Culture and Agriculture: A Comment on Sissel Schroeder, Maize Productivity in the Eastern Woodlands and Great Plains of North America

2001 ◽  
Vol 66 (3) ◽  
pp. 505-515 ◽  
Author(s):  
William W. Baden ◽  
Christopher S. Beekman
Keyword(s):  
Great Plains ◽  
Maize Yield ◽  
Yield Potential ◽  
Average Yield ◽  
Yield Data ◽  
Eastern Woodlands ◽  
Maize Agriculture ◽  
Maize Productivity ◽  
Agricultural Potential ◽  
Behavioral Constraints

Using selective maize yield data from ethnohistoric and government sources dating between the mid-nineteenth and mid-twentieth centuries, Schroeder (1999) argues that Mississippian average yield potential fell within a 9-10 bu/acre range. We evaluate her argument in terms of well-established climatic, environmental, varietal, and behavioral constraints on maize agriculture and conclude that reconstructing prehistoric agricultural potential requires a more precise methodology that incorporates these factors.

Maize Productivity in the Eastern Woodlands and Great Plains of North America

1999 ◽  
Vol 64 (3) ◽  
pp. 499-516 ◽  
Author(s):  
Sissel Schroeder
Keyword(s):  
Nineteenth Century ◽  
Native American ◽  
Native Americans ◽  
Great Plains ◽  
Nuclear Family ◽  
Eastern Woodlands ◽  
Resource Productivity ◽  
Maize Productivity ◽  
Mean Size ◽  
The Mean

Archaeologists and ethnohistorians have long been interested in quantifying potential maize productivity for late prehistoric and early historic Native Americans of the Eastern Woodlands. Maize yields obtained by Native Americans using traditional farming techniques in the nineteenth century are compared to yields obtained by nineteenth-century Native Americans using plows, and nineteenth- and twentieth-century farmers in Illinois and Missouri. The result is a notion of average resource productivity for maize that is more reasonable and modest than previous estimates. In this study, the mean yield of maize for nineteenth-century Native American groups who did not use plows was 18.9 bu/acre (stdev=4.1) (1,185.4 kg/ha [stdev=254.1]). Yields on the order of 10 bu/acre (627.2 kg/ha) probably are closer to the average prehistoric yields that were available for subsistence purposes. The mean size of gardens cultivated by nineteenth-century Native American families without plows was .59 acre (stdev=.45) (.24 ha [stdev=.18]). These newly compiled data are used to generate a model of nuclear family household economy and minimal and maximal garden sizes given different levels of maize productivity and consumption. Population estimates made on the basis of previous assessments of high rates of resource productivity will need to be reevaluated.

scholarly journals Status and prospects of maize research in Nepal

2015 ◽  
Vol 1 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Govind KC ◽  
Tika B Karki ◽  
Jiban Shrestha ◽  
Buddhi B Achhami
Keyword(s):  
Technology Development ◽  
Animal Feed ◽  
Maize Yield ◽  
Yield Potential ◽  
Maize Production ◽  
Climate Change Effects ◽  
Maize Productivity ◽  
Future Direction ◽  
The Many ◽  
The Hill

Food and nutritional securities are the major threats coupled with declining factor productivity and climate change effects in Nepal. Maize being the principal food crops of the majority of the hill people and source of animal feed for ever growing livestock industries in Terai of Nepal. Despite the many efforts made to increase the maize productivity in the country, the results are not much encouraging. Many of the maize based technologies developed and recommended for the farmers to date are not fully adopted. Therefore, problem is either on technology development or on dissemination or on both. Considering the above facts, some of the innovative and modern approaches of plant breeding and crop management technologies to increase the maize yield need to be developed and disseminated. There is a need for location-specific maize production technologies, especially for lowland winter maize, marginal upland maize production system, and resource poor farmers. Research efforts can be targeted to address both yield potential and on-farm yields by reducing the impacts of abiotic and biotic constraints. Therefore, in order to streamline the future direction of maize research in Nepal, an attempt has been made in this article to highlight the present status and future prospects with few key pathways.Journal of Maize Research and Development (2015) 1(1):1-9DOI: http://dx.doi.org/10.5281/zenodo.34284

scholarly journals Identifying maize yield and precipitation gaps in Uganda

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Terence Epule Epule ◽  
Driss Dhiba ◽  
Daniel Etongo ◽  
Changhui Peng ◽  
Laurent Lepage
Keyword(s):  
Cropping Systems ◽  
Growing Season ◽  
Maize Yield ◽  
Sub Saharan Africa ◽  
World Bank Group ◽  
Precipitation Data ◽  
Yield Data ◽  
Yield Gaps ◽  
Maize Yields ◽  
Growing Season Precipitation

AbstractIn sub-Saharan Africa (SSA), precipitation is an important driver of agricultural production. In Uganda, maize production is essentially rain-fed. However, due to changes in climate, projected maize yield targets have not often been met as actual observed maize yields are often below simulated/projected yields. This outcome has often been attributed to parallel gaps in precipitation. This study aims at identifying maize yield and precipitation gaps in Uganda for the period 1998–2017. Time series historical actual observed maize yield data (hg/ha/year) for the period 1998–2017 were collected from FAOSTAT. Actual observed maize growing season precipitation data were also collected from the climate portal of World Bank Group for the period 1998–2017. The simulated or projected maize yield data and the simulated or projected growing season precipitation data were simulated using a simple linear regression approach. The actual maize yield and actual growing season precipitation data were now compared with the simulated maize yield data and simulated growing season precipitation to establish the yield gaps. The results show that three key periods of maize yield gaps were observed (period one: 1998, period two: 2004–2007 and period three: 2015–2017) with parallel precipitation gaps. However, in the entire series (1998–2017), the years 2008–2009 had no yield gaps yet, precipitation gaps were observed. This implies that precipitation is not the only driver of maize yields in Uganda. In fact, this is supported by a low correlation between precipitation gaps and maize yield gaps of about 6.3%. For a better understanding of cropping systems in SSA, other potential drivers of maize yield gaps in Uganda such as soils, farm inputs, crop pests and diseases, high yielding varieties, literacy, and poverty levels should be considered.

An economic comparison of alternative and traditional cropping systems in the northern Great Plains, USA

2006 ◽  
Vol 21 (1) ◽  
pp. 68-73 ◽  
Author(s):  
Eric A. DeVuyst ◽  
Thomas Foissey ◽  
George O. Kegode
Keyword(s):  
North Dakota ◽  
Great Plains ◽  
Cropping Systems ◽  
Cropping System ◽  
Conventional Tillage ◽  
Northern Great Plains ◽  
Yield Data ◽  
Government Program ◽  
Current Production ◽  
Commodity Programs

AbstractCurrent production practices in the Red River Valley of North Dakota and Minnesota involve use of extensive tillage and/or herbicides to control weeds. Given the erosion potential, environmental concerns associated with herbicides, and herbicide-resistant weeds, alternative cropping systems that mitigate these problems need to be assessed economically. Furthermore, the role that government commodity programs play in the adoption of more ecologically friendly cropping systems needs to be determined. We evaluated 8 years of yield data (1994–2001) from field plots near Fargo, North Dakota, to compare the economics of two alternative cropping systems, reduced-input (RI) and no-till (NT), to a conventional tillage (CT) cropping system. The RI system relies on a more diverse rotation of soybean (SB), spring wheat (SW), sweet clover (SC) and rye, and uses fewer herbicide and fertilizer inputs than CT or NT. Both NT and CT systems rotate SB and SW. We found that CT returns averaged over $47 ha−1more than NT during the study period. Because SC yield data were not available, the economic competitiveness of RI was calculated using break-even yields and returns for SC. Historical SC yields in Cass County, North Dakota were not statistically different from the break-even yields. However, when government program payments were considered, break-even returns for SC increased by about $15 and $18 ha−1and break-even yields by 0.44 and 0.52 MT ha−1for RI to compare with NT and CT, respectively. These results indicate that CT management offers greater economic return than either RI or NT and that government program payments impede adoption of more environmentally friendly cropping systems in the northern Great Plains.

scholarly journals Combating Dual Challenges in Maize Under High Planting Density: Kernel Abortion and Stem Lodging

2021 ◽  
Vol 12 ◽  
Author(s):  
Adnan Noor Shah ◽  
Mohsin Tanveer ◽  
Asad Abbas ◽  
Mehmet Yildirim ◽  
Anis Ali Shah ◽  
...  
Keyword(s):  
Agricultural Land ◽  
Plant Density ◽  
Sugar Metabolism ◽  
Strong Relationship ◽  
Maize Yield ◽  
Planting Density ◽  
Lodging Resistance ◽  
Genetic Characteristics ◽  
Maize Productivity ◽  
High Plant Density

High plant density is considered a proficient approach to increase maize production in countries with limited agricultural land; however, this creates a high risk of stem lodging and kernel abortion by reducing the ratio of biomass to the development of the stem and ear. Stem lodging and kernel abortion are major constraints in maize yield production for high plant density cropping; therefore, it is very important to overcome stem lodging and kernel abortion in maize. In this review, we discuss various morphophysiological and genetic characteristics of maize that may reduce the risk of stem lodging and kernel abortion, with a focus on carbohydrate metabolism and partitioning in maize. These characteristics illustrate a strong relationship between stem lodging resistance and kernel abortion. Previous studies have focused on targeting lignin and cellulose accumulation to improve lodging resistance. Nonetheless, a critical analysis of the literature showed that considering sugar metabolism and examining its effects on lodging resistance and kernel abortion in maize may provide considerable results to improve maize productivity. A constructive summary of management approaches that could be used to efficiently control the effects of stem lodging and kernel abortion is also included. The preferred management choice is based on the genotype of maize; nevertheless, various genetic and physiological approaches can control stem lodging and kernel abortion. However, plant growth regulators and nutrient application can also help reduce the risk for stem lodging and kernel abortion in maize.

scholarly journals Field-scale soil moisture bridges the spatial-scale gap between drought monitoring and agricultural yields

2020 ◽  
Author(s):  
Noemi Vergopolan ◽  
Sitian Xiong ◽  
Lyndon Estes ◽  
Niko Wanders ◽  
Nathaniel W. Chaney ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Spatial Scale ◽  
Root Zone ◽  
Maize Yield ◽  
Remotely Sensed ◽  
Drought Monitoring ◽  
Surface Model ◽  
Field Scale ◽  
Yield Data ◽  
Scale Modeling

Abstract. Soil moisture is highly variable in space, and its deficits (i.e. droughts) plays an important role in modulating crop yields and its variability across landscapes. Limited hydroclimate and yield data, however, hampers drought impact monitoring and assessment at the farmer field-scale. This study demonstrates the potential of field-scale soil moisture simulations to advance high-resolution agricultural yield prediction and drought monitoring at the smallholder farm field-scale. We present a multi-scale modeling approach that combines HydroBlocks, a physically-based hyper-resolution Land Surface Model (LSM), and machine learning. We applied HydroBlocks to simulate root zone soil moisture and soil temperature in Zambia at 3-hourly 30-m resolution. These simulations along with remotely sensed vegetation indices, meteorological conditions, and data describing the physical properties of the landscape (topography, land cover, soil properties) were combined with district-level maize data to train a random forest model (RF) to predict maize yields at the district- and field-scale (250-m) levels. Our model predicted yields with a coefficient of variation (R2) of 0.61, Mean Absolute Error (MAE) of 349 kg ha−1, and mean normalized error of 22 %. We captured maize losses due to the 2015/2016 El Niño drought at similar levels to losses reported by the Food and Agriculture Organization (FAO). Our results revealed that soil moisture is the strongest and most reliable predictor of maize yield, driving its spatial and temporal variability. Consequently, soil moisture was also the most effective indicator of drought impacts in crops when compared with precipitation, soil and air temperatures, and remotely-sensed NDVI-based drought indices. By combining field-scale root zone soil moisture estimates with observed maize yield data, this research demonstrates how field-scale modeling can help bridge the spatial scale discontinuity gap between drought monitoring and agricultural impacts.

scholarly journals Evaluating the Yield Response of Maize (Zea mays L.) and Rice (Oryza sativa L.) to Future Climate Variability in The Gambia

2019 ◽  
Vol 7 (2) ◽  
pp. 11
Author(s):  
Ebrima Sonko ◽  
Sampson K. Agodzo ◽  
Philip Antwi-Agyei
Keyword(s):  
Climate Variability ◽  
Rice Yield ◽  
Oryza Sativa L ◽  
Maize Yield ◽  
Future Climate ◽  
Yield Response ◽  
Climate Data ◽  
Negative Effects ◽  
Yield Data ◽  
Maize Cultivars

Climate change and variability impact on staple food crops present a daunting challenge in the 21st century. The study assesses future climate variability on maize and rice yield over a 30-year period by comparing the outcomes under two GCM models, namely, CSIRO_RCP4.5 and NOAA_RCP4.5 of Australia’s Commonwealth Scientific and National Oceanic and Atmospheric Administration respectively. Historical climate data and yield data were used to establish correlations and then subsequently used to project future yields between 2021 and 2050. Using the average yield data for the period 1987-2016 as baseline yield data, future yield predictions for 2021-2030, 2031-2040 and 2041-2050 were then compared with the baseline data. The results showed that the future maize and rice yield would be vulnerable to climate variability with CSIRO_RCP4.5 showing increase in maize yield whilst CSIRO_RCP4.5 gives a better projection for rice yield. Furthermore, the results estimated the percentage mean yield gain for maize under CSIRO_RCP4.5 and NOAA_ RCP4.5 by about 17 %, 31 % and 48 % for the period 2021-2030, 2031-2040 and 2041-2050 respectively. Mean rice yield lossess of -23 %, -19 % and -23 % were expected for the same period respectively. The study recommended the use of improved rice and maize cultivars to offset the negative effects of climate variability in future.

scholarly journals Using QUEFTS model for estimating nutrient requirements of maize in the Northeast China

2017 ◽  
Vol 63 (No. 11) ◽  
pp. 498-504 ◽  
Author(s):  
Jiang Wenting ◽  
Liu Xiaohu ◽  
Qi Wen ◽  
Xu Xiaonan ◽  
Zhu Yucui
Keyword(s):  
Northeast China ◽  
Field Experiments ◽  
Nutrient Use Efficiency ◽  
Maize Yield ◽  
Yield Potential ◽  
Nutrient Requirements ◽  
Plant Nitrogen ◽  
Nutrient Use ◽  
Supply Surplus ◽  
Use Efficiency

Accurate estimating of the balanced nutrition for maize is necessary for optimizing fertilizer management to prevent nutrient supply surplus or deficiency. Data from 300 field experiments in the Northeast China conducted between 2006 and 2011 were gathered to study the characteristics of maize yield, and using the QUEFTS model to estimate the balanced nutrition at different yield potential. The average grain yield was 10 427 kg/ha, and average internal efficiencies were 54.3, 251.5 and 78.2 kg grain per kg plant nitrogen (N), phosphorus (P) and potassium (K), respectively. With the harvest index values < 0.40 as outliers were excluded, the model simulated a linear-parabolic-plateau curve for the balanced N, P and K uptake when the initial yield target increased to the yield potential levels of 10 000 to 14 000 kg/ha. When the yield target reached approximately 60–70% of the yield potential, 16.7 kg N, 3.8 kg P, and 11.4 kg K were required to produce 1000 kg grain. The corresponding internal efficiencies were 60.0, 265.7 and 88.0 kg grain per kg plant N, P and K, respectively. These results contributed to improving nutrient use efficiency, and to demonstrate that the QUEFTS model could be a promising approach for estimating the balanced nutrition.

Effect of field peas and wheat on the yield and protein content of subsequent wheat crops grown at several rates of applied nitrogen

1994 ◽  
Vol 34 (5) ◽  
pp. 641 ◽  
Author(s):  
IC Rowland ◽  
MG Mason ◽  
IA Pritchard ◽  
RJ French
Keyword(s):  
N Availability ◽  
Average Increase ◽  
Average Yield ◽  
Response Curves ◽  
Yield Data ◽  
Yield Increase ◽  
Field Peas ◽  
Quadratic Response ◽  
The Difference ◽  
Rate Interaction

The responses of wheat to various rates of N fertiliser were compared following field peas (PW) or wheat (WW) in the previous year. Seventeen trials were carried out at 5 sites between 1986 and 1991. The trials were on medium- and fine-textured soils (clay loams or shallow duplex soils). The overall grain yield of PW appeared greater than WW in 11 trials [was significantly greater in 9 (P<0.05)], and did not appear different in 6 trials. When no N was applied the yield advantage of PW was 41% (PW 1.91 t/ha cf. WW 1.37 t/ha). Quadratic response curves were fitted to all yield data. Rotation x N rate interaction was significant (P<0.05) in 10 comparisons. In 5 trials, while there was a yield increase to N fertiliser with WW, the yields decreased with PW. In 3 trials while there was an increase with WW there was no response with PW or a reduction at higher rates of N. In the remaining 2 trials there were responses with both PW and WW, but this was greater for WW. The response curves in these 10 trials either converged and met, indicating that the difference between rotations was due to N availability, or converged but did not meet, indicating that N was important but did not explain the whole difference. Where there was no interaction between rotation and N rate the response curves were parallel. The type of response could not be predicted. It was not profitable to apply N fertiliser to wheat in the PW rotation in 11 of the 17 trials. The average yield advantage of PW over WW, in the absence of N was 540 kg/ha, while there was an average increase of 1.7% grain protein.

scholarly journals Factors causing yield gap in rape seed production in the eastern of Mazandaran province, Iran

2020 ◽  
Vol 15 (1) ◽  
pp. 10-19
Author(s):  
Esmail Nezamzade ◽  
Afshin Soltani ◽  
Salman Dastan ◽  
Hossein Ajamnoroozi
Keyword(s):  
Relative Yield ◽  
Crop Management ◽  
Yield Potential ◽  
Boundary Line ◽  
Optimum Level ◽  
Average Yield ◽  
Rape Seed ◽  
Mazandaran Province ◽  
Yield Gap ◽  
Line Analysis

The reduction of yield gap and achievement yield potential of oil plants make a significant contribution to yield increases and oil production in developing countries. This research was carried out to investigate the factors causing yield gap associated with rape seed crop management in the Neka region, east of the Mazandaran province, Iran, through a field study during 2015-2016 and 2016- 2017. Boundary line analysis (BLA) was only applied to crop management practices/inputs, e.g. sowing date and rate, fertilizer applications, etc. Boundary lines were fitted to the edge of the data cloud of crop yield versus management variables in data. The average yield in 100 farms was 2051 kg/ha. According to findings of BLA, an average yield, based on the optimum level of the 14 studied variables, was 3032 kg/ha with a 981 kg/ha yield gap per hectare. The average relative yield and relative yield gap for the 14 investigated variables were 68.35% and 31.65%, respectively. Therefore, it can be concluded that the use of the boundary line analysis in yield gap studies can clearly show the yield responses to management factors and calculate the possible potentials. Thus, cultivation practice management of the studied variables in farmers’ fields can lead to increased yield and reduced yield gap.

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