Studies have long proved that both environmental and genotype factors have an impact on cultivars of different kinds. Consequently, studies have concluded that different genotypes are suited to different environments. However, most of these studies have been conducted on small-scale environments which may not be successfully applied, with desired results, on a larger scale. This paper argues that such kind of studies ought to be tested through large-scale experiments. This has been linked to the fact that in most cases, the genotype is the major factor involved, but the environment can also affect plant growth and reproduction. Therefore, the paper suggests that large-scale studies are required to eliminate observer effect of small-scale trials.
Available literature attests to the fact that environmental factors and genotype do exert significant influence on the growth and production of many cultivars. One such study was done by Chhetri et al (2016) in which it was observed that various strawberry cultivars showed marked differences in fruit characteristics and growth when the strawberry (ananassa x Fragaria) genotype was grown in high hill conditions. This study was carried out as Randomized Block Design (RBD). Likewise, earlier studies by Privé et al (1993) proved the influence of climate on reproductive and vegetative components of primocane-fruiting and red raspberry cultivars; yet again proving that the environment and the genotype interaction had a key impact in selecting and developing cultivars for wider production. Similar to Privé et al.’s study, in 2005, Connor et al proved a correlation between environmental and genotypic variation, in total phenolic content and anti-oxidant activity among hybrid-berry and blackberry cultivars. Later on, a similar study was carried out by Tulipani et al (2008), which concluded similar results, in addition to the nutritional quality of different strawberry genotypes. These and many more studies, however, have focused on the assessment of genotypic and environmental factors, though on a successful degree; but limited to a smaller scale.
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"Variation in Raspberry and Blackberry Cultivars due to Genotype".
Whereas results from these earlier studies have been groundbreaking and offer insights into this area, recent research efforts ought to be directed to testing of these factors in large-scale experiments. Presently, there is need to carry out similar studies on large scale as a way of eliminating observer effect of small-scale trials. Results from studies carried out by Kravchenko et al (2016), on field-scale, showed yield gaps in low input and organic cropping systems. From this, they acknowledged that the current knowledge in production systems and performance is mostly based on studies that are conducted on plot-scale. They argued that this is despite the yield gaps that exist between field-scale research and plot-scale, which has been widely acknowledged.
They maintain that although the limitations of plot-scale results being applied on large fields have been documented, their implications have been ignored. In the research they carried, they found out reasons for this conclusion. Their experimental results indicated that for corn, wheat and soybean managed conventionally, plot-scale results were seen to show similar performance on larger fields. The difference came in when they experimented on soybean and corn in biologically based management and limited input. In this case, Kravchenko et al (2016) found out that there was a higher tendency in favor of plot-scale compared to larger fields. They explained that these results proved that there were greater overall yield gaps due to organic management as well as reduced inputs in the larger fields, compared to the observations in the plot-scale. Consequently, they warn that if the existing global yield gaps are to be closed, there is need to start addressing the root cause of yields gaps in an effort to fix not just the current but also future global food needs. Kravchenko et al (2016), therefore, advice that since it has been proved, though overlooked, the plot-scale research results cannot be conclusively applied to fields; understanding the role and impact of large-scale experimental results will be instrumental in identifying the root cause of such yield gaps, and the best ways to close them.
In addition, Kravchenko et al (2016) pointed out that in most places in the world, row-crop agriculture is done in fields ranging from 25-100+ ha, whereas the process management and knowledge recommendations are usually based on studies carried out in plots of about 0.005-0.01 ha. According to them, unlike plots, fields have significant topographical and soil diversity that could affect yields. Also, they advance that another factor that accounts for the current yield gaps is related to low-input management. In their explanation, Kravchenko et al (2016) claim that edaphic variability in the field is more complex to manage by biological means, hence the use of chemicals. To them, this variability will usually be reduced in plot-scale experimental results as a result of judicious plot layouts, contiguous designs, and blocking. Locating plots on more favorable soils has also been seen to bring about this variability when looking at plot-scale studies. As a result of this locational bias, Kravchenko et al (2016) address that the yields from plot-scale experiments have usually been seen to be more than the field yields.
Most biologically based systems of management are dependent on a number of practices that are aimed at replenishing soil fertility, control pests and manage soil moisture. Among the most challenging fertility systems, are those based on crops; which involve a diversity of crop types like grass and legumes. To Kravchenko et al (2016), temporal and spatial variation in this system will typically impact on the biomass production, soil fertility as well as cover crop growth. Since low-input management usually relies on controlling weeds mechanically, they advise that optimal soil moisture would be a crucial factor to its success.
In conclusion, genotype and environmental factors have proved to exert influence in many different cultivars. Studies carried out extensively in this area by Chhetri et al (2016), Tulipani et al (2008), and Privé et al (1993) have proved this fact. Typically, such studies have been done in plot-scale environments. Results from the plot-scale experiments are then generalized and applied to larger fields. Current studies have expressed skepticisms about the adequacy and suitability of such plot-scale experimental results on giving a clear picture of the field-scale practices. As shown by Kravchenko et al (2016), results from such studies have proved that to a greater extent, plot-scale experimental results cannot be used to prove larger scale practices. The yield gaps that have been witnessed in other cases attest to this fact. Therefore, it is apparent that there is a need for attention in the area of field-scale experiments, from which case; the results would be applied in similar scenarios. This fact is particularly important considering the fact that due to yield gaps being witnessed, there is a concern for the current and future global food needs. Research in this area would be of great importance. This paper looked at literature that explains this phenomenon. It is in the view of this paper that because of observer bias and other factors mentioned; it is necessary that field-scale studies be carried out.
