Modern Concepts & Developments in Agronomy

Journal Information
EISSN : 2637-7659
Current Publisher: Crimson Publishers (10.31031)
Total articles ≅ 132

Latest articles in this journal

Modern Concepts & Developments in Agronomy; doi:10.31031/mcda

Ted Lefroy
Modern Concepts & Developments in Agronomy, Volume 7, pp 740-741; doi:10.31031/mcda.2020.07.000667

Ted Lefroy* Adjunct Professor, Tasmanian Insitute of Agriculture, University of Tasmania, Australia *Corresponding author: Dr. Ted Lefroy, Adjunct Professor, Tasmanian Insitute of Agriculture, University of Tasmania, Researcher ID: J-7144-2014, Australia Submission: November 11, 2020Published: November 13, 2020 DOI: 10.31031/MCDA.2020.07.000667 ISSN 2637-7659Volume7 Issue 4 It is not often that an academic paper is downloaded over 600,000 times. Even rarer that one is described as ‘the scientific paper sending people into therapy’ [1]. Such is the social phenomenon triggered by the paper Deep Adaptation: A map for navigating climate tragedy [2], published privately after it was rejected by the journal Sustainability Accounting, Management and Policy [3]. What follows is an agronomist’s attempt to understand the basis for the paper’s claim that we face ‘inevitable near-term societal collapse’ due to ‘…uncontrollable levels of climate change bringing starvation, destruction, migration, disease, and war’ [1]. In the paper’s preamble we learn it resulted from a 2017 sabbatical spent reviewing the latest climate science. And in a letter to the journal editor attached as a postscript, the author responds to a reviewer who questioned whether the climate data supported the paper’s argument by stating that section is ‘…the core of the paper as everything then flows from the conclusions of that analysis’ [2]. Several aspects of that analysis warrant a closer look. First, throughout the paper the term non-linear is used to imply unstoppable or runaway climate change. Non-linear means change in the output of a system that is not proportional to change in the inputs. It implies nothing about the direction or speed of change or the feasibility of human intervention or management. When Gavin Schmidt, Director of the NASA Goddard Institute for Space Studies, was asked to comment on an earlier version he replied ‘This is nonsense. Non-linearity (which is ubiquitous) is not synonymous with ‘runaway’ climate change’. To which the author responded ‘Verdict: No clarification or correction. Adding a reference to the new findings from scientists will be useful in future publications’ [4]. The new findings included in the revised version are drawn from an article on climate tipping points [5] which, the paper claims, indicate that we ‘have tipped into self-reinforcing and irreversible change’ [2]. What those authors actually said was ‘If damaging tipping cascades can occur and a global tipping point cannot be ruled out, then this is an existential threat to civilization’ [5]. The qualifier ‘if’ is important as the phenomenon of tipping cascades is hypothetical, which is why the paper was published as a comment, not a research paper. On global tipping points, others have argued ‘The global human enterprise is driving large-scale changes in most components of the Earth system, but in a haphazard fashion, with responses often being weakly connected or transmitted slowly at a cross-continental scale’ making it ‘…implausible that the planet, or indeed most of its component systems, are primed to tip irreversibly to a radically different state that is inhospitable’ [6]. Second, the prediction that global tipping points will lead to inevitable near term societal collapse rests largely on two phenomenon, Arctic ice melt and methane release. Both rely on a few, selected sources. In the case of the Arctic ice melt, the work of one scientist whose predictions have not eventuated [7]. In the case of methane release, it relies on the clathrate gun hypothesis first proposed in 2003 that has since been challenged in multiple reviews [8]. Third on crop yields, the paper notes that the IPCC has estimated that climate change has reduced growth in crop yields by 1-2% per decade over the past century. This needs to be seen in the context of yield increases in the major crops of 300-800% over the same period. In the UK ~300% for oats and barley, ~400% for wheat and potatoes and ~800% for sugar beet; in the USA, ~500% for corn [9]. Climate change is real and is having an impact on agriculture, but the major challenge now is not yield but equitable access. The major challenge for the future is declining investment, particularly in plant breeding and agronomy. Fourth, on declining fish stocks, the paper states that ocean acidification ‘degrades the base of the marine food web, thereby reducing the ability of fish populations to reproduce themselves across the globe’ [2]. The paper cited in support of this statement mentions acidification once, in the first paragraph of the introduction, as a process that ‘may impact the productivity of fish stock’ [10]. Acidification is not referred to again in the paper and is not implicated in reduced recruitment capacity. What this paper does say is that recruitment capacity (the ability of stocks to produce surviving offspring) has been altered by 3% of the historical maximum per decade by both environmental changes and overfishing, with overfishing more significant than environmental factors (sea surface temperature and chlorophyll concentration as a surrogate for phytoplankton biomass). Ocean acidification does affect phytoplankton, but this is not discussed in this paper. Fifth, the paper claims rates of sea level rise ‘may soon become exponential’ [2]. The source is a University press release about a study of relative sea level rise at selected locations in North America, so changes in both sea level and land surface, which does not mention exponential rise. Finally, there is the alarming claim ‘About half of all plant and animal species in the world’s most biodiverse places are at risk of extinction due to climate change’ [2]. The source is a press...
Aristeidis Georgakis
Modern Concepts & Developments in Agronomy, Volume 7, pp 694-697; doi:10.31031/mcda.2020.07.000654

Aristeidis Georgakis* and Georgios Stamatellos Laboratory of Forest Biometrics, School of Forestry and Natural Environment, Aristotle University of Thessaloniki, Thessaloniki, Greece *Corresponding author: Aristeidis Georgakis, Laboratory of Forest Biometrics, School of Forestry and Natural Environment, Aristotle University of Thessaloniki, Thessaloniki, Greece Submission: June 23, 2020Published: August 18, 2020 DOI: 10.31031/MCDA.2020.07.000654 ISSN 2637-7659Volume7 Issue 1 The sampling design is a crucial topic that would be considered in Small Area Estimation (SAE). Applications of sampling designs presented in Forest Inventories (FIs) for SAE, with the two-phase sampling to have the most references. Eventually, FIs that are applied for SAE is an open research topic. An important contribution to this topic would be the comparison and the optimization of sampling designs that aims to improve SAE in FIs. Keywords: Survey sampling; SAE procedure;Domain;Forest management unit;Auxiliary information Forest inventories (FIs), based on a geographical scale, can be distinguished in National Forest Inventories (NFIs) and Management Forest Inventories (MFIs), that provide information for policy-making or local decision-making correspondingly. The initial objective of sampling design in FIs is to produce information (estimates) for one or more population parameters (variables of interest) of a targeted population, after selecting the proper formulas (estimators) [1,2] and the second aim is to provide suitable statistics for subpopulations, the so-called “domains” or “small areas” [3]. The last objective of sampling design (survey sampling) can be achieved through small area estimation (SAE) techniques. There is an increasing need to use national or regional inventories for local estimations [4], particularly reliable forest attribute information is needed at different geographical scales with different requirements per scale. “SAE techniques address the situation where the number of samples within a small area is too small to provide reliable estimates for that unit” [5]. A small area characterized by small or even null sample size [6]. In the case of a small area, where direct estimations are not possible and when the sample size cannot be increased, indirect estimators (SAE technique) can be applied, “borrowing strength” from other domains or periods and combining the terrestrial information with the extensive use of auxiliary information such as derived from remotely sensed variables [4,6-8]. Borrowing strength is the basic idea of SAE, where models are fitted globally and applied locally, albeit with minor modifications [9]. Although FIs depicts the state of forests through a plethora of target variables, in SAE the most important quantitative variables of interest are the growing stock volume and the aboveground forest biomass. The basic prerequisite of SAE implementation is the acquisition of auxiliary variables (Figure 1). The main auxiliary data/information are satellite imagery and 3-D data from LiDAR or airborne laser scanning (ALS)and photogrammetry. The most critical step for having small area statistics is the selection of suitable estimation procedure under the existing (usually) sampling design. The problem of small area statistics starts when the original sample design aims to the estimations of population totals (mean and variance) for a variable of interest and not in the small area of interest such as management units (eg. forest stands or compartments). What sample design can be used for SAE of small domains in the design phase, is an open question and a basic issue that should be considered [3]. In this paper, we will present existing sampling designs that support effectively the SAE procedure and we will discuss restrictions and opportunities about the implementation in FIs. Sampling designs in SAE for FIs Knowing the variable of interest, having defined the small area of interest and having available suitable auxiliary information with existing terrestrial data, the last “two steps” (Figure 1) for an effective “small area estimation strategy” are the sampling design and the selection of proper statistical modelling (estimation design) [3,10,11]. From another perspective, the last steps of design and estimation can be considered inseparable [6]. The research of SAE literature is broader out of the forestry borders, as well as, on sampling designs for SAE purposes. In socioeconomic fields, various sampling designs examined parallelly with different types of estimation strategies for SAE implementation [3,10-12]. Generally, there is a gap of this kind of research in forestry literature. Some exception is the work of [13] who compared and tested different sizes of sampling grids for SAE of forest area and the growing stock volume of temperate mixed forests. The following sampling designs have been applied to SAE in FIs. The common component of all SAE applications is the use of auxiliary information that is exhaustive or partial exhaustive (for the whole population). Double-Sampling or two-phase is one of the most frequently used sampling design, characterized by its cost-efficiency for inventories in large remote forest areas [4,5,7,9,14-16], (section 6.3), three-phase sampling in smaller extend [5,17,18], stratified systematic (cluster) sampling [19], stratified random sampling [20], and post-stratification [15,21-23] for design-unbiased estimates (mean and variance) when a reasonable amount of field plots is needed in a small area [24]. Systematic or grid (sample locations on a regular grid) is one of the most common sampling (including cluster) scheme in MFIs and especially in NFIs. Correspondingly the majority of SAE bibliography utilizes NFI data to downscale the estimates to finer resolutions like territories, forest districts, or domains [5,13,25]. In small scale MFIs, systematic sampling...
Sarmiento Miguel, Bruno Carlos, Guerrero Maldonado Natalia
Modern Concepts & Developments in Agronomy, Volume 6, pp 657-659; doi:10.31031/mcda.2020.06.000642

This article presents the results of studies carried out in Santiago del Estero, Argentina that assessed people’s willingness to pay (WTP) and willingness to accept (WTA) for useful plants conservation using the Contingent Valuation Methodology (CVM). The WTP of residents in rural areas in Santiago del Estero, Argentina was researched. In this study residents expressed that medicinal, food and dye plants are very important to them. In different parts of the province of Santiago del Estero, 268 families in eleven small towns were surveyed obtaining values of willingness to pay and willingness to accept. The use of useful plants has been passed down over many generations, which ensures the availability of a continuous flow of environmental services. The results expressed in monetary terms that show the importance that environmental services provided by native forests for rural communities.
Guy R McPherson
Modern Concepts & Developments in Agronomy, Volume 6, pp 654-656; doi:10.31031/mcda.2020.06.000641

The idea of planting trees to sequester atmospheric carbon is considered. Obviously, the process of photosynthesis insures that trees sequester carbon from the atmosphere. However, there are important questions that arise as we consider whether, how, and how many trees to plant. How fast do trees sequester carbon from the atmosphere? How much carbon do trees sequester? What negative side-effects are associated with planting large numbers of trees? These critical questions are addressed herein.
Waleed Fouad Abobatta
Modern Concepts & Developments in Agronomy, Volume 6, pp 649-650; doi:10.31031/mcda.2020.06.000639

Citrus is an important evergreen economic tree in different regions in the world, and there is a significant relationship between its yield and climate conditions in different growth stages. In the climate change era, there is more need to understanding the impacts of climate change on citrus growth and productivity and the influence of the potential climate changes in the next decades in major citrus production regions such as the U S A, Brazil, Egypt, Spain, Australia, South Africa, Turkey, and South Asia [1]. Climate change is a major challenge to citrus production worldwide and has directly affected tree yields, consequently, reduce growers’ profitability, as well as maybe changing the geographic distribution of varieties and production regions, therefore, there is requires new strategies addressing these challenges [2].
Alexandru Naghiu
Modern Concepts & Developments in Agronomy, Volume 6, pp 649-650; doi:10.31031/mcda.2020.06.000640

Now, at the beginning of the 21st millennium, the world is going through a new and critical era, one of great challenges related to food, water, energy, healthy environment and security, in the conditions of increasing population and climate change. The Earth’s population is still growing (it is true that it has reached the peak of the asymptote), according to the latest estimates, it is expected to reach 9.8 billion in 2050 and 11.2 billion in 2100 [1] and the world agricultural production has increased by 145%. from 1960 [2]. In the same time, the food loss and waste has become an important issue as today represents more than 1/3 of total (1,3 billiard of tons/year!) [3].
Lorena Pizarro
Modern Concepts & Developments in Agronomy, Volume 6, pp 646-648; doi:10.31031/mcda.2020.06.000638

Modern agriculture control diseases by extensive application of chemicals, however, this strategy brings undesired effects, such as environmental contamination and development of pesticide-resistant pathogens. Therefore, the need to develop alternative or supplementary strategies to control crop diseases has arisen.
Igor Souza Gonçalves, Tatiana Rodrigues Carneiro, Paulo Afonso Viana
Modern Concepts & Developments in Agronomy, Volume 6, pp 640-645; doi:10.31031/mcda.2020.06.000637

The aim of this study was to determine the main families of beetles occurring in an integrated crop-livestock- forest system, evaluating the influence of abiotic factors (average temperature and rainfall) in their distribution in Prudente de Morais region, State of Minas Gerais, Brazil. The survey was carried out in the experimental farm EPAMIG Centro-Oeste.
Jan Bocianowski
Modern Concepts & Developments in Agronomy, Volume 6, pp 638-639; doi:10.31031/mcda.2020.06.000636

Genetic similarity of genotypes is the very important for analysis of quantitative traits in all organisms. All organisms are exposed on the influence of different environmental conditions but in the genetic level are the same in all environments. A number of studies have shown that the greater the genetic similarity of parental lines, the smaller the heterosis effect [1]. Genetic or phenotypic similarity can be estimated by genotype testing on the basis of the observations obtained through prediction (a priori) or of the observations and studies (a posteriori). Coors [2] stated that predicting the effect of heterosis between groups of germplasm showing genetic similarity of germplasm was not possible on the basis of the genetic distance determined with using the DNA markers, but should be determined in the field experiments. The paper presents five the most popular methods of estimation of genetic similarity (S) based on coefficients proposed by Jaccard, Kulczynski, Sokal and Michener, Nei as well as Rogers.
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