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Unpredictable Nature of Environment on Nitrogen Supply and Demand
Author(s) -
Raun William R.,
Dhillon Jagmandeep,
Aula Lawrence,
Eickhoff Elizabeth,
Weymeyer Gwen,
Figueirdeo Bruno,
Lynch Tyler,
Omara Peter,
Nambi Eva,
Oyebiyi Fikayo,
Fornah Alimamy
Publication year - 2019
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2019.04.0291
Subject(s) - randomness , entropy (arrow of time) , yield (engineering) , nitrogen , crop yield , mathematics , environmental science , agronomy , statistics , chemistry , biology , physics , thermodynamics , organic chemistry
The second law of thermodynamics states that entropy or randomness in a given system will increase with time. This is shown in science, where more and more biological processes have been found to be independent. Contemporary work has delineated the independence of yield potential (YP0) and nitrogen (N) response in cereal crop production. Each year, residual N in the soil following crop harvest is different. Yield levels change radically from year to year, a product of an ever‐changing and unpredictable/random environment. The contribution of residual soil N for next years’ growing crop randomly influences N response or the response index (RI). Consistent with the second law of thermodynamics, where it is understood that entropy increases with time and is irreversible, biological systems are expected to become increasingly random with time. Consequently, a range of different biological parameters will influence YP0 and RI in an unrelated manner. The unpredictable nature that environment has on N demand, and the unpredictable nature that environment has on final grain yield, dictate the need for independent estimation of multiple random variables that will be used in mid‐season biological algorithms of the future. Core Ideas Randomness in biological systems is increasing. Many biological processes are independent. Yield levels change from one year to the next. Environments change over time and are random. Optimum fertilizer nitrogen rates change dramatically from year to year.