Estimate Cotton Water Consumption from Shallow Groundwater under Different Irrigation Schedules

Shallow groundwater is considered an important water resource to meet crop irrigation demands. However, limited information is available on the application of models to investigate the impact of irrigation schedules on shallow groundwater depth and estimate evaporation while considering the interaction between meteorological factors and the surface soil water content (SWC). Based on the Richards equation, we develop a model to simultaneously estimate crop water consumption of shallow groundwater and determine the optimal irrigation schedule in association with a shallow groundwater depth. A new soil evaporation function was established, and the control factors were calculated by using only the days after sowing. In this study, two irrigation scheduling methods were considered. In Method A, irrigation was managed based on the soil water content; in Method B, irrigation was based on the crop water demand. In comparison with Method B, Method A was more rational because it could use more groundwater, and the ratio of soil evaporation to total evapotranspiration was low. In this model, the interaction between meteorological factors and the SWC was considered to better reflect the real condition; therefore, the model provided a better way to estimate the crop water consumption.

Hazelnuts (Corylus avellana L.) from Spontaneous Flora of the West Part of Romania: A Source of Nutrients for Locals

In this study, the nutritional potential of some hazelnut varieties from the spontaneous flora of Romania was analyzed as a means to increase the sustainability of the local production. The chemical composition from hazelnuts (Corylus avellana L.) from spontaneous flora was determined in terms of mineral substances, protein, as well as essential and non-essential amino acids. The eight amino acids investigated had the following average values: Arg—0.68 g/100 g, Phe—0.415 g/100 g, Ser—0.277 g/100 g, Glu—0.188 g/100 g, Asp—0.133 g/100 g, Pro—0.038 g/100 g, and Lys—0.031 g/100 g. The average values of metal content were in the ranges: 88.39–146.98 µg·g−1 (Fe); 96.93–123.23 µg·g−1(Zn); 46.68–100.38 µg·g−1 (Cu); 26.00–87.78 µg·g−1 (Mn); 4.87–32.19 µg·g−1 (Ni); 1.87–2.84 µg·g−1 (Cr); and 1.29–1.86 µg·g−1 (Cd). Crude protein content values were in the range 16.33–22.31%. In order to harness this nutritional potential, the variety with superior quality indices was included, in the form of flour, in biscuit-type baked goods that were characterized from nutritional and sensory points of view. The results showed that the content of polyphenols increased with the addition of hazelnut flour, as did the content of polyunsaturated fatty acids.

Non-Chemical Approaches to Control Postharvest Gray Mold Disease in Bell Peppers

Bell pepper (Capsicum annuum) is a widely grown vegetable crop that is nutritious and flavorful and economically important for growers worldwide. A significant limiting factor in the postharvest storage and long-distance transport of peppers is gray mold caused by Botrytis cinerea. The pathogen is widespread in nature, highly aggressive, and able to cause disease at cool refrigerated temperatures during transport and storage. Fungicides have been relied on in the past to reduce bell pepper rots in storage; however, concern over residues on the fruit and environmental degradation have heightened the importance of natural and generally recognized as safe (GRAS) solutions that effectively limit disease. Essential oils, plant extracts, inorganic chemicals, biocontrols, defense activators, hot water treatments, and modified storage conditions have been tested to reduce losses from gray mold. Despite significant amounts of research on natural methods of control of B. cinerea postharvest, research specific to gray mold in peppers is limited. The objective of this review is to summarize the research conducted with environmentally friendly alternatives to chemical fungicides to control this important pathogen of peppers postharvest. To ensure a steady supply of healthy and nutritious produce, more research is needed on the development, use, and application of non-hazardous Botrytis control methods. Until an effective solution is found, using a combined approach including environmental controls, sanitation, and GRAS products remain paramount to limit Botrytis fruit rot of peppers postharvest.

Novel Sequencing and Genomic Technologies Revolutionized Rice Genomic Study and Breeding

Rice is one of the most important food crops worldwide. Population growth and climate change posed great challenges for further rice production. In the past decade, we have witnessed an explosive development in novel sequencing and genomic technologies. These technologies have been widely applied in rice genomic study and improvement processes, and contributed greatly to increase the efficiency and accuracy of rice breeding. On the other hand, novel sequencing and genomic technologies also promote the shift of breeding schemes from conventional field selection processes to genomic assisted breeding. These technologies have revolutionized almost every aspect of rice study and breeding. Here, we systematically sorted out and reviewed the progress and advancements of sequencing and genomic technologies. We further discussed how these technologies were incorporated into rice breeding practices and helped accelerate the rice improvement process. Finally, we reflected on how to further utilize novel sequencing and genomic technologies in rice genetic improvement, as well as the future trends of advancement for these technologies. It can be expected that, as the sequencing and genomic technologies will develop much more quickly in the future, and be combined with novel bioinformatics tools, rice breeding will move forward into the genomic assisted era.

A Deep Learning-Based Sensor Modeling for Smart Irrigation System

The use of Internet of things (IoT)-based physical sensors to perceive the environment is a prevalent and global approach. However, one major problem is the reliability of physical sensors’ nodes, which creates difficulty in a real-time system to identify whether the physical sensor is transmitting correct values or malfunctioning due to external disturbances affecting the system, such as noise. In this paper, the use of Long Short-Term Memory (LSTM)-based neural networks is proposed as an alternate approach to address this problem. The proposed solution is tested for a smart irrigation system, where a physical sensor is replaced by a neural sensor. The Smart Irrigation System (SIS) contains several physical sensors, which transmit temperature, humidity, and soil moisture data to calculate the transpiration in a particular field. The real-world values are taken from an agriculture field, located in a field of lemons near the Ghadap Sindh province of Pakistan. The LM35 sensor is used for temperature, DHT-22 for humidity, and we designed a customized sensor in our lab for the acquisition of moisture values. The results of the experiment show that the proposed deep learning-based neural sensor predicts the real-time values with high accuracy, especially the temperature values. The humidity and moisture values are also in an acceptable range. Our results highlight the possibility of using a neural network, referred to as a neural sensor here, to complement the functioning of a physical sensor deployed in an agriculture field in order to make smart irrigation systems more reliable.

A Network Analysis for Environmental Assessment in Wine Supply Chain

In the agri-food sector, the Life Cycle Assessment method (LCA) is used to evaluate the environmental impact of a product. Within agri-food products, wine is among the most analysed products, not only for its economic importance but also for the environmental impact of its activity. The paper aims to identify the main trends in the wine sector revolving around environmental evaluation using the LCA method in the academic literature. The aim is to investigate the literature on life cycle assessment analysis of grape and wine production through the systematic grouping of papers into clusters of research. So, the purpose is to discuss the gaps and insights identified by the study in order to aid in the development of a comprehensive state of the art on the topic. Scopus and Web of Science were used to search all articles following a clear and replicable protocol. The results (keywords) were subjected to co-occurrence analysis using VOSviewer, after which the articles were further analysed. Through a bibliographic coupling analysis, the research results were grouped through a network analysis that allowed identifying the research trends on the topic. Three clusters were identified containing the main lines of research on the subject. The results show that nowadays the literature is focusing on concerns related to climate change and consumer awareness on sustainability issues and certifications as well as environmental impacts generated mainly in the production phase in the vineyard. The research results are of interest for future research on LCA analysis in the wine sector in order to contribute to the discussion on the current model in the global wine sector.

Exploiting Plant Functional Diversity in Durum Wheat–Lentil Relay Intercropping to Stabilize Crop Yields under Contrasting Climatic Conditions

Relay intercropping is considered a valuable agroecological practice to increase and stabilize crop yields while ensuring the provision of several ecosystem services as well as sustainability and resilience to changing climatic conditions. However, farmers are still reluctant in the use of intercropping practices since there is a huge knowledge gap regarding the time of sowing, sowing ratio, crop stand density, and cultivar choice. In this study, we carried out a 3-year field experiment in Central Italy to assess the effect of relay intercropping on the agronomic performance and competitiveness of winter durum wheat (Triticum durum Desf. cv. Minosse) and spring lentil (Lens culinaris Medik. cv. Elsa) under a low-input management system, comparing different crop stand types (monocrop vs. intercrop) and target plant densities (350 plants m2—full dose vs. 116 plants m2—1/3 dose). The results revealed that intercropping increased grain yield compared to monocropping: significantly (p < 0.0001) against both monocrops in 2021 and non-significantly against durum wheat in 2019 and 2020. Yield advantage in both intercropping systems ranged between 164 and 648%. Durum wheat competitiveness was stronger in 2019 and 2021, while lentil was the most competitive component in 2020. Intercropping favored P accumulation in durum wheat shoots. There was no difference in grain yield of both crops between the highly- and lowly-dense system in 2020 and 2021. Both intercropping strategies were as effective as mechanical hoeing in controlling weeds and proved beneficial in stabilizing lentil productivity. Further economic analysis capturing the additional costs incurred in intercropping and mechanical weeding would highlight the magnitude of profitability of these systems.

The Impact of Microbial and Botanical Insecticides on Grape Berry Moths and Their Effects on Secondary Pests and Beneficials

According to the European Directive 2009/128/EC and the subsequent provisions activated in member states, conventional pesticides should be progressively replaced by “non-chemical tools and/or measures”. The identification of reliable alternatives to pesticides is crucial to achieve this objective. A European project (PURE) was funded to investigate this topic with reference to annual and perennial crops. In this framework, a number of natural insecticides, in particular microbial and botanical ones (Bacillus thuringiensis subsp. kurstaki, Beauveria bassiana, azadirachtin, pyrethrins and spinosad) were selected to test their effectiveness against grape berry moths, the key pests in most European vineyards. Trials were conducted in 2011 and 2012 in two experimental vineyards located in Italy (Tuscany and Veneto regions), following a randomized block design. Additional investigations were carried out in the Veneto region during 2013. Trial results stressed the high performance of spinosad and B. thuringiensis in controlling berry moth densities and the related damage. The use of B. bassiana mixed with B. thuringiensis did not significantly improve the impact of B. thuringiensis alone. Azadirachtin, and especially pyrethrins, proved to be less effective on berry moths than previous insecticides. The use of selected insecticides caused side-effects on a number of secondary pests, in particular leafhoppers. In 2011, densities of Empoasca vitis were more abundant in spinosad-treated plots probably because of a reduced egg parasitism rate. One year later, population densities of Zygina rhamni were more abundant on spinosad and pyrethrin-treated plots. This trend was confirmed on spinosad-treated plots in the last experimental year. At the same time, spinosad and pyrethrins significantly reduced the predatory mite populations compared to other treatments. The use of these insecticides in viticulture is discussed in the framework of organic viticulture and Integrated Pest Management (IPM).

Ecophysiological Crop Modelling Combined with Genetic Analysis Is a Powerful Tool for Ideotype Design

Improving the grain yield of crops in both favourable and stressful environments is the main breeding objective required to ensure food security. In this review, I outline a genotype-to-phenotype approach that exploits the potential values of quantitative genetics and process-based crop modelling in developing new plant types with high yields. The effects of quantitative trait locus (QTL), for traits typically at the single-organ level over a short time scale, were projected for their impact on crop growth during the whole growing season in the field. This approach can provide more markers for selection programmes for specific environments whilst also allowing for prioritization. Crop modelling is thus a powerful tool for ideotyping under contrasting conditions, i.e., use of single-environment information for predicting phenotypes under different environments.

Effect of Different Tillage Systems on Soil Organic Carbon and Enzymatic Activity

The aim of the study was to compare the effect of conventional, simplified, and organic farming systems on changes in the content of soil organic carbon, organic matter fractions, total nitrogen, and the enzymatic activity. The research was conducted from 2016–2018 on arable land in the south-eastern part of Poland. The selected soils were cultivated in conventional tillage (C_Ts), simplified tillage (S_Ts), and organic farming (O_Fs) systems. The analyses were performed in soil from the soil surface layers (up to 25 cm depth) of the experimental plots. The highest mean contents of soil organic carbon, total nitrogen, and organic matter fractions were determined in soils subjected to the simplified tillage system throughout the experimental period. During the study period, organic carbon concentration on surface soil layers under simplified tillage systems was 31 and 127% higher than the soil under conventional tillage systems and organic farming systems, respectively. Also, the total nitrogen concentration in those soils was more than 40% and 120% higher than conventional tillage systems and organic farming systems, respectively. Moreover, these soils were characterised by a progressive decline in SOC and Nt resources over the study years. There was no significant effect of the analysed tillage systems on the C:N ratio. The tillage systems induced significant differences in the activity of the analysed soil enzymes, i.e., dehydrogenase (DH) and catalase (CAT). The highest DH activity throughout the experiment was recorded in the O_Fs soils, and the mean value of this parameter was in the range of 6.01–6.11 μmol TPF·kg−1·h−1. There were no significant differences in the CAT values between the variants of the experiment. The results confirm that, regardless of other treatments, such as the use of organic fertilisers, tillage has a negative impact on the content of SOC and organic matter fractions in the O_Fs system. All simplifications in tillage reducing the interference with the soil surface layer and the use of organic fertilisers contribute to improvement of soil properties and enhancement of biological activity, which helps to maintain its productivity and fertility.