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Purpose – The purpose of the research aims to observe the high growth of corn crops with a different cropping pattern.

Design/Methodology/Approach – The research is conducted based on field experiments with Group Randomized Design (hereafter RAK shortened from Cluster Random Design). The treatment of cropping pattern I is that corn crops are planted in one row with the size of plot 9 m × 4 m, and the distance planting of the crops is 70 cm × 40 cm. Cropping pattern II is that corn crops are planted in two rows with the size of plot 9 m × 4 m, and the distance planting is 70 cm × 40 cm. Cropping pattern III is that corn crops are planted in three rows with the size of plot 9 m × 4 m, and the distance among the crops is 70 cm × 40 cm.

Findings – The result of research shows that the highest corn crops are from cropping pattern II.3 at age 15 and 30 after planting time (called HariSetelahTanam or HST). The increase of cropping rows from one row to two rows indicates that intra-specific competition are more dominant. The growth of crops is faster because they need full sunlight at vegetative and generative stages. The need of full sunlight at the growing stage causes the increasing of stem height of crops to enable the crops to receive the sunlight optimally due to the continuity of photosynthesis process. The increasing growth of stem diameter is in accordance with the growth speed of height plant at the same age.

Research Limitations/Implications – This research intends to find out the best growing process of the plant. Further research is needed to study the outcome of final product of the plant.

Practical Implications – This is to see the utilization of the best cropping pattern and optimal land utilization.

Originality/Value – High growth of corn crops and stem diameter (Zea may, S) with a different cropping pattern has not yet been published.

This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.

The choice of crops to produce at a location depends to a large degree on the climate. As the climate changes and food demand evolves, farmers may need to produce a different mix of crops. This study assesses how much cropland may be subject to such upheavals at the global scale, and then focuses on China as a case study to examine how spatial heterogeneity informs different contexts for adaptation within a country.

A global agricultural economic model is linked to a cropland allocation algorithm to generate maps of cropland distribution under historical and future conditions. The mix of crops at each location is examined to determine whether it is likely to experience a major shift.

Two-thirds of rainfed cropland and half of irrigated cropland are likely to experience substantial upheaval of some kind.

This analysis helps establish a global context for the local changes that producers might face under future climate and socioeconomic changes. The scale of the challenge means that the agricultural sector needs to prepare for these widespread and diverse upheavals.

Crop suitability analysis is vital for identifying a piece of land’s potential for sustainable crop production and aids in the formulation of an effective agricultural management plan. This study aims to conduct crop suitability analysis of prominent Kharif (rice and maize) and Rabi (potato and wheat) crops in Sirajganj district, a flood-prone area of Bangladesh, and recommend a suitable cropping pattern to mitigate the detrimental effects of flooding.

Various factors such as soil drainage, soil depth, soil moisture, soil texture, soil permeability, soil pH, erosion hazard, nutrient status and flooding risk were considered for this study. For all four crops, the weights of each factor were determined using the analytical hierarchy process approach, and the scores of each subfactor were assigned on the basis of favorable circumstances of crop cultivation. Using the weighted overlay analysis in the ArcGIS 10.3 environment, the crop suitability maps were generated and were divided into four suitable classes. Geographic information system integration of crop suitability for all the crops determined the suitable cropping pattern of the study area in Kharif and Rabi seasons.

A vast portion of the study area covering 64.80% of the total land is suitable for cultivating either rice or maize in Kharif season followed by either potato or wheat in Rabi season. Other suitable cropping pattern for Kharif and Rabi seasons found in the study area are rice-wheat, rice-wheat/potato, rice/maize-wheat and rice/maize-potato, which covers a little portion of the study area.

This research validates the suitable location of crop cultivation on the basis of flooding occurrences in the locality.

Smallholder farmers have always been profoundly the first to be impacted by climate change, and therefore, farmers understanding of climate change and accessibility to alternative adaptation strategies are crucial for reducing the effect of climate change. The purpose of this study is to assess the perception of farmers to climate change, adaptation strategies and determinants of adaptation choice in central Ethiopia.

The study used data from randomly selected 240 farm households. Descriptive statistics were used to describe farmers’ perceptions of climate change and adaptation strategies. Also, a multivariate probit model was used to identify the major factors affecting farmers’ choice of adaptation strategies to climate change in central Ethiopia.

Smallholder farmers perceive climate change in the past two decades in response; the majority (91.47%) of farmers used adaptation options. Improved crop varieties and input intensity, crop diversification, planting date adjustment, soil and water conservation activities and changing of the crop type were used as adaptation options in the study area. A few of these strategies were significantly confirmed a complementary and supplementary relationship. The study identified sex, family size, agroecology, climate information, crop-fail history and formal extension service as significant determinants for farmers’ adaptation choices as these variables significantly affected more than two farmers’ adaptation strategies simultaneously.

Farmers’ choice of adaptation was highly constrained by institutional factors and all these identified factors can be possibly addressed through a better institutional service provision system. It is, therefore, recommended that local administrators should explore the institutional service provision system for a better farm-level adaptation while considering demographic characteristics as well.

This study identified factors affecting farmers’ several adaptation strategies at a time and provides information for the policymaker to make cost-effective interventions for better farm-level adaptation practices.

The geographical range of agricultural crops is shifting because of climate change. Reducing the potential negative impact of this shift requires efficient crop switching at farm level. Yet there are scant studies that examine how crop switching is currently taking place and what factors facilitate the process. Even these few existing studies often based their analysis on inadequately established causal link between climate change and switching decisions. This study aims to identify the specific switching decisions that are primarily motivated by climate change, and their determinants.

The study used a household survey on 190 households in Semien Shewa Zone in Ethiopia. Subjective rating of farmers was used to identify the relative importance of climate change in motivating the different types of switching decisions. A logit model is used to identify determinants of crop switching decisions primarily motivated by climate change.

Farmers in the study area are currently abandoning certain crops as a response to climate change. The adoption of new crops is, however, mainly attributed to price changes. Most farmers who abandoned at least one crop adopted mung bean mainly due to its price advantages. As expected, crop switching as an adaptation strategy is more prevalent particularly in drier and hotter agroecologies. The logit model showed that crop switching is strongly correlated with land size and agroecology.

This paper provides an in-depth examination of crop switching as an adaptation strategy to climate change. Crop switching is an adaptation strategy that is expected to substantially reduce the damage from climate change in agriculture. The findings are particularly relevant for adaptation planning in the context of smallholder agriculture.

This study aims to examine the effect of climate variability on smallholders’ crop income and the determinants of indigenous adaptation strategies in three districts (Mieso, Goba-koricha and Doba) of West Hararghe Zone of Ethiopia. These three districts are located in high-moisture-stress areas because of crop season rainfall variability.

Primary data collected from 400 sample households were used for identifying factors that affect households’ crop income. The study used ordinary least square (OLS) regression to examine the effect of climate variability. Given this, binary logit model was used to assess smallholders’ adaptation behavior. Finally, the study used multinomial logistic regression to identify determinants of smallholders’ indigenous adaptation strategies.

The OLS regression result shows that variability in rainfall during the cropping season has a significant and negative effect, and cropland and livestock level have a positive effect on farmers’ crop income. The multinomial logistic regression result reveals that households adopt hybrid crops (maize and sorghum) and dry-sowing adaptation strategies if there is shortage during the cropping season. Variability in rainfall at the time of sowing and the growing are main factors in the area’s crop production. Cropland increment has positive and significant effect on employing each adaptation strategy. The probability of adopting techniques such as water harvesting, hybrid seeds and dry sowing significantly reduces if a household has a large livestock.

The three districts are remote and accessibility is difficult without due support from institutions. Thus, this study was conducted on the basis of the primary data collected by the researchers after securing grant from Swedish International Development Agency (SIDA).

This study aims to evaluate the impact of climate change on some specific areas of agricultural production in Quang Nam Province, including assessing the possibility of losing agricultural land owing to sea level rise; assessing the impact on rice productivity; and, assessing the impact on crop water demand.

This study used the method of collecting and processing statistics data; method of analysis, comparison and evaluation; method of geographic information system; method of using mathematical model; and method of professional solution, to assess the impacts of climate change.

Evaluation results in Quang Nam Province show that, by the end of the 21st century, winter–spring rice productivity may decrease by 33%, while summer–autumn rice productivity may decrease by 49%. Under representative concentration pathway (RCP) 4.5 scenario, water demand increases by 31.1% compared to the baseline period, of which the winter–spring crop increases by 28.4%, and the summer–autumn crop increased by 34.3%. Under RCP 8.5 scenario, water demand increases by 54.1% compared to the baseline period, of which the winter–spring crop increases by 46.7%, and the summer–autumn crop increased by 63.1%. The area of agricultural land likely to be inundated by sea level rise at 50 cm is 418.32 ha, and at 80 cm, it is 637.07 ha.

To propose adaptation solution to avoid the impacts of climate change on agriculture, it is necessary to consider about the impact on losing land for agriculture, the impact on rice productivity, assess the impact on crop water demand and other. The result of this assessment is useful for policymakers for forming the agriculture development plan.

The purpose of this paper is to explore the economic performance of Norwegian crop farms using a stochastic frontier analysis.

The analysis was based on a translog cost function and unbalanced farm-level panel data for 1991–2013 from 455 Norwegian farms specialized in crop production in eastern and central regions of Norway.

The results of the analysis show that the mean efficiency was about 78–81 percent. Farm management practices and socioeconomic factors were shown to significantly affect the economic performance of Norwegian crop farms.

Farmers are getting different types of support from the government and the study does not account for the different effects of different kinds of subsidy on cost efficiency. Different subsidies might have different effects on farm performance. To get more informative and useful results, it would be necessary to repeat the analysis with less aggregated data on subsidy payments.

One implication for farmers (and their advisers) is that many of them are less efficient than the estimated benchmark (best performing farms). Thus, those lagging behind the best performing farms need to look at the way they are operating and to seek out ways to save costs or increase crop production. Perhaps there are things for lagging farmers to learn from their more productive farming neighbors. For instance, those farmers not practicing crop rotation might be well advised to try that practice.

For both taxpayers and consumers, one implication is that the contributions they pay that go to subsidize farmers appear to bring some benefits in terms of more efficient production that, in turn, increase the supply of some foods so possibly making food prices more affordable.

Unlike previous performance studies in the literature, the authors estimated farm-level economic performance accounting for the contribution of both an important farm management practice and selected socioeconomic factors. Good farm management practices, captured through crop rotation, land tenure, government support and off-farm activities were found to have made a positive and statistically significant contribution to reducing the cost of production on crop-producing farms in the Central and Eastern regions of Norway.

Farmers' adaptation strategies in agricultural production are required to minimise the negative impact of climate change on a nation's food production in developing countries. Based on the panel data of the provincial level in China from 2000 to 2017, this study aims to analyse the changing climate over recent years and farmers' adaptation strategy in terms of cropping in agricultural production.

This study uses Simpson's diversity index (SDI) to measure the degree of crop diversity planted by farmers and evaluate the influence of climate change on farmers' cropping strategy using the fixed-effect model. Further, the authors estimate the impact of farmers' cropping strategy on their economic performances in two aspects including yields and technical efficiency of crops.

The empirical results show that the overall climate appears a warming trend. Different from farmers in some other countries, Chinese farmers tend to adopt a more specialised cropping strategy which can significantly improve the technical efficiency and yields of crops in agriculture. In addition, as a moderating role, the specialised cropping can help farmers to alleviate the negative impact of climate change on technical efficiency of their crops.

First, previous studies showed that the changing climate influenced farmers' adaptation strategies, while most studies focussed on multiple adaptation strategies from the farm-level perspective rather than cropping strategy from the nation-level perspective. Second, the present study investigates how the cropping strategy affects the economic performance (in terms of the technical efficiency and crop yields) of agricultural production. Third, the stochastic frontier analysis method is used to estimate the technical efficiency. Fourth, this study explores the moderating effect between farmers' cropping strategy and technical efficiency by introducing an interaction item of SDI and accumulated temperature.