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Adaptation for Crop Production and Sustainable Agriculture in a Changing Climate (2nd Edition)

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A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 16936

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Dr. Muhammad Habib ur Rahman

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Guest Editor

1. Institute of Crop Science and Resource Conservation (INRES), Crop Science Group, University of Bonn, 53113 Bonn, Germany
2. Department of Agronomy, MNS-University of Agriculture, Multan, Punjab, Pakistan
Interests: crop production and climate models climate change; impact assessments; agroecosystems modeling; adaptation to climate change; crop production; digital agriculture; climate smart agriculture; cropping systems; ecosystem services; crop physiology; nutrients cycling; sustainable soil and environment management
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Dear Colleagues,

Crop production and sustainable agriculture are under threat due to climate variability and change. Climate change is a serious threat to agricultural sustainable production systems. To feed the ever-increasing world population, it is essential to enhance agricultural production for food security. To combat climate change, adaptations, especially those providing technological and digital interventions, are required in current crop and agricultural production systems for sustainable food production under climate change scenarios. Sustainable agricultural production methods which adopt digital adaptations can improve crop productivity with nutritive food to ensure food security. Digital and technological adaptations such as the monitoring of crops and agricultural systems with sensors, web applications, artificial intelligence, precision agriculture and real-time simulation using sensors and UAV data, decision support systems, and robotics have the potential to precisely utilize resources and ensure sustainable production in agriculture systems. These digital and technological adaptations for climate change will improve crop productivity and the sustainable production of agricultural systems from local to national and global perspectives.

This Special Issue is a follow-up of the first Special Issue, entitled “Adaptation for Crop Production and Sustainable Agriculture in a Changing Climate” (https://www.mdpi.com/journal/atmosphere/special_issues/adaptations_crop_production), published in Atmosphere in 2021. The aim of this Special Issue is to present original research articles and reviews related to digital and technological adaptions to produce more food on a sustainable basis through the effective management of ever-decreasing resources. In this Special Issue, we seek original work focused on addressing new digital technologies, innovative methods related to sensors’ development and applications in agriculture, new technologies for precision agriculture, real-time simulations, the development of decision support systems for the monitoring of agriculture systems in the field, and effective resource utilization for sustainable agriculture.

Specific topics include, but are not limited to, the following:

improving resource-use efficiency
sustainable crop production
digital and technological adaptations for sustainable agriculture production
precision resource management (soil, water, fertilizer, etc.)
technological interventions for climate-smart agriculture
innovation in sensors and crop monitoring through UAVs
diversification in food production system
agronomic and breeding adaptation
real-time monitoring and simulation
decision support system development and application
emerging tools and techniques for sustainable agriculture
diversification in cropping systems
water-smart technologies
the provision of ecosystem services in different agro-ecosystems
future climate change scenarios and impacts on agriculture
the application of machine learning and artificial intelligence in agriculture
big data management and uses in agriculture
climate change scenarios

Dr. Muhammad Habib ur Rahman
Guest Editor

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Published Papers (6 papers)

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Research

17 pages, 1308 KiB

Open AccessArticle

Dynamics and Determinants of Farmers’ Perceptions about Causes and Impacts of Climate Change on Agriculture in Saudi Arabia: Implications for Adaptation, Mitigation, and Sustainability

by Bader Alhafi Alotaibi, Azhar Abbas, Raza Ullah, Muhammad Imran Azeem, Abdus Samie, Muhammad Muddassir, Abduaziz Thabet Dabiah, Moodhi Raid and Tahira Sadaf

Atmosphere 2023, 14(6), 917; https://doi.org/10.3390/atmos14060917 - 24 May 2023

Cited by 3 | Viewed by 2637

Abstract

Concerns over the potential harmful impacts of changing climate are strongly echoing around the globe. With its wide range of hazards to human societies, climate change is posing serious threats to human survival and impacting every aspect of human life, including food production systems. It is, therefore, imperative to gauge the local knowledge, perceptions, and adaptation capacity for the effective mitigation of the ill impacts of climate change. In this backdrop, the present study has been designed to investigate the perceptions of farmers regarding causes and impacts of climate change on agriculture. Required data were collected from the Madinah region in Saudi Arabia and analyzed to answer the following study questions: How do farmers perceive impacts of climate change? What factors affect their perceived impacts of climate change? Additionally, what factors affect their perception about the causes of climate change? Individual logit models were used to assess the impacts of various factors on perceived causes and perceived impacts of climate change on agriculture. A multinomial logit model was also employed to figure out significant determinants of perceived causes of climate change on agriculture. Results indicated that the most dominant perceived impacts of climate change are its effects on crop production, followed by drying water sources. The results also revealed that the age of the farmers had a positive effect on their perception of natural processes being the cause of climate change. Similarly, farming experience had an inverse effect on their perceptions regarding causes of climate change. The majority of the farmers seemed clear about the possible drivers of climate change in the country. In particular, about 79 percent of the farmers believed that GHGs and pollution are causing climate change in the country. The findings provide useful insights into farmers’ perceptions about causes and impacts of climate change and may be used by policymakers to strategically design extension and agricultural development initiatives for helping the farmers to implement sustainable agricultural practices to adapt to and lower the adverse impacts of climate change in the Kingdom. Full article

(This article belongs to the Special Issue Adaptation for Crop Production and Sustainable Agriculture in a Changing Climate (2nd Edition))

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24 pages, 2418 KiB

Open AccessArticle

Assessment of Climate Change Impact on Maize Production in Serbia

by Gordana Petrović, Tatjana Ivanović, Desimir Knežević, Adriana Radosavac, Ibrahim Obhođaš, Tomislav Brzaković, Zorica Golić and Tatjana Dragičević Radičević

Atmosphere 2023, 14(1), 110; https://doi.org/10.3390/atmos14010110 - 4 Jan 2023

Cited by 8 | Viewed by 3832

Abstract

Climate factors have an impact on plant life cycle, yield, productivity, economy and profitability of agricultural production. There are not a lot of studies on understanding of influence of climate factors variation on maize yield in agro-ecological conditions of Serbia. The aim of this paper is analysis of variation of climatic factors over a long-time period, as well as assessment of impact of the examined climate parameters on maize yield in two localities in the Republic of Serbia. For the analysis of climatic factors (temperature, precipitation, sunshine, humidity) in the region of Central Serbia and Vojvodina, the data of meteorological stations Kragujevac and Sombor during two thirty-year periods (1961–1990 and 1991–2020) were used. In order to determine the existence and strength of the relationship between the observed climatic factors and maize yield, a correlation analysis of these indicators for the period 2005–2020 years, was performed. In the period 1991–2020, the average values of temperature were annually increased for 0.046 °C in Kragujevac and for 0.05 °C in Sombor, and in the same period the average value of sunshine on an annual level was increased for 1.3 h in Kragujevac and for 5.01 h in Sombor, 2020 in comparison to average values in period of 1961–1990. The humidity was decline annually for 1.3 in Kragujevac and for 3.4 in Sombor in period 1991–2020 in comparison to average humidity in period of 1961–1990. The results of the correlation analysis showed that the maize yield was significantly lower in the years with expressed high temperatures and precipitation deficit. Based on these studies, established effect of climate change on maize yield and that this demand developing adaptation agricultural practice through creating maize hybrids and varieties with greater adaptability and improvement of agrotechnic measure. Full article

(This article belongs to the Special Issue Adaptation for Crop Production and Sustainable Agriculture in a Changing Climate (2nd Edition))

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14 pages, 2752 KiB

Open AccessArticle

Establishment of Crop Water Stress Index for Sustainable Wheat Production under Climate Change in a Semi-Arid Region of Pakistan

by Muhammad Imran Khan, Qaisar Saddique, Xingye Zhu, Sikandar Ali, Ali Ajaz, Muhammad Zaman, Naeem Saddique, Noman Ali Buttar, Rao Husnain Arshad and Abid Sarwar

Atmosphere 2022, 13(12), 2008; https://doi.org/10.3390/atmos13122008 - 29 Nov 2022

Cited by 7 | Viewed by 2842

Abstract

The Crop Water Stress Index (CWSI) is a useful tool for evaluating irrigation scheduling and achieving water conservation and crop yield goals. This study examined the CWSI under different water stress conditions for the scheduling of wheat crop irrigation and developed indices using the leaf canopy temperature in Faisalabad, Pakistan. The experiments were conducted using a randomized, complete block design and four irrigation treatments with deficit levels of D_0%, D_20%, and D_40% from the field capacity (FC) and D_100% (100% deficit level). The CWSI was determined at pre-heading and post-heading stages through the lower baseline (fully watered crop) and upper limit (maximum stress). These baselines were computed using the air temperature and canopy temperature of plant leaves and the vapor pressure deficit (VPD). The CWSI for each irrigation treatment was calculated and the average seasonal CWSI value for the whole season was used to develop the empirical relationships for scheduling irrigation. The relationships between the air canopy temperatures and the VPD resulted in slope (x) = −0.735 and interception (c) = −0.8731 as well as x = −0.5143 and c = −1.273 at the pre- and post-heading stages, respectively. The values of the CWSI for the treatment at deficit levels of D_0%, D_20%, D_40%, and D_100% were found to be 0.08, 0.61, 0.20, and 0.64, respectively. The CWSI values developed in this study can be effectively used to promote better the monitoring of irrigated wheat crops in the region. Full article

(This article belongs to the Special Issue Adaptation for Crop Production and Sustainable Agriculture in a Changing Climate (2nd Edition))

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10 pages, 2888 KiB

Open AccessArticle

Quantifying the Space-Time Variations of Water Demands for Major Crops in Hebei Province, China

by Mengna Li, Mengxia Shi, Jiaxiao Zhang, Yunjiao Qi and Yongdeng Lei

Atmosphere 2022, 13(9), 1399; https://doi.org/10.3390/atmos13091399 - 31 Aug 2022

Cited by 1 | Viewed by 1853

Abstract

Hebei Province is a typical water-scarce agricultural region in North China. Quantifying the water demands of major crops and their variations in this region is crucial for the sustainable use of agricultural water resources. Based on meteorological data and crop growth parameters of 21 national weather stations in Hebei Province from 2007 to 2017, this study analyzed the crop water requirement, irrigation water demand, and water deficit index and their dynamic changes for several grain and vegetable crops including winter wheat, summer maize, soybean, potato, tomato, cucumber, eggplant, cowpea, Chinese cabbage, cabbage, and carrot. In addition, regional total irrigation water demands of these water-intensive crops were estimated. The results indicated that, except for summer maize, the crop water requirements and irrigation water demands of grain crops during the growth periods were mostly higher than those of vegetable crops. Winter wheat and cabbage had the highest water deficits among grain and vegetable crops, respectively, while summer maize had the lowest water deficits. Temporally, the irrigation water demands of winter wheat, summer maize, cabbage, and eggplant have increased for years, along with the increase in planting areas. Spatially, the total irrigation water demand in the southeast of Hebei Province was higher than that in the northwest, and the total irrigation water demand of winter wheat was much higher than that of the other crops. To mitigate water scarcity while ensuring food security, the planting areas of crops with higher yields and lower water consumptions, including summer maize, potato, cabbage, and carrot could be appropriately expanded. In contrast, the scale of water-intensive crops such as winter wheat and tomato should be strictly controlled. Our findings will be of great significance for constructing sustainable water-saving cropping systems in a changing climate. Full article

(This article belongs to the Special Issue Adaptation for Crop Production and Sustainable Agriculture in a Changing Climate (2nd Edition))

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32 pages, 11435 KiB

Open AccessArticle

Enhancing Capacity for Short-Term Climate Change Adaptations in Agriculture in Serbia: Development of Integrated Agrometeorological Prediction System

by Ana Vuković Vimić, Vladimir Djurdjević, Zorica Ranković-Vasić, Dragan Nikolić, Marija Ćosić, Aleksa Lipovac, Bojan Cvetković, Dunja Sotonica, Dijana Vojvodić and Mirjam Vujadinović Mandić

Atmosphere 2022, 13(8), 1337; https://doi.org/10.3390/atmos13081337 - 22 Aug 2022

Cited by 6 | Viewed by 2350

Abstract

The Integrated Agrometeorological Prediction System (IAPS) was a two-year project for the development of the long term forecast (LRF) for agricultural producers. Using LRF in decision-making, to reduce the risks and seize the opportunities, represents short-term adaptation to climate change. High-resolution ensemble forecasts (51 forecasts) were made for a period of 7 months and were initiated on the first day of each month. For the initial testing of the capacity of LRF to provide useful information for producers, 2017 was chosen as the test year as it had a very hot summer and severe drought, which caused significant impacts on agricultural production. LRF was very useful in predicting the variables which bear the memory of the longer period, such are growing degree days for the prediction of dates of the phenophases’ occurrences and the soil moisture of deeper soil layers as an indicator for the drought. Other project activities included field observations, communication with producers, web portal development, etc. Our results showed that the selected priority forecasting products were also identified by the producers as being the highest weather-related risks, the operational forecast implementation with the products designed for the use in agricultural production is proven to be urgent and necessary for decision-making, and required investments are affordable. The total cost of the full upgrade of agrometeorological climate services to meet current needs (including monitoring, seamless forecasting system development and the development of tools for information dissemination) was found to be about three orders of magnitude lower than the assessed losses in agricultural production in the two extreme years over the past decade. Full article

(This article belongs to the Special Issue Adaptation for Crop Production and Sustainable Agriculture in a Changing Climate (2nd Edition))

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25 pages, 14036 KiB

Open AccessArticle

Warming Climate and Elevated CO₂ Will Enhance Future Winter Wheat Yields in North China Region

by Muhammad Rizwan Shoukat, Dongyu Cai, Muhammad Shafeeque, Muhammad Habib-ur-Rahman and Haijun Yan

Atmosphere 2022, 13(8), 1275; https://doi.org/10.3390/atmos13081275 - 11 Aug 2022

Cited by 7 | Viewed by 2484

Abstract

The projected climate change substantially impacts agricultural productivity and global food security. The cropping system models (CSM) can help estimate the effects of the changing climate on current and future crop production. The current study evaluated the impact of a projected climate change under shared socioeconomic pathways (SSPs) scenarios (SSP2-4.5 and SSP5-8.5) on the grain yield of winter wheat in the North China Plain by adopting the CSM-DSSAT CERES-Wheat model. The model was calibrated and evaluated using observed data of winter wheat experiments from 2015 to 2017 in which nitrogen fertigation was applied to various growth stages of winter wheat. Under the near-term (2021–2040), mid-term (2041–2060), and long-term (2081–2100) SSP2-4.5 and SSP5-8.5 scenarios, the future climate projections were based on five global climate models (GCMs) of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The GCMs projected an increase in grain yield with increasing temperature and precipitation in the near-term, mid-term, and long-term projections. In the mid-term, 13% more winter wheat grain yield is predicted under 1.3 °C, and a 33 mm increase in temperature and precipitation, respectively, compared with the baseline period (1995–2014). The increasing CO₂ concentration trends projected an increase in average grain yield from 4 to 6%, 4 to 14%, and 2 to 34% in the near-term, mid-term, and long-term projections, respectively, compared to the baseline. The adaptive strategies were also analyzed, including three irrigation levels (200, 260, and 320 mm), three nitrogen fertilizer rates (275, 330, and 385 kg ha⁻¹), and four sowing times (September 13, September 23, October 3, and October 13). An adaptive strategy experiments indicated that sowing winter wheat on October 3 (traditional planting time) and applying 275 kg ha⁻¹ nitrogen fertilizer and 260 mm irrigation water could positively affect the grain yield in the North China Plain. These findings are beneficial in decision making to adopt and implement the best management practices to mitigate future climate change impacts on wheat grain yields. Full article

(This article belongs to the Special Issue Adaptation for Crop Production and Sustainable Agriculture in a Changing Climate (2nd Edition))

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