A Multivariate Approach to Evaluate Reduced Tillage Systems and Cover Crop Sustainability

The evaluation of the effects of conservation agriculture during the transition from conventional tillage to no-tillage requires numerous indicators to be considered. For this purpose, we monitored changes in a multi-parameter dataset during a three-year experiment that combined three tillage intensities (conventional tillage—CT; minimum tillage—MT; and no tillage—NT) with three soil covering managements (tillage radish cover crop, winter wheat cover crop and bare soil). Using a multivariate analysis, we developed a Relative Sustainability Index (RSI) based on 11 physical (e.g., bulk density and penetration resistance), chemical (e.g., soil organic carbon and pH) and biological soil properties (e.g., earthworm density) to evaluate cropping systems sustainability. The RSI was most affected by tillage intensity showing higher RSI values (i.e., better performances) in reduced tillage systems. Specifically, the RSI under NT was 42% greater than that of CT and 13% greater than that of MT. Soil covering had little impact on the RSI. Among the tested parameters, the RSI was increased most by saturated hydraulic conductivity (+193%) and earthworm density (+339%) across CT and NT treatments.to. Our results suggest that conservation agriculture and, particularly, reduced tillage systems, have the potential to increase farm environmental and agronomic sustainability.

Irriman Platform: Enhancing Farming Sustainability through Cloud Computing Techniques for Irrigation Management

Crop sustainability is essential for balancing economic development and environmental care, mainly in strong and very competitive regions in the agri-food sector, such as the Region of Murcia in Spain, considered to be the orchard of Europe, despite being a semi-arid area with an important scarcity of fresh water. In this region, farmers apply efficient techniques to minimize supplies and maximize quality and productivity; however, the effects of climate change and the degradation of significant natural environments, such as, the “Mar Menor”, the most extent saltwater lagoon of Europe, threatened by resources overexploitation, lead to the search of even better irrigation management techniques to avoid certain effects which could damage the quaternary aquifer connected to such lagoon. This paper describes the Irriman Platform, a system based on Cloud Computing techniques, which includes low-cost wireless data loggers, capable of acquiring data from a wide range of agronomic sensors, and a novel software architecture for safely storing and processing such information, making crop monitoring and irrigation management easier. The proposed platform helps agronomists to optimize irrigation procedures through a usable web-based tool which allows them to elaborate irrigation plans and to evaluate their effectiveness over crops. The system has been deployed in a large number of representative crops, located along near 50000 ha of the surface, during several phenological cycles. Results demonstrate that the system enables crop monitoring and irrigation optimization, and makes interaction between farmers and agronomists easier.

Asian Rust Severity in Soybean Sown in December and February in Mato Grosso State

The objective of this work was to assess the effect of December sowing time with February on the Asian soybean rust severity. In on-farm trials two soybean treatments sowing in December (2020) (DSS.) and February (2021) (FSS) were assessed for Asian soybean rust severity in 24 sites, in three regions of Mato Grosso state. The DSS treatment was established in the growers commercial farms and the FSS in a 5 ha area sown specifically for this treatment. The DSS treatment was conducted in 16 sites and the FSS in eigth. For rust control fungicides with efficacy higher than 60% were sprayed consisting of DMIs, QoIs and SDHIs in double or triple mixtures, always added by multisites (chlorothalonil, mancozeb, or copper oxychloride). About eighty soybean leaflets from four plots repetitiond, demarcated at random in each field, were taken in each smpling. In laboratory leaflet severity was appraised and area under disease progress curve (AUDPC) calculated. Related to DSS, the AUDPC overall mean was 174 units and receiving 6.9 fungicide spraying and for FSS 26 units with 4.8 fungicide sprayings. Our results reinforce that the sowing time can be changed from the end of December to February to maintain soybean crop sustainability.

Crop Germplasm: Molecular and Physiological Perspective Towards Achieving Global Crop Sustainability

Germplasm is a long-term resource management mission and investment for civilization. For both food and nutritional health, the present changing environmental scenario has become an urgent universal concern. Multiple excellent studies have been previously performed, although the advancement and innovation of practices will require the exploration of the potentiality of crop germplasm. In this study, we emphasized (i) germplasm activates, current challenges and ongoing trends of the crop germplasm, and (ii) how the system biology will be helpful to understand the complex traits such as water use efficiency (WUE), and nitrogen use efficiency (NUE) to mitigate challenges for sustainable development under growing food requirement and climate change conditions. We focused on a vision for transforming PGR into a bio-digital resource system, for the development of climate-smart crops for sustainable food production. Moreover, this review attempted to address current challenges, research gaps and describe the advanced integrated strategies that could provide a platform for future crop improvement research.

Resistance to ‘Candidatus Liberibacter asiaticus,’ the Huanglongbing Associated Bacterium, in Sexually and/or Graft-Compatible Citrus Relatives

Huanglongbing (HLB) is the most destructive, yet incurable disease of citrus. Finding sources of genetic resistance to HLB-associated ‘Candidatus Liberibacter asiaticus’ (Las) becomes strategic to warrant crop sustainability, but no resistant Citrus genotypes exist. Some Citrus relatives of the family Rutaceae, subfamily Aurantioideae, were described as full-resistant to Las, but they are phylogenetically far, thus incompatible with Citrus. Partial resistance was indicated for certain cross-compatible types. Moreover, other genotypes from subtribe Citrinae, sexually incompatible but graft-compatible with Citrus, may provide new rootstocks able to restrict bacterial titer in the canopy. Use of seedlings from monoembryonic species and inconsistencies in previous reports likely due to Las recalcitrance encouraged us to evaluate more accurately these Citrus relatives. We tested for Las resistance a diverse collection of graft-compatible Citrinae species using an aggressive and consistent challenge-inoculation and evaluation procedure. Most Citrinae species examined were either susceptible or partially resistant to Las. However, Eremocitrus glauca and Papua/New Guinea Microcitrus species as well as their hybrids and those with Citrus arose here for the first time as full-resistant, opening the way for using these underutilized genotypes as Las resistance sources in breeding programs or attempting using them directly as possible new Las-resistant Citrus rootstocks or interstocks.

Development of an application to make knowledge available to the farmer: Detection of the most suitable crops for a more sustainable agriculture

Precision agriculture has different strategies to collect, process and analyze different types and nature data to be able to make decisions that improve the efficiency, productivity, quality, profitability and sustainability of agricultural production. Specifically, crop sustainability is directly related to reducing costs for farmers and minimizing environmental impact. In this paper, an application to help in the decision making about the most convenient type of crop to plant in a certain zone is developed, taking into account the climate conditions of that zone, in order to make a sustainable crop. This application is integrated within the Internet of Things system, which can be adapted and parameterized for any kind of crop and zone. The Internet of Things system components are described in detail and a fuzzy clustering model is proposed for the system’s intelligent module. This fuzzy model focuses on making a zone grouping (management zones), taking into account the zone climate conditions. The model manages fuzzy data, which allows us more extensive information and a more natural data treatment. A real study case of the proposed application is presented using data from the Region of Murcia (Spain). In this study case, the entire deployed Internet of Things system has been described, the fuzzy model to group similar areas in terms of meteorology has been validated and evaluated and the recommendation module has been implemented, taking into account the actual production data and the needed resources for the crops in the Region of Murcia (Spain).

A Systematic Literature Review on Cash Crop Production

Works of literature have clearly attested to the fact that cash crop production as a global phenomenon has a track of history. Past and contemporary scholars on economics, agriculture, and history show little commitment to the subject matter of cash crop production globally. Related studies are reviewed in order to develop sensible solutions and add value to the limited sources on the area (finding). Thus, this research aims at a systematic literature review of relevant literature on cash crop production. Literature that relates to the subject matter is assembled, examined, and incorporated according to the need of this systematic literature review. We focus on the studies that encompass cash crop sustainability, cash crop smallholders/small-scale/households, cash crop farming/farmers, cash crop and food production, groundnut production, sustainable groundnut production, groundnut seed production, groundnut small-holders farmers, and contribution, impact, and the role of groundnut production on the economy.