Crop Production Challenges Research Articles

Integration of organic amendments and phosphate-solubilizing bacteria improves wheat growth and yield by modulating phosphorus availability and physiological reponses

Saline calcareous soil presents significant challenges for crop production due to its poor nutrient availability and adverse effects on plant growth. Hence this study aimed to investigates the impact of integrating organic amendments—specifically Moringa seed residues, biogas manure, and vermicompost (Ver)—with and without phosphate-solubilizing bacteria (PSB), alongside two types of phosphatic fertilizers, ordinary super phosphate (OSP) and rock phosphate (RP), on the growth, yield, and nutrient uptake of wheat plants in saline calcareous soil conditions. The results indicate that the combined application of Ver + PSB, particularly when paired with OSP, consistently yields superior outcomes across all measured parameters, followed by Ver + PSB with RP. Notably, the Ver + PSB with OSP treatment exhibits the highest values across several key parameters: chlorophyll levels (chlorophyll a at 1.8, chlorophyll b at 0.84, and carotenoids at 0.72 mg g−1f wt), proline at 38.5 μg g−1 DW, relative water content at 80.76%, membrane stability index at 67.62%, as well as net photosynthetic rate (Pn), transpiration rate (Tr), and stomatal conductance (gs). Furthermore, this treatment showcases the highest antioxidant enzyme activities (Superoxide dismutase, SOD at 9.27 A564 min−1 g−1 protein, Catalase, CAT at 78.53 A564 min−1 g−1 protein, Peroxihdase, POX at 1.86 A564 min−1 g−1 protein), as well as NPK content and uptake in wheat straw and grains. Additionally, it leads to significant increases in wheat growth parameters, including plant height, straw weight, grain weight, 1000 grain weight, and protein content. However, it also results in a notable decrease in other parameters such as total soluble sugars and nonenzymatic antioxidants (Ascorbate, AsA; Total glutathione, GsH; and α-Tocopherol, α-TOC).

Predicting Subsurface Drainage Requirement for Different Soil Desalinization Goals in Coastal Reclamation Areas

ABSTRACTBuilding subsurface drainage systems for more efficient salt leaching with the natural rainfall or artificial irrigation is a widely accepted practice for saline soils reclamation, but the high initial cost of the system construction often limits its adoption, and the uncertainty in drainage intensity requirement to meet desired desalinization goals for field crop production challenges the system design. In this paper, we proposed a soil desalinization model based on the field hydrology model‐DRAINMOD, predicted number of years required to lower soil salinity to a threshold level under different subsurface drainage conditions, and estimated the net return from different subsurface drainage system layout based on a case study in a coastal reclamation area in eastern China. The results showed that, DRAINMOD accurately predicted water table fluctuations in artificially drained fields: the root mean square error to standard deviation ratio (RSR) was 0.4 and 0.54, and the Nash Sutcliffe efficiency (NSE) was 0.84 and 0.68, respectively, during the model calibration and validation periods. The DRAINMOD based soil desalinization model predicted a negative relationship between subsurface drainage intensity and the soil desalinization period, that is, improving drainage condition shortened the time requirement for soil desalinization. For the study area, the model's predictions showed that installing subsurface drainage at 20 m spacing and 1.2 m deep lowered soil salinity to the slightly saline level in less than 7 years under the rainfall leaching only, and such system layout produced the maximum economic return based on the local agricultural practice. The results indicate that, early investment in adequate subsurface drainage systems is beneficial for field crop production in the salt impacted farmland areas. Findings from this research may provide technical references for saline soil reclamation or land improvement in both rain fed and irrigated agricultural areas.

Genome-wide association analysis reveals novel candidate loci and a gene regulating tiller number in orchardgrass

Tillers are specialized lateral shoots arising from axillary buds at basal nodes, and are also an important agronomic trait that determines the aboveground biomass and grain yield of various gramineous crops. So far, few genes have been reported to control tiller formation and most have been in the annual crop rice (Oryza sativa). Orchardgrass (Dactylis glomerata) is an important perennial forage crop with great economic and ecological value, but its genes regulating tillering have remained largely unknown. In the present study, we used a natural population of 264 global orchardgrass germplasms to determine genes associated with quantitative variation in tiller number through genome-wide association study analysis. A total of 19 putative loci and 55 genes associated with tiller number were thus identified. Additionally, 26 putative differentially expressed genes with tiller number, including DgCYC-C1, were identified by RNA-seq and genome-wide association study analysis. DgCYC-C1 which is involved in cell division, was overexpressed, revealing that DgCYC-C1 positively regulates tiller number. These results provide some new candidate genes or loci for the improvement of tiller number in crops, which might advance new sustainable strategies to meet global crop production challenges.

ARTIFICIAL INTELLIGENCE BASED SUSTAINABLE COTTON CROP PRODUCTION USING REMOTE SENSING DATASET

The decline in cotton production in Pakistan has directly impacted the country's foreign exchange earnings, plummeting from twelve million bales in 1991, the number decreased to four million bales in 2020. Considering a substantial portion of Pakistan's exports are linked to the textiles area, with 40% of jobs tied to production, this decline is concerning. Factors such as climate change and changes in biotic and abiotic stresses have contributed to substantial losses in cotton production. In Pakistan, where 90% of farmers face resource constraints, there is a pressing need for more accurate mechanisms to understand the challenges in crop production. Timely acknowledgment and adoption of more flexible approaches to irrigation, fertilizer application, and pest and disease control are crucial. Excessive use of pesticides has exacerbated the situation, leading to the development of resistance among pests and diseases. Traditional visual inspection methods alone are insufficient for predicting crop health effectively, resulting in deprived crop yields and financial losses for agrarians. Enhancing crop health condition requires leveraging information gathered from remote sensing and terrestrial sensors, along with truth field surveys. By processing this data through tools like the Decision Support System for Agrotechnology Transfer (DSSAT) and employing machine learning techniques such as artificial neural networks, more accurate local and field-level advice can be provided to farmers. This approach aims to optimize crop management practices, reduce losses, and ultimately improve farmers' incomes.

Tomato yield and soil chemical properties influenced by low–molecular–weight organic acids in calcareous soil

<p>Calcareous soils have restrictive characteristics that limit and pose a challenge for crop production; in this environment, plants can exude low-molecular-weight organic acids (LMWOAs). This study aimed to verify the influence of exogenously applied LMWOAs in calcareous soils on tomato yield and the chemical characteristics of soil and leachate. <em>Solanum lycopersicum</em> L. seedlings were grown in pots containing calcareous soil in a greenhouse, fertilized by drip irrigation with Steiner nutrient solution in which the treatments 0.1 mM citric acid (CA), 0.1 mM oxalic acid (OA), 0.01 mM salicylic acid (SA) and a control without LMWOAs (T0) were prepared, applied during the whole growth cycle. The experiment was repeated four times, with twenty replicates per treatment, under a completely randomized design. The yield per plant was quantified, while pH and microbial respiration (RMS) were measured in the soil. The pH, electrical conductivity (EC), oxidation-reduction potential (ORP), carbonate (CO<sub>3</sub><sup>2–</sup>), and bicarbonate (HCO<sub>3</sub><sup>–</sup>) contents were quantified in the leachates. SA application reduced the soil pH (8.75). SA and CA improved the fruit yield per plant by 11% and 33%, respectively (p < 0.05). CA induced a 1.7% reduction in leachate pH (p < 0.05) and a 15.9% increase in HCO<sub>3</sub><sup>–</sup> content (p < 0.05). SA decreased EC and CO<sub>3</sub><sup>2–</sup> concentrations by 8.9 and 23.1% (p < 0.05), but increased HCO<sub>3</sub><sup>–</sup> content by 23.1 % (p < 0.05). The use of LMWOAs as a strategy in the management of calcareous soils can promote favorable conditions for tomato yield per plant.</p>

From swamp to field: how genes from mangroves and its associates can enhance crop salinity tolerance.

Salinity stress is a critical challenge in crop production and requires innovative strategies to enhance the salt tolerance of plants. Insights from mangrove species, which are renowned for their adaptability to high-salinity environments, provides valuable genetic targets and resources for improving crops. A significant hurdle in salinity stress is the excessive uptake of sodium ions (Na+) by plant roots, causing disruptions in cellular balance, nutrient deficiencies, and hampered growth. Specific ion transporters and channels play crucial roles in maintaining a low Na+/K+ ratio in root cells which is pivotal for salt tolerance. The family of high-affinity potassium transporters, recently characterized in Avicennia officinalis, contributes to K+ homeostasis in transgenic Arabidopsis plants even under high-salt conditions. The salt overly sensitive pathway and genes related to vacuolar-type H+-ATPases hold promise for expelling cytosolic Na+ and sequestering Na+ in transgenic plants, respectively. Aquaporins contribute to mangroves' adaptation to saline environments by regulating water uptake, transpiration, and osmotic balance. Antioxidant enzymes mitigate oxidative damage, whereas genes regulating osmolytes, such as glycine betaine and proline, provide osmoprotection. Mangroves exhibit increased expression of stress-responsive transcription factors such as MYB, NAC, and CBFs under high salinity. Moreover, genes involved in various metabolic pathways, including jasmonate synthesis, triterpenoid production, and protein stability under salt stress, have been identified. This review highlights the potential of mangrove genes to enhance salt tolerance of crops. Further research is imperative to fully comprehend and apply these genes to crop breeding to improve salinity resilience.

Review on physiological and ecological characteristics and agronomic regulatory pathways of intercropping to delay root-canopy senescence of crops

Intercropping has been widely used in arid and semi-arid regions because of its high yield, and stable productivity, and efficient utilization of resources. However, in recent years, the high yield of traditional intercropping is mainly attributed to the large amount of purchased resources such as water and fertilizer, plastic film, and mechanical power. It leads to the decline of cultivated land quality and the phenomenon of premature root-canopy senescence of intercrops is become increasing serious. So, the application of traditional intercropping faces major challenges in crop production. In this paper, the manifestations, occurrence mechanisms, and agronomic regulatory pathways of crop senescence were analyzed in detail. The physiological and ecological characteristics of intercropping to delay root-canopy senescence of crops are reviewed in this paper. The main agronomic regulatory pathways of intercropping to delay root-canopy senescence of crops are based on above- and blow-ground interactions, include collocation of crop varieties, spatial arrangement, water and fertilizer management, and tillage and mulch practices. Future research fields of intercropping to delay root-canopy senescence should focus on the aspects of selecting and breeding special varieties, application of molecular biology techniques, and developing or applying models to predict and evaluate root-canopy senescence process of intercrops. Comprehensive analysis and evaluation of different research results could provide a basis for enhancing intercropping delay root-canopy senescence through adopting innovative technologies for regulating physio-ecological characteristics of intercrops. This would provide support for the development and adoption of high-yield, efficient, and sustainable intercropping systems in arid and semi-arid areas with more people and less land, and abundant light and heat resources.

Revolutionizing agriculture with artificial intelligence: plant disease detection methods, applications, and their limitations.

Accurate and rapid plant disease detection is critical for enhancing long-term agricultural yield. Disease infection poses the most significant challenge in crop production, potentially leading to economic losses. Viruses, fungi, bacteria, and other infectious organisms can affect numerous plant parts, including roots, stems, and leaves. Traditional techniques for plant disease detection are time-consuming, require expertise, and are resource-intensive. Therefore, automated leaf disease diagnosis using artificial intelligence (AI) with Internet of Things (IoT) sensors methodologies are considered for the analysis and detection. This research examines four crop diseases: tomato, chilli, potato, and cucumber. It also highlights the most prevalent diseases and infections in these four types of vegetables, along with their symptoms. This review provides detailed predetermined steps to predict plant diseases using AI. Predetermined steps include image acquisition, preprocessing, segmentation, feature selection, and classification. Machine learning (ML) and deep understanding (DL) detection models are discussed. A comprehensive examination of various existing ML and DL-based studies to detect the disease of the following four crops is discussed, including the datasets used to evaluate these studies. We also provided the list of plant disease detection datasets. Finally, different ML and DL application problems are identified and discussed, along with future research prospects, by combining AI with IoT platforms like smart drones for field-based disease detection and monitoring. This work will help other practitioners in surveying different plant disease detection strategies and the limits of present systems.

Unveiling the potential of Daldinia eschscholtzii MFLUCC 19-0629 through bioactivity and bioinformatics studies for enhanced sustainable agriculture production

Endophytic fungi constitute a rich source of secondary metabolites that can be manipulated to produce desirable novel analogs for combating current agricultural challenges for crop production, especially controlling plant disease. The endophytic fungus Daldinia eschscholtzii MFLUCC 19-0629, was newly isolated from tropical ancient plants, Oncosperma sp., and displays a broad-spectrum of antifungal and antibacterial activities against several plant pathogens including Ralstonia solanacearum, Fusarium oxysporum, Colletotrichum gloeosporioides, Colletotrichum acutatum, Stagonosporopsis cucurbitacearum, Corynespora cassiicola and Stemphylium spp. A high-quality genome sequence was obtained using Oxford nanopore technology, the accuracy and length of reads resulting in no need for Illumina or other sequencing techniques, for D. eschscholtzii MFLUCC 19-0629, resulting in a genome size of 37.56 Mb assembled over 11 contigs of significant size, likely to be at the chromosomal level. Bioinformatics analysis revealed that this strain is biosynthetically talented encoding 67 predicted biosynthetic gene clusters (BGCs). Only eight of the 67 BGCs matched or demonstrated high similarity to previously characterized BGCs linked to the production of known secondary metabolites. The high number of predicted unknown BGCs makes this strain a promising source of novel natural products. The discovery that D. eschscholtzii MFLUCC 19-0629 has a broad spectrum of antimicrobial activity against seven major plant pathogenic microorganisms relevant to crop production and its complete genome sequence carries immense importance in the advancement of novel microbial biocontrol agents (MBCAs). This also unveils the prospect of uncovering new compounds that could be utilized for sustainable agriculture and pharmaceutical purposes.

Heat stress and sexual reproduction in maize: unveiling the most pivotal factors and the greatest opportunities.

The escalation in the intensity, frequency, and duration of high-temperature (HT) stress is currently unparalleled, which aggravates the challenges for crop production. Yet, the stage-dependent responses of reproductive organs to HT stress at the morphological, physiological, and molecular levels remain inadequately explored in pivotal staple crops. This review synthesized current knowledge regarding the mechanisms by which HT stress induces abnormalities and aberrations in reproductive growth and development, as well as by which it alters the morphology and function of florets, flowering patterns, and the processes of pollination and fertilization in maize (Zea mays L.). We identified the stage-specific sensitivities to HT stress and accurately defined the sensitive period from a time scale of days to hours. The microspore tetrad phase of pollen development and anthesis (especially shortly after pollination) are most sensitive to HT stress, and even brief temperature spikes during these stages can lead to significant kernel loss. The impetuses behind the heat-induced impairments in seed set are closely related to carbon, reactive oxygen species, phytohormone signals, ion (e.g. Ca2+) homeostasis, plasma membrane structure and function, and others. Recent advances in understanding the genetic mechanisms underlying HT stress responses during maize sexual reproduction have been systematically summarized.

Challenges and Adaptation Practices of Farmers on Climate Change

Climate change presents the agricultural industry with unforeseen difficulties, impacting livelihoods, food security, crop productivity, and sustainability. This descriptive study aims to illuminate the prevalent challenges in production and cropping patterns experienced by farmers due to climate change, along with their primary adaptation practices to mitigate adverse effects. It employs statistical tools such as ranking, mean, standard deviation, frequency count, and percentage distribution for data analysis. The respondents primarily consisted of high school graduate women with extensive farming experience and land ownership. Results indicate that climate change has exacerbated challenges in crop production, with low yields, pest and disease outbreaks, and flood damage being the most prominent issues. Farmers encounter numerous challenges in deciding on cropping patterns, mainly due to limited knowledge about viable techniques such as crop mapping, intercropping, pest and nutrient management, and water scarcity in non-irrigated fields. The results also show that farmers have adopted several strategies, including reducing the use of pesticides and petroleum-based fertilizers, conserving water during dry seasons, and improving drainage and soil mulching to prevent weed growth. Interestingly, indigenous methods have also been continuously utilized to mitigate the effects of climate change. This emphasizes the importance of innovative farming methods and ongoing farmer education initiatives for capacity building. Additionally, the results found no statistically significant association between challenges and adaptation practices.

Intelligent Farming based on Uncertainty Expert System with Butterfly Optimization Algorithm for Crop Recommendation

Meeting the current population's food demands has become challenging, given the rising population, frequent climate fluctuations, and limited resources. Smart farming, also known as precision agriculture, has emerged as an advanced approach to tackle modern challenges in crop production. At the heart of this cutting-edge technology is machine learning, serving as the driving force behind its implementation. Though, there are many algorithms are available in crop prediction process, the problem of predicting vague information is still a challenging issue. Unfortunately, existing algorithms mostly avoids the complicated instances in crop recommendation dataset by not handling them effectively, due to imbalance class distribution. Hence in this research work to conduct an intelligent farming, two different uncertain theories are adopted to handle the issue of vagueness in appropriate recommendation of crop by considering soil fertility and climatic condition. The proposed is developed based on uncertainty expert system with both neutrosophicalparaconsistent inference model. The neutrosophic inference model is integrated with the paraconsistent logic to overcome the problem of uncertainty in prediction of appropriate crop by representing the factors in terms of certainty degree and contradiction degree. The rule generated by paraconsistent model is validated to improve the accuracy of crop prediction by fusing the knowledge of butterfly optimization algorithm. The nectar searching behavior of the butterflies are used for searching potential rules as a validation process. With the pruned rules generated by uncertainty expert model, the suitable crop is predicted more accurately compared to the other existing prediction models.

Yield and nutritional responses of quinoa (Chenopodium quinoa Willd.) genotypes to irrigated, rainfed, and drought-stress environments

This study aimed to select higher-yielding and drought-tolerant quinoa (Chenopodium quinoa Willd.) lines suitable for cultivation in the U.S. Midwest, where water scarcity poses a common challenge for crop production. Quinoa, known as a superfood and climate-smart crop, is rich in nutrients, possesses resilience to abiotic stress, and is ideal for sustainable food production and supporting nutritional security in the face of changing climate conditions. To achieve this goal, 128 quinoa germplasms, collected from the USDA-ARS-GRIN, were evaluated. Among those lines, ten quinoa lines were selected for further assessment and evaluated at four different locations in Missouri, United States. Evaluations were conducted under three environments: irrigated, rainfed, and drought stress, over 2 years (summer of 2021 and 2022). Two of the selected ten lines, Ames13746 and PI614927, produced higher yields across various locations and environments. Remarkably, these lines demonstrated significantly higher grain yields under drought stress compared to irrigated and rainfed conditions. However, there was no significant difference in grain yield between irrigated and rainfed environments. Notably, despite the presence of moisture stress, the concentration of essential amino acids remained unaffected, while there was a slight decrease in the total protein content under drought-stress conditions. These research results and selected genotypes can potentially facilitate quinoa production in the U.S. Midwest regions prone to water stress, contributing to food security and sustainable agricultural practices.

Assessment and Characterization of Agricultural Salt-Affected Soils around Abaya and Chamo Lakes, South Ethiopia Rift Valley

Soil salinity/sodicity is becoming a challenge for crop production in Ethiopia’s semi-arid and arid regions. However, more information on soil salinity/sodicity needs to be available around Abaya and Chamo Lakes, South Ethiopia Rift Valley. This study aimed to assess and characterize soil salinity/sodicity and determine salt-affected soils’ morphological, physical, and chemical properties. The representative soil pits that were 60 ∗ 60 ∗ 60 cm in size were examined, and samples were taken from 0–20, 20–40, and 40–60 cm depths based on the criteria set for agricultural salt-affected soil studies. The soil properties determined include soil color, structure, consistency, bulk density, particle density, porosity, texture, pH, EC, SAR, ESP, CEC, BS, OC, TN, available P, CaCO3−, exchangeable bases, and soluble ions (Na+, Ca2+, Mg2+, K+, Cl−, SO4−2, NO3−, CO3−2, and HCO3−. The soil-analyzed results were rated and interpreted following a guide to standardized analysis methods for soil data. The results of this study reveal that the soils had considerable heterogeneity in soil morphological, physical, and chemical properties. The soils of the study site were highly alkaline and had very high sodium content, very high CEC value, and low levels of organic carbon and exchangeable calcium. The dominant soluble cation was sodium, followed by magnesium, calcium, and potassium in all soil depths of the pits. Similarly, Cl− was dominant among the anions throughout the soil depth, followed by HCO3−, SO42−, and NO3−. The findings of this study imply that removing sodium and salts from the soil depth may improve the salt-affected soils’ productivity in the study area. Application of organic amendments, including manures and crop residues, may also be beneficial in increasing fertility and organic matter content.

The Splicing Factor OsSCL26 Regulates Phosphorus Homeostasis in Rice.

Phosphorus (P) is an essential nutrient for plant growth. However, its deficiency poses a significant challenge for crop production. To overcome the low P availability, plants have developed various strategies to regulate their P uptake and usage. In this study, we identified a splicing factor, OsSCL26, belonging to the Serine/arginine-rich (SR) proteins, that plays a crucial role in regulating P homeostasis in rice. OsSCL26 is expressed in the roots, leaves, and base nodes, with higher expression levels observed in the leaf blades during the vegetative growth stage. The OsSCL26 protein is localized in the nucleus. Mutation of OsSCL26 resulted in the accumulation of P in the shoot compared to the wild-type, and the dwarf phenotype of the osscl26 mutant was alleviated under low P conditions. Further analysis revealed that the accumulated P concentrations in the osscl26 mutant were higher in the old leaves and lower in the new leaves. Furthermore, the P-related genes, including the PHT and SPX family genes, were upregulated in the osscl26 mutant, and the exclusion/inclusion ratio of the two genes, OsSPX-MFS2 and OsNLA2, was increased compared to wild-type rice. These findings suggest that the splicing factor OsSCL26 plays a pivotal role in maintaining P homeostasis in rice by influencing the absorption and distribution of P through the regulation of the transcription and splicing of the P transport genes.

Granular and powdered lime improves soil properties and maize (Zea mays l.) performance in humic Nitisols of central highlands in Kenya

Acidic soils pose a major challenge for crop production in heavily weathered tropical soils, especially due to the high toxicity of aluminum (Al), low cation exchange capacity, and low availability of phosphorus (P) to plants. Lime application was recommended to alleviate soil acidity problems. Granular CaCO3 lime was introduced into the Kenyan market as an alternative to powdered CaCO3 and CaO-lime for small Kenyan farms, providing uniform distribution and efficient application. The aim of this study was therefore to investigate the effectiveness of different types of powdered and granular lime individually and in combination with mineral fertilizers in improving soil properties and maize yield. The study was conducted at two sites, Kirege (extremely acidic) and Kangutu (moderately acidic). Experiments were conducted in a randomized complete block design repeated four times in two consecutive seasons: long rain (LR) in 2016 and short rain (SR) in 2016. Three types of lime were applied before planting. Selected chemical properties of the soil were analyzed before and after the experiment. Maize and stover yield data were collected and analyzed. Results showed that lime application significantly increased soil pH and decreased exchangeable acidity. Powdered calcium carbonate (CaCO3) showed the highest pH increase in both extreme (+19%) and moderate (+14%) acid sites. All types of lime and fertilizer applications alone significantly increased the available soil P at both the seasonal and site levels. However, maize grain yield was lower with fertilizer alone or lime alone than with lime and fertilizer combination. Powdered CaCO3+ fertilizer was found to give the highest grain yields on both very acidic (5.34 t ha-1) and moderately (3.71 t ha-1) acid sites. In the study, combining powdered CaCO3 lime with fertilizers was most effective in improving acidic soils by decreasing soil acidity and increasing available phosphorus, which ultimately increased grain yield. The results of this study recommend the use of powdered CaCO3 as an effective and practical solution for farmers facing soil acidification problems.

Biological Agent Trichoderma asperellum and Its in Vitro Inhibitory Activity Against Mango Fruit Rot Pathogens

Diseases are one of the major challenges in crop production which can lead to significant economic losses. Ironically, while having multiple negative impacts, synthetic chemical pesticides are considered the main strategy in tackling plant diseases. Trichoderma asperellum is one of the potential fungal species that can inhibit numerous plant diseases. This study reconfirmed the morphological characteristics of Trichoderma isolates obtained and identified it by molecular techniques. In addition, the inhibitory activity of the isolates was tested in vitro against the mango pathogens Colletotrichum asianum and Diaporthe pseudophoenicicola. The results showed that isolate T4 was identified as Trichoderma asperellum. Isolate T4 was able to inhibit C. asianum and D. pseudophoenicicola by 28.19% and 15.64%, respectively. Therefore, this isolate can be used as a biological agent to control plant pathogens in an environmentally friendly, sustainable manner, and as an alternative to synthetic chemical pesticides.

Effects of soil water and nitrogen on drought resilience, growth, yield, and grain quality of a spring wheat

Drought imposes a significant challenge for crop production. However, little is known about the impact of drought priming and nitrogen (N) application and their interactive effects on drought resilience, yield, and grain quality in wheat. Spring wheat (cv. Stettler) was grown in plastic pots (25 cm diameter) with high, moderate, and low soil water levels and received N (added N) or without N (no N added), and subjected to acute drought for 10 days, then rewatering at the tillering stage. Canopy temperature, maximum efficiency of photosystem II, and normalized difference vegetation index were measured at 3-day intervals during drought-recovery periods to quantify drought resistance and resilience. Above-ground dry matter, straw dry matter, seed dry matter, harvest index, and grain N, phosphorus (P), and zinc (Zn) concentrations were determined. Both moderate- and low-water-grown plants had higher drought resistance than high-water-grown plants. The addition of N alleviated acute drought stress in high- and moderate-water-grown plants but exacerbated drought stress in low-water-grown plants. Both high and moderate water resulted in higher grain yields, but had a lower harvest index than low water. The highest and lowest grain N were observed in the low- and high-water-grown plants, respectively. The addition of N increased N and N:P in grains but decreased grain Zn:N. This study showed that moderate drought priming along with N application can improve drought resistance, yield, and grain quality. The results also indicated that canopy thermal imaging is a useful tool for high-throughput quantification of the drought resistance of wheat.

Green manure and maize intercropping with reduced chemical N enhances productivity and carbon mitigation of farmland in arid areas

Keeping high productivity and low soil carbon emission (CE) while reducing chemical fertilizer is a significant challenge for crop production in developing modern agriculture. A field experiment was conducted to evaluate the effect of intercropping green manure with reduced N on maize productivity and carbon mitigation in northwestern China. The field experiment used a split-plot design with three replicates. Three cropping patterns were maize-common vetch intercropping (M/V), maize-rape intercropping (M/R), and sole maize (M). Two N fertilizer rates formed the subplots: the conventional N rate was reduced by 25% (N1: 270 kg ha−1) and the conventional N rate (N2: 360 kg ha−1). The compensation effect (TCE, %) was used to quantify the degree of recovery of intercropping green manure on maize grain yield (GY) under N reduction. It was shown by the results that the negative effect of N reduction on maize GY was compensated by intercropping green manure. Maize-common vetch intercropping integrated with N reduction (M/VN1) had a more substantial compensation effect (TCE) with the planting years lengthening, and TCE was 1.0%, 0.9%, 4.1%, and 4.9% in 2018, 2019, 2020, and 2021, respectively. The CE of the cropping system was decreased by intercropping green manure compared to sole maize. The CE in the intercropping system was further decreased by N reduction, and the CE of M/RN1 and M/VN1 was decreased by 27.7% and 32.1%, respectively, compared to MN2 (i.e., the control). Finally, the CE of the intercropping system was decreased by M/VN1 by 6.5% compared to M/RN1 in 2019–2021. We used the ratio of net primary productivity to carbon emission (NPP/CE) to determine soil C sequestration (CS) potential. Intercropping green manure with N reduction in enhancing soil CS mainly occurred in the late growth period of maize. Over the four years of study, the ratios of NPP/CE for M/RN1 and M/VN1 were 23.3% and 32.9%, respectively, greater than that of MN2; also, it of M/VN1 was increased by 8.9% compared to M/RN1 in 2019–2021. M/VN1 had great potential for enhancing soil CS. Thus, adding green manure as an intercropping component in the maize cropping system while reducing chemical N fertilizer is a promising system to enhance maize productivity and carbon mitigation in the farmlands of arid areas.

A review of core agricultural robot technologies for crop productions

It has become a common understanding that robotization could be one of effective solutions to address the increasing skilled labor shortage challenge in crop production, thus the research and development of agricultural robotic technologies has become a popular topic in recent years, with numerous innovative new technologies, methodologies and applications being published at various resources. This article intends to provide a systematic overview of the recent achievements on core agricultural robotic technologies for crop productions, mainly on three aspects of (1) mobile platforms and in-field navigation technologies; (2) actuation mechanisms and end-effector technologies; and (3) target detection and operation planning technologies. This article also briefly introduces a few recent reported successes in developing robotic solutions for various field operations, such as transplanting, weeding, harvesting, and pruning, as evidences of promising.