the representation of an unknown function in a complete orthonormal basis using as input a partial set of expansion coefficients, and the inference of line shapes and power spectra.
This study evaluates quantitatively the effect of three policies (payments for cropland retirement, fertilizer use taxes and payments for crop rotations) on agricultural land use in the upper Mississippi River basin. This is done by estimating two logit models of land use decisions using data from the 1982, 1987, 1992 and 1997 Natural Resource Inventories. The models predict farmers' crop choice, crop rotation and participation in the Conservation Reserve Program (CRP) at more than 48,000 Natural Resource Inventories sites under each of the three policies. Results suggest that an increase in the CRP rental rates would significantly increase the CRP acreage, but most of the acreage increase would come initially from less fertilizer intensive crops. In contrast, a fertilizer use tax would significantly reduce acreage planted to more fertilizer-intensive crops, and thus would likely be cost effective for reducing agricultural chemical use and pollution. Although an incentive payment for a corn-soybean rotation would raise acreage of this rotation and reduce the acreage of continuous corn, the acreage response is in general quite inelastic.
Farmers' management practices can have a significant effect on agricultural pollution. Past research has analyzed factors
influencing adoption of a single management practice. But often adoption decisions about many practices are made simultaneously,
which suggests use of a polychotomous-choice model to analyze decisions. Such a model is applied to the choice of alternative
management practices on cropland in the Central Nebraska Basin and controlled for self-selection and the interaction between
alternative practices. The results of the choice model are used to estimate the economic and environmental effects of adopting
alternative combinations of management practices.
The consequences of carryover for the optimal application of fertilizer are considered using dynamic programming. The conclusions are relevant for the further problem of deciding how many grain crops to harvest from grain sorghum plants grown in a tropical environment. Dynamic programming is also used for solving this problem for the Ord River Valley, and takes account of the interrelations between season and crop cycle number. Data were obtained from investigations conducted in the area. 1973 The Australian Agricultural Economics Society
The growth in conservation programs has created a need for modeling frameworks capable of measuring microlevel behavioral responses and macrolevel landscape changes. This paper presents an empirical model that predicts farmers' production practices and the resulting levels of agricultural runoffs at more than 42,000 agricultural sites in the upper-Mississippi river basin under alternative conservation policies. Results suggest that payments for conservation tillage and crop rotations increase the use of these conservation practices. However, the acreage response is inelastic and the programs are not likely to be cost effective on their own for addressing hypoxia problem in the Gulf of Mexico. Copyright 2004, Oxford University Press.
Many important problems in agricultural and natural resource economics concern an intertemporal choice between alternate dynamic systems. This significance has motivated a theoretical literature generalizing the necessary conditions of Optimal Control Theory to multiple-phase problems. However, gaining detailed insight into their practical management is difficult because general numerical solution methods are not available. This paper resolves this deficiency through the development of a flexible and efficient computational algorithm based on a set of necessary conditions derived for finite-time, multiple-phase systems. Its effectiveness is demonstrated in an application to a nontrivial crop rotation problem.
A socially efficient agricultural policy would provide incentives for farmers to supply the appropriate combination of market and nonmarket goods demanded by society (Antle and
Capalbo 2002). Ecosystem services (ES) are the most important type of public goods provided by agriculture. To support the transition from commodity-based subsidy policies
to policies based on the efficient provision of ES, policy decision makers will need to
know how to design efficient mechanisms for the provision of ES from agriculture, and will
need estimates of their environmental and economic effects. For example, the 2002 Farm Bill created the Conservation Security Program, which pays farmers who adopt environmentally beneficial practices. The ten-year costs of implementing this program were estimated to be 8.9 billion in 2004. This cost underestimation was due in part to inaccurate estimates of farmer participation
(General Accounting Office 2006). This example suggests that estimates of benefits and
costs of these policies with a reasonable degree of accuracy will be needed to facilitate the transition to policies based on provision of ES. At the same time, to be useful for policy decision making, information needs to be provided in a timely manner. Researchers will inevitably need to trade-off cost, timeliness, and accuracy in making decisions about the appropriate modeling approach.
The purpose of this paper is to present a conceptual framework for the analysis of ES
supply, and to discuss some of the data and modeling issues that arise in predicting farmers’ participation in ecosystem service contracts and the supply of ES resulting from
them. Two key features of agro-ecosystems that have been identified in the scientific literatures are the complexity of the biophysical and human environments in which they
operate, and the complexity of the ecological and economic processes governing the systems. To frame the discussion, we outline a model of the supply of ES that illustrates the
ways that spatial and system complexity can affect it. We use this model to discuss the
data and modeling issues that arise in empirical implementation. We conclude with recommendations regarding modeling strategies that can provide sufficiently accurate and timely information needed to support informed policy decision making.
This note demonstrates that a certain class of stochastic problems for determination of optimal fertilizer application rates in the presence of fertilizer carry-over can be simplified to static, certainly equivalent problems. Conditions required for certainty equivalence to hold are: (1) fertilizer carry-over is agronomically equivalent to applied fertilizer; and (2) some addition of fertilizer is optimal in every decision period. The importance of nitrogen carry-over in determining optimal fertilization rates has been increasingly recognized in the last decade. Kennedy, et al. used a deterministic dynamic programming (DP) model to determine optimal nitrogen carry-over and application rates for grain sorghum grown in a tropical environment. Assuming that carry-over was proportional to applied nitrogen plus carry-over in the previous crop year, they showed that the only relevant variable pertaining to future periods in the optimization model was the price of nitrogen in the next period. Thus, the solution to the deterministic multiperiod problem is no more difficult than comparable static problems. Characteristics of this deterministic problem were further discussed and refined by Godden and Helyar, and Kennedy. A more sophisticated nitrogen carryover study was reported by Stauber, et al. In this study they recognized the influence of precipitation during the growing season on nitrogen carry-over in grass pastures. Since they treated precipitation as
A method of deriving rules for optimal fertilizer application when there is carryover is presented. The carryover situations considered are: carryover a deterministic function of fertilizer available in the previous period; carryover a deterministic function of fertilizer applied in more than one previous period; and carryover a stochastic function of fertilizer available in the previous period. The method of derivation is more direct than an inductive one previously presented. The rules are given an economic interpretation, and the gains from using them in practice are considered.
The consequences of carryover for the optimal application of fertilizer are considered using dynamic programming. The conclusions are relevant for the further problem of deciding how many grain crops to harvest from grain sorghum plants grown in a tropical environment. Dynamic programming is also used for solving this problem for the Ord River Valley, and takes account of the interrelations between season and crop cycle number. Data were obtained from investigations conducted in the area.
A computer adaptable method for finding similarities in the amino acid sequences of two proteins has been developed. From these findings it is possible to determine whether significant homology exists between the proteins. This information is used to trace their possible evolutionary development.The maximum match is a number dependent upon the similarity of the sequences. One of its definitions is the largest number of amino acids of one protein that can be matched with those of a second protein allowing for all possible interruptions in either of the sequences. While the interruptions give rise to a very large number of comparisons, the method efficiently excludes from consideration those comparisons that cannot contribute to the maximum match.Comparisons are made from the smallest unit of significance, a pair of amino acids, one from each protein. All possible pairs are represented by a two-dimensional array, and all possible comparisons are represented by pathways through the array. For this maximum match only certain of the possible pathways must be evaluated. A numerical value, one in this case, is assigned to every cell in the array representing like amino acids. The maximum match is the largest number that would result from summing the cell values of every pathway.
We present a dynamic model of on-farm nitrogen fertilisation management that allows for a structural relationship between land allocation decisions and nitrogen carry-over from previous crops. We derive conditions for efficient inter-temporal nitrogen management in a multi-crop setting, and suggest an empirical testing procedure for crop rotation patterns based on farm-level data. Nitrogen carry-over indexes and production parameters are estimated by the Generalised Method of Moments using panel data for a sample of French farmers. Copyright 2003, Oxford University Press.
Presents a study which looked at farmers' choice of conservation, tillage, rotation and soil testing practices in the Nebraska corn area. Estimation of various combinations of the practices impact on fertilizer use, corn yield, and soil erosion; Details on a polychotomous-choice selectivity model; Factors which affect conservation practices.
A model of optimal dynamic agricultural supply is derived and fitted assuming farmers have two annual stochastic crop production
activities, a joint limitation on production capacity, interdependencies between past acreage utilization and current productivity,
and rational expectations. A five-equation specification is fitted to annual data, 1948–80. Estimated parameters are consistent
with the theory, and the model simulates well. The long-run price elasticity of corn acreage is 0.2, which is similar to those
obtained from ad hoc dynamic models, but our short-run elasticities are different.
We develop an empirically tractable model of acreage allocation decisions in which farmers consider impacts of current crop
production 00 future soil productivity. Because of the soil productivity effects, future crop prices are shown to affect current
acreage allocations. Government programs which alter farmers' expectations of future crop prices relative to current prices
also alter farmers' consideration of soil productivity effects of current acreage allocations. Reduced form and structural
versions of our model are shown to yield reasonable parameter estimates.
Land-use change is arguably the most pervasive socioeconomic force driving the change and degradation of ecological systems and wildlife habitat. This paper integrates an econometric model of land use with a species-habitat association matrix to assess the effects of land use policies on land use changes and the resulting impacts on habitat abundance for 763 terrestrial vertebrates in four western states of the United States (California, Oregon, Washington, and Idaho). Results suggest that if the goal is to protect biodiversity through habitat conservation, directly acquiring land and setting it aside for habitat preservation (e.g., by purchasing development rights) is more effective than policies that attempt to change the relative returns from different land uses.
On peut dire que le changement d'affectation des terres constitue la force socioéconomique la plus répandue entraînant la modification et la dégradation des écosystèmes et des habitats fauniques. Dans le présent article, nous avons intégré un modèle économétrique d'affectation des terres et une matrice espèces-habitats pour évaluer l'impact des politiques d'affectation des terres sur les changements d'affectation des terres et leurs répercussions sur l'abondance des habitats pour 763 vertébrés terrestres dans quatre États de l'Ouest des États-Unis (Californie, Oregon, Washington et Idaho). Si l'objectif visé est la protection de la biodiversité par la conservation des habitats, les résultats semblent indiquer que l'acquisition directe de terres en vue de les réserver pour la préservation des habitats (en faisant l'acquisition de droits d'aménagement par exemple) est plus efficace que les politiques qui tentent de modifier les rendements relatifs tirés des diverses affectations des terres.
An issue when seeking to identify rotation choice is persistence in yield-enhancement and input-saving carry-over effects. Focusing on carry-over length and the monoculture decision, we use quasi-convexity of choice functions to develop price-independent and price-dependent principles concerning rotation structure. Iowa corn-soybean rotation data suggest corn has one-year memory. For corn, soybeans in the prior year is yield increasing (16.5 bu./ac.) and nitrogen saving (51 lb./ac.). The hypothesis that soybean has two-year memory cannot be rejected. Corn in the prior year (two years) increases yield by 7 bu./ac. (11.6 bu./ac.). We simulate to find price and practice subsidy levels that support different rotations. Copyright 2006 American Agricultural Economics Association.
Land use change is the most pervasive force driving the degradation of watershed ecosystems. This article combines an econometric
model of land use choice with models of watershed health indicators to examine the effects of land use policies on watershed
ecosystems through their effect on land use. Our results suggest that incentive-based land use policies and property acquisition
programs can have relatively large positive impacts on watershed health, while policies that change the returns to land use
are less effective. The results suggest that there is potential for targeting these policies because their impacts vary across
watersheds with different land use mixes.
Lucerne (Medicago sativa L.) helps to prevent soil salinisation in the Western Australian Wheatbelt by reducing recharge to saline water tables. There is broad consensus, though, that it is not sufficiently profitable to motivate producers to plant it at the intensity at which considerable off-site benefits would be conferred. This paper employs a multiple-phase optimal control model to explore the value of this perennial pasture for the management of herbicide-resistant annual ryegrass (Lolium rigidum Gaud.) in a crop-pasture rotation, given the difficulty of observing this value in practice. The availability of selective herbicides for efficient weed control is found to determine whether or not it is profitable to adopt lucerne pasture under optimal management. Herbicide resistance requires producers to employ costly, non-selective treatments for in-crop weed control. Thus, it motivates the adoption of perennial pasture in which cost-effective forms of control can be implemented. Moreover, this result is robust to feasible changes in the current economic environment. Copyright 2008 The Author. Journal compilation 2008 Australian Agricultural and Resource Economics Society Inc. and Blackwell Publishing Asia Pty Ltd.
We argue that to support agriculture-environmental policy decision making, stakeholders need 'quantitative back-of-the-envelope' analysis that is timely and sufficiently accurate to make informed decisions. We apply this concept to the analysis of the supply of ecosystem services from agriculture. We present a spatially explicit production model and show how it can be used to derive the supply of ecosystem services in a region. This model shows that the supply of ecosystem services can be derived from the spatial distribution of opportunity cost of providing those services. We then show how this conceptual model can be used to develop a minimum-data (MD) approach to the analysis of the supply of ecosystem services from agriculture that can be implemented with the kinds of secondary data that are available in most parts of the world. We apply the MD approach to simulate the supply of carbon that could be sequestered in agricultural soils in the dryland grain-producing region of Montana. We find that the supply curve derived from the MD approach can approximate the supply curve obtained from a more elaborate model based on site-specific data, and can do so with sufficient accuracy for policy analysis. Copyright Australian Agricultural and Resource Economics Society Inc. and Blackwell Publishing Ltd 2006.
The theory of combination enterprises on individual farms
- S E Johnson
- SE Johnson