Search

In the context of India's evolving economy, where agriculture remains a vital yet limited sector, the challenge is to enhance productivity on finite cultivable land. This research addresses this imperative by introducing the Crop Yield Prediction Using Deep Learning (CYPBL) model, leveraging the Bi-Directional Long Short-Term Memory (Bi-LSTM) algorithm. Employing soil health and crop yield data from the Government of India, the CYPBL model is implemented through PySpark for scalability. Featuring 20 LSTM layers with a 12 × 1 input shape, including a bidirectional LSTM layer, the model achieves exceptional accuracy at 99.5 percent on test data. With a focus on real-time data, a batch size of 1 ensures optimal responsiveness. Beyond technological advancements, CYPBL emerges as a groundbreaking soil health monitoring system, bridging the gap between experts and farmers. By empowering farmers with insights into soil conditions, crop suitability, and improvement strategies, this research paves the way for data-driven, responsive agriculture in India and globally, contributing to the pressing issue of global food security. [ABSTRACT FROM AUTHOR]

Over 50% of India's population relies on crop growing, making it the foundation of the country's economy. Differences in weather, temperature, and other environmental factors are now a significant threat to the continued success of agriculture. This makes it difficult to predict the crop yield appropriately. Hence, computer-based models are believed to be more predictive in analyzing crop yields. Machine learning (ML) and deep learning (DL) models play a vital role as the supporting tool for Crop Yield Prediction (CYP), which includes assisting decisions on which crops to plant and the measures to be taken for the growth of crops. This paper aims to propose a deep ensemble model for predicting crop yields more accurately. The steps followed are: Improved Log scaling-based pre-processing of data. Then, from the preprocessed data, the input features like higher-order features, Enhanced entropy-based features and correlation-based features are derived. Further, the optimal features are elected using the Integrated Bird Swarm and BOA (IBS-BOA) algorithm. Based on the selected features, prediction is done by the Deep Ensemble Model (DMO, Bi-GRU and CNN). Also, one of the models of Ensemble classifiers, CNN is trained by the IBS-BOA algorithm. Finally, the performance of the proposed DEC-IBSBOA is evaluated concerning varied error factors namely, MEAE, MAE, MALE, MAPE, ME and MSE. For the suggested system minimum error is obtained for MAE (~ 1.0) when compared to the other existing methods such as Bi-GRU, DMO, CNN, PLMDC, SVM, LSTM, SSTNN, EC + WOA, EC + BES, EC + BOA, EC + BMO and EC + BSA. [ABSTRACT FROM AUTHOR]

The objective of modern agriculture includes environmental sustainability, low production costs, and higher productivity. Biostimulants are composed of humic acids, hormones, algae extracts, plant growth-promoting bacteria, amino acids, and a chain of peptides. Black gram and soybean crops are of immense economic significance. The growth and yield of these crops are limited by supply of nutrients. The potentiation of the early growth of plants by treating seeds with these substances has been one of the adopted alternatives, which often promote physiological changes that stimulate growth. The field experiment was conducted with randomized complete block design and replicated four times. Effects of different biostimulants at different concentrations as foliar spray and seed treatment were examined on growth, yield parameters, and yield of black gram (TAU-1) and soybean (JS-335) during kharif 2020 and 2021. Results showed that foliar application of Quantis biostimulant @ 5 ml L−1 recorded higher growth, yield parameters, and seed yield (897 kg ha−1), biological yield (1209 kg ha−1), production efficiency (13.00 kg day−1 ha−1) in black gram and seed treatment with Epivio Energy @ 2 ml kg−1 fetched higher seed yield (1403 kg ha−1), biological yield (2914 kg ha−1), production efficiency (16.13 kg day−1 ha−1) along with higher growth and yield parameters in soybean. It can be concluded that they will help in achieving higher growth and yield of black gram and soybean. [ABSTRACT FROM AUTHOR]

ABSTRACT Drought is one of the most severe environmental factors limiting plant growth and crop yield, necessitating the identification of genes that enhance drought resistance for crop improvement. Through screening an ethyl methyl sulfonate‐mutagenized rice mutant library, we isolated the PEG tolerance mutant 97‐1 (ptm97‐1), which displays enhanced resistance to osmotic and drought stress, and increased yield under drought conditions. A point mutation in OsMATE6 was identified as being associated with the drought‐resistant phenotype of ptm97‐1. The role of OsMATE6 in conferring drought resistance was confirmed by additional OsMATE6 knockout mutants. OsMATE6 is expressed in guard cells, shoots and roots and the OsMATE6‐GFP fusion protein predominantly localizes to the plasma membrane. Our ABA efflux assays suggest that OsMATE6 functions as an ABA efflux transporter; mutant protoplasts exhibited a slower ABA release rate compared to the wild type. We hypothesize that OsMATE6 regulates ABA levels in guard cells, influencing stomatal closure and enhancing drought resistance. Notably, OsMATE6 knockout mutants demonstrated greater yields under field drought conditions compared to wild‐type plants, highlighting OsMATE6 as a promising candidate for improving crop drought resistance. [ABSTRACT FROM AUTHOR]

Nitrogen is an essential nutrient for plants and a major determinant of plant growth and crop yield. Plants acquire nitrogen mainly in the form of nitrate and ammonium. Both nitrogen sources affect plant responses and signaling pathways in a different way, but these signaling pathways interact, complicating the study of nitrogen responses. Extensive transcriptome analyses and the construction of gene regulatory networks, mainly in response to nitrate, have significantly advanced our understanding of nitrogen signaling and responses in model plants and crops. In this study, we aimed to generate a more comprehensive gene regulatory network for the major crop, rice, by incorporating the interactions between ammonium and nitrate. To achieve this, we assessed transcriptome changes in rice roots and shoots over an extensive time course under single or combined applications of the two nitrogen sources. This dataset enabled us to construct a holistic co-expression network and identify potential key regulators of nitrogen responses. Next to known transcription factors, we identified multiple new candidates, including the transcription factors OsRLI and OsEIL1, which we demonstrated to induce the primary nitrate-responsive genes OsNRT1.1b and OsNIR1. Our network thus serves as a valuable resource to obtain novel insights in nitrogen signaling. [ABSTRACT FROM AUTHOR]

BACKGROUND: Low recovery of conventional fertilizers remains a significant bottleneck for maize production globally. In particular, with phosphate fertilization, zinc (Zn) is prone to precipitation in soil, reducing recovery of both phosphorus (P) and Zn by maize. RESULTS: The present study was designed to investigate the synergistic effect of zinc oxide (ZnO) nanoparticles (NPs) and P on maize crop growth, yield, and nutrient uptake under ZnO seed coating and foliar application in a randomized complete block design. However, plants were subjected to two ZnO NPs levels (0.5 and 12 kg ha−1) amended with two P levels (45 and 90 kg ha−1). ZnO NPs, especially in the form of foliar application, with a P dose of 90 Kg ha−1 significantly (P < 0.05) improved maize crop growth, yield, and nutrient uptake compared with control. In comparison with the control group, plants grown in these conditions absorbed higher levels of Zn and P. Zn uptake rose to 16.34 g ha−1, 137.88 g ha−1, and 166.89 g ha−1 in roots, grains, and stover respectively, and P uptake increased to 0.80 mg kg−1, 10.066 mg kg−1, and 12.17 mg kg−1 respectively. Additionally, seed emergence rate, plant height, and cob length increased by up to 2%, 1177 cm2, and 3.3 cm respectively compared with control. Furthermore, Zn use efficiency was increased up to 38.55% in ZnO NPs foliar application. CONCLUSIONS: Application of ZnO NPs at 0.5 kg ha−1 in the form of foliar application with 90 kg ha−1 P dose produced a more pronounced increment in the parameters studied than ZnO NPs seed coating did. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Saline soils pose significant challenges to global agricultural productivity, hindering crop growth and efficiency. Despite various mitigation strategies, the issue persists, underscoring the need for innovative and sustainable solutions. One promising approach involves leveraging microorganisms and their plant interactions to reclaim saline soils and bolster crop yields. This review highlights pioneering and recent advancements in utilizing multi-traits Trichoderma and Bacillus species as potent promoters of plant growth and health. It examines the multifaceted impacts of saline stress on plants and microbes, elucidating their physiological and molecular responses. Additionally, it delves into the role of ACC deaminase in mitigating plant ethylene levels by Trichoderma and Bacillus species. Although there are several studies on Trichoderma-Bacillus, much remains to be understood about their synergistic relationships and their potential as auxiliaries in the phytoremediation of saline soils, which is why this work addresses these challenges. [ABSTRACT FROM AUTHOR]

Background Results Conclusion Maize, wheat, rice and soybean production are intimately linked to food security. Identifying the key factors affecting crop yields and determining the countries where increased irrigation and nitrogen application most effectively enhance yields are essential steps towards achieving sustainable development goals and ensuring food security. Identifying these areas is crucially dependent on yield gaps. However, the lack of comparability between different regions in current regional‐scale yield gap studies stems from varied methodologies. Moreover, global yield gap research, relying on statistical models and regression methods, tends to neglect the crop growth process. In this study, we used a random forest model, based on statistical and meteorological data, to pinpoint the key factors influencing crop yields. Subsequently, using unified yield data from the Inter‐Sectoral Impact Model Intercomparison Project (ISIMIP), derived from crop models simulations, we applied the yield gap method to calculate the potential yield increase for four crops across countries, under conditions of full irrigation and nitrogen application.Our research finds that nitrogen application is the main factor affecting yields globally, while irrigation plays a crucial role in the major producing countries. The countries with high potential for yield increases are located at the border between Africa and Eurasia. The global average yield of the four major crops increased 13.7–29.8% under full irrigation, 2.9–39.1% under full nitrogen application and 29.4–97.8% under both conditions.This study provides crucial insights into global crop yield changes and their determinants, which are highly important for global sustainable agriculture and food security efforts. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Phosphorous (P) is a limiting macronutrient for crop growth. Its deficiency prevents plant development leading to an extensive use of phosphatic fertilizers globally. Bio-organic phosphate (BOP) fertilizer provides a sustainable approach to optimize nutrient availability, enhance crop yield, and mitigate the negative impacts of chemical fertilizers on the environment. Therefore, the present study integrates the application of heat-tolerant phosphate-solubilizing bacteria, rock phosphate, and organic materials for the development of BOP. For this purpose, potential heat-tolerant phosphate-solubilizing bacteria (PSB) were isolated from major wheat-growing areas of southern Punjab. Five isolates were the efficient phosphate solubilizers based on in vitro phosphate-solubilizing activity (291-454 μg ml-1 and 278-421 μg ml-1) with a concomitant decrease in pH (up to 4.5) at 45°C and 50°C, respectively. These PSB were used for the development of potential consortia that are compatible and showed high P solubilization. In planta evaluation of these PSB consortia in a pot experiment under net house conditions showed that consortium-2 had a favorable impact on growth parameter with enhanced grain yield (9.63 g plant-1) and soil available P (10 μg g-1) as compared with 80% uninoculated control. The microcosm study was conducted to evaluate PSB consortium-2 integrated with carrier material (plant material and filter mud) and rock phosphate as BOP increased total phosphorous (14%) as compared with uninoculated controls. Plant-based BOP showed higher viable count (3.5 × 108\u00B0CFU) as compared with filter mud-based BOP. Furthermore, the effect of BOP on wheat growth parameters revealed that BOP showed a promising influence on grain yield (4.5 g plant-1) and soil available P (10.7 μg g-1) as compared with uninoculated 80 and 100% controls. Principle component analysis (PCA) further validates a positive correlation between BOP with grain weight and plant height and soil available P as compared with both 80 and 100% controls. For the first time, this study reports the combined application of bio-organic phosphate fertilizer and heattolerant PSB, which offers an eco-friendly option to harvest better wheat yield with low fertilizer input. [ABSTRACT FROM AUTHOR]

Background: Optimum crop growth and yield is result of interlinking of several factors. In semi- tropical soil in central plateau and hills zone are deficit in organic carbon and NPK content; therefore inadequate fertilization may leads to pure quality and also lower crop productive capacity of soil. For the maintenance of sustainable and productive production, maintaining soil health is a critical factor. Under low fertility levels, mungbean gives low seed yield. Potassium humate, nitrogen and phosphorus (RDF) application may be increase yield of mungbean in this zone. Methods: A field experiment was conducted to study, “Nodulation, yield attributes and yield of mungbean [Vigna radiata (L.)] influenced by different level of potassium humate and fertility level”. The experiment was carried out in factorial randomized block design with three replications and sixteen treatment combination. Result: Result showed that total number of root nodules, effective nodules, fresh and dry weight of root nodules, leghaemoglobin, nodule index, no. of pods/plant, no. of seeds/pod, test weight, seed and straw yield were observed significantly higher with application of potassium humate @ 4.5 kg/ha. Among different fertility level, the application of 100% RDF significantly increased the total number of root nodules and effective nodules, fresh and dry weight of root nodules, leghaemoglobin, nodule index, no. of pods/plant, no. of seeds/pod and test weight, seed and straw yield. With combined application of potassium humate @ 3.0 Kg/ha + 75% RDF significantly higher no. effective nodules, dry weight of root nodules and seed yield were observed, as well as saving of 25% RDF and 1.5 kg potassium humate were also observed. [ABSTRACT FROM AUTHOR]

Cold stress has severe negative consequences for plant growth and crop yield. Here, we report that an Arabidopsis thaliana mutant that lacks the HPE1 gene, which encodes an RNA‐binding protein, maintains higher photosynthetic activity under cold stress, together with higher accumulation of thylakoid proteins. We showed that HPE1 interacts with MORF2 and MORF9 and thereby mediates RNA editing in chloroplasts. Loss of HPE1 function increased the editing efficiency at four RNA editing sites, rpoC‐488, ndhB‐149, ndhB‐746 and matK‐706, under cold stress and altered the expression of nuclear photosynthesis‐related genes and cold‐responsive genes. We propose that HPE1‐mediated RNA editing acts as a trigger for retrograde signaling that affects photosynthesis under cold stress. [ABSTRACT FROM AUTHOR]

BACKGROUND: Root‐zone hole fertilization has a positive impact on enhancing crop production and fertilization efficiency. However, a suitable spacing for hole fertilization in rapeseed cultivation is unclear. To explore an adaptive hole spacing for improving rapeseed yield and fertilization efficiency, field experiments were conducted. Four spacings of hole fertilization were designed: 10 (FD10), 20 (FD20), 30 (FD30) and 40 cm (FD40), using no fertilization (F0) and deep‐banded placement of fertilizer (DBP) as controls. The burial depth was 10 cm for FD and DBP treatments. RESULTS: Compared to DBP, hole fertilization impacted soil microenvironment, crop growth and yield components, resulting in a significant increase of 28.4% in seed yield and 25.6% in oil yield. Seed yield in FD20 (4345.43 kg ha−1) increased by 4.3%, 9.4% and 15.1% compared to FD10, FD30 and FD40, respectively. Fertilizer partial factor productivity under FD20 was 4.2%, 8.6% and 13.9% greater than FD10, FD30 and FD40, respectively; whereas the increase for agronomic efficiency was 6.0%, 12.7% and 21.0%, and the increase for N recovery efficiency was 39.5%, 52.5% and 62.9%, respectively. CONCLUSION: Fertilization with a hole spacing of 17 cm is a promising practice to maintain high production and fertilization efficiency when cultivating rapeseed. These results provide a theoretical foundation and scientific basis for improving rapeseed productivity and fertilizer utilization. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Roots and associated soil biota are key to the energy balance of plants since they consume substantial amounts of photosynthates and in turn provide resources that fuel photosynthesis. Due to spatiotemporal soil heterogeneity, single root systems are repeatedly exposed to soil conditions that either foster or limit plant growth. Knowledge concerning the root responses to repeated cycles of edaphic stress remain scarce but is indispensable to understand root foraging behaviour in soil. Quantification of the acclimative value of root responses to soil heterogeneity requires distinction between plastic (i.e., persistent) and elastic (i.e., reversible) root responses. We introduce energy balances as an approach to capture the effects of repeated edaphic stress cycles on crop growth and yield formation and to quantify the acclimative value of root responses to specific soil environments. Spatiotemporal soil heterogeneity and the resulting edaphic stress cycles can be decisive for crop growth. However, our understanding of the acclimative value of root responses to heterogeneous soil conditions remains limited. We outline a framework to evaluate the acclimative value of root responses that distinguishes between stress responses that are persistent and reversible upon stress release, termed 'plasticity' and 'elasticity', respectively. Using energy balances, we provide theoretical evidence that the advantage of plasticity over elasticity increases with the number of edaphic stress cycles and if responses lead to comparatively high energy gains. Our framework provides a conceptual basis for assessing the acclimative value of root responses to soil heterogeneity and can catalyse research on crop adaptations to heterogeneous belowground environments. [ABSTRACT FROM AUTHOR]

Soybean is a crucial crop utilized for both food and oil production, with balanced crop nutrition being a key determinant of soybean yield throughout its growth cycle. Sulfur, an essential nutrient for crop growth, substantially impacts soybean yield. In this study, two soybean cultivars, Laidou 2 and Hefeng 55, were used to study the changes in nitrogen, phosphorus, potassium, and sulfur contents in soybean plants at different growth stages. Additionally, the effects of dry matter accumulation under five different sulfur levels were examined. The results showed that the sulfur levels had varying effects on the nitrogen, phosphorus, potassium, and sulfur contents and accumulation in different parts of the soybean plants. There were marked differences in the accumulation and distribution of dry matter in different parts of the soybean plant. Soybean dry matter weight shows the best overall performance under the S80 treatment. With increasing sulfur nutrition, the nitrogen, phosphorus, potassium, and sulfur contents in various plant parts exhibited an unimodal trend, reaching maximum values when the sulfur content was 80 mg/L. This study elucidates the dynamic changes in nutrient elements in soybeans under different sulfur levels and is important in guiding the rational application of sulfur fertilizers in agricultural production. [ABSTRACT FROM AUTHOR]

Nitrogen (N) is one of the most crucial elements for crop yields. N management is incredibly important because it’s a major component of crop productivity. It is challenging to control due to the large field variability of the innate soil N and the differences in crop demand at various crop growth stages. Additionally, N’s partial factor production is deteriorating day by day. Furthermore, crop, cultivar, and environmental factors affect how much N is needed. Therefore, crop production depends heavily on applying N at the right rate for the crop’s needs. Precision N management increases N use efficiency while reducing N loss from runoff, ammonia volatilization, and leaching. By providing N during crucial growth phases, real-time N management increases use efficiency by applying N based on need at the appropriate time and amount. One aspect of real-time N management is the application of the leaf color chart (LCC). The LCC is a relatively basic, low-cost, portable, and user-friendly gadget that contrasts the color of the leaf with the device’s color hues. Because farmers typically prefer dark-colored leaves, they apply N regardless of need, which poses serious risks to the ecosystem and contaminates the surface and groundwater. The sustainability of output is threatened by the declining soil health caused by increased fertilizer application. Therefore, for small and marginal farmers, employing a leaf color chart for site-specific N management is a more practical solution. [ABSTRACT FROM AUTHOR]

The high-throughput and full-time acquisition of images of crop growth processes, and the analysis of the morphological parameters of their features, is the foundation for achieving fast breeding technology, thereby accelerating the exploration of germplasm resources and variety selection by crop breeders. The evolution of embryonic soybean radicle characteristics during germination is an important indicator of soybean seed vitality, which directly affects the subsequent growth process and yield of soybeans. In order to address the time-consuming and labor-intensive manual measurement of embryonic radicle characteristics, as well as the issue of large errors, this paper utilizes continuous time-series crop growth vitality monitoring system to collect fulltime sequence images of soybean germination. By introducing the attention mechanism SegNext_Attention, improving the Segment module, and adding the CAL module, a YOLOv8-segANDcal model for the segmentation and extraction of soybean embryonic radicle features and radicle length calculation was constructed. Compared to the YOLOv8-seg model, the model respectively improved the detection and segmentation of embryonic radicles by 2% and 1% in mAP50-95, and calculated the contour features and radicle length of the embryonic radicles, obtaining the morphological evolution of the embryonic radicle contour features over germination time. This model provides a rapid and accurate method for crop breeders and agronomists to select crop varieties. [ABSTRACT FROM AUTHOR]

Introduction: Jordan suffers from agricultural land degradation, water scarcity, increasing in population, and the huge gap between production and consumption. Boosting of food production to meet the demand is one of the solutions. Biofertilizers are substances include beneficial microorganisms (e.g., bacteria) that are important in agricultural soil to improve yield through different mechanisms. The aim of this experiment is to study the impact of using locally produced-microorganisms along with chemical fertilizers to improve the yield of cucumber planting. Methods: The experiment was carried out in a greenhouse equipped with all requirements for planting. The planting process of cucumber seedling was implemented using pots filled with soil collected from an agricultural land in the Jordan Valley, and mixed with manure, and categorized in three plots. Mixture of three types of microorganisms (STIMULANT A and B, and PHYTOEM) along with chemical fertilizers were applied to the soil in some pots. Plants growth and agricultural parameters were observed. Data about crop yield, water consumption, leaf area, and chlorophyll were collected. Lab analysis of soil characteristics was also done to assess the impact of the products on soil. Results: The results showed that the yield production was the maximum in the plot of combining the benefits of biological and the chemical fertilizers compared to the control plot by 48%. The same plot showed water saving with 32.4% over the control plot. The bacterial biofertilizers enhanced the seedling growth all the time during the experiment by 14% more than the plants in the control plot. The average leaves area in plot with bio-products was 22.6% bigger than the control plot. In addition, the chlorophyll test indicated that the chlorophyll content was more in plot with biofertilizers. According to the soil analysis, the presence of bacterial biofertilizers enhanced the plant’s absorption of nutrients, and accordingly the EC decreased in the soil. Discussion: The results of the experiment showed superiority of plot using the bacterial biofertilizers along with the chemical fertilizer, over the plots either using the chemical fertilizers alone or the bacterial biofertilizers alone. This can be attributed to the addition of bacterial biofertilizers with the chemical fertilizers in appropriate conditions. Our findings highlight the potential for bacterial biofertilizers to significantly improve crop yields and resource efficiency, contributing to food system transformation. This aligns with the UN Sustainable Development Goals, particularly SDG 2 (Zero Hunger) and SDG 15 (Life on Land), by offering sustainable agricultural solutions. [ABSTRACT FROM AUTHOR]

The decline in soil productivity due to intensive cultivation, unbalanced fertilization and climate change are key challenges to future food security. There is no significant research conducted on the effect of organic amendments on soil properties and active carbon fractions in organic-matter deficient soils under changing climate. Biochar (BC) is a stabilized organic amendment produced from organic materials and is increasingly recognized as being able to improve soil health and crop productivity. The present study was conducted to determine the efficacy of compost (CM) (0.5%, 1%) (w/w) and animal manure (AM) (0.5%, 1%) (w/w) alone and combined with 3% (w/w) biochar, on soil carbon fractions, soil properties, and crop growth in a low-fertile soil. The results revealed significant increased 46% plant height, 106% and 114% fresh and dry shoot weight respectively, and 1,000-grain weight increased up to 40% when 3% BC with 1% CM was applied, compared to a control. Similarly, substantial increases in 69% soil organic matter, and 70% carbon pool index were observed at 3% BC, and under 3% BC with 1% CM increased 11% microbial biomass carbon compared to the control. Overall, the results suggest that 3% BC addition along with 1% CM and AM (1%) had greater potential to improve the soil carbon pool, microbial biomass, and soil health, all of which will ultimately enhance maize yield when grown in low-fertility soil. The application of BC, CM, and AM are a viable green approach, that not only boosts crop yields and improves soil properties and but also contributes to a circular economy. [ABSTRACT FROM AUTHOR]

To better promote the research and development of regional crop yield simulations, we review related research on regional crop yield simulations over the past ten years, summarize the research progress on regional crop yield simulations at home and abroad from the three aspects of crop growth models, remote sensing technology, and data assimilation technology, and propose three future development directions for regional crop yield simulations: (1) Based on the agronomic mechanism of crop yield estimation, it is necessary to fully consider crop growth characteristics and yield formation mechanisms. (2) With respect to the remote sensing mechanism of crop yield estimation, we can consider combining radar stereo lateral view measurement technology to determine crop characteristics and remote sensing information. (3) From the perspective of combining agronomy and remote sensing, the crop yield spatiotemporal simulation assimilation algorithm should be optimized, and the yield simulation unit should be extended. It is expected that these considerations can provide new ideas for regional crop yield simulations with high accuracy, a large scale, and full coverage. [ABSTRACT FROM AUTHOR]

Aims: Film mulching has been widely used for increasing crop yields in semiarid areas, but its long-term impact on crop performance and soil quality remains poor. This study aims at investigating the long-term effects of different mulching methods on the crop root growth and soil aggregates stability. Methods: A continuous experiment for eight years was set to assess the effects on the soil aggregates stability, root traits, and yield under five different treatments: (i) control method comprising flat planting without mulching (CK), (ii) flat planting with half film mulching (P), (iii) film mulching on ridges and planting in narrow furrows (S), (iv) full film mulching on double ridges (D), and (v) film mulching on ridges and planting in wide furrows (R). Results: The soil quality improved significantly after continuous film mulching for eight years. Compared with CK, mulching decreased the soil bulk density, and increased the soil porosity, soil macroaggregate content (7.39%-22.92% by dry-sieving, and 8.49%-21.67% by wet-sieving), and soil aggregate stability, especially under S and D. Mulching could promote the root growth (root length, root diameter, root surface area, and root volume) distinctly, while S and D increased the average root biomass by 17.27% compared with R and P. The improved soil structure and root traits under mulching increased the yield (29.98–63.96%), and the average yield under S was 1.32%, 25.7%, and 26.14% higher than those under D, R, and P, respectively. Conclusions: In general, the best improved soil aggregate fractions and stability was found under film mulching on ridges and planting in narrow furrows (S), which was significantly associated with the root traits improvement, and thus increasing the crop yield. Therefore, it can be considered an effective mulching pattern for increasing and stabilizing the crop yield in the Loess Plateau region of China. [ABSTRACT FROM AUTHOR]

Salinity stress has a great impact on crop growth and productivity and is one of the major factors responsible for crop yield losses. The K-homologous (KH) family proteins play vital roles in regulating plant development and responding to abiotic stress in plants. However, the systematic characterization of the KH family in rice is still lacking. In this study, we performed genome-wide identification and functional analysis of KH family genes and identified a total of 31 KH genes in rice. According to the homologs of KH genes in Arabidopsis thaliana, we constructed a phylogenetic tree with 61 KH genes containing 31 KH genes in Oryza sativa and 30 KH genes in Arabidopsis thaliana and separated them into three major groups. In silico tissue expression analysis showed that the OsKH genes are constitutively expressed. The qRT-PCR results revealed that eight OsKH genes responded strongly to salt stresses, and OsKH12 exhibited the strongest decrease in expression level, which was selected for further study. We generated the Oskh12-knockout mutant via the CRISPR/Cas9 genome-editing method. Further stress treatment and biochemical assays confirmed that Oskh12 mutant was more salt-sensitive than Nip and the expression of several key salt-tolerant genes in Oskh12 was significantly reduced. Taken together, our results shed light on the understanding of the KH family and provide a theoretical basis for future abiotic stress studies in rice. [ABSTRACT FROM AUTHOR]

Background: Vermicomposting or the conversion of organic wastes into fertile manure by earthworms has long been used in agriculture to increase production of crops. Chemical composition of vermicompost determines the quality and its use in increasing crop yield. It is important to carry out compositional analysis of the vermicompost samples if different substrates are used for their preparation. Methods: In this study, we prepared vermicompost using earthworm Eisenia fetida (old name Eisenia foetida) and different organic wastes, namely wheat straw, bagasse, grass, neem leaves etc. The nutrient content (C, H, N, S, P, K and Humic Acid) was determined for each sample and the effect on plant growth was also observed. Result: It was observed that despite the source of vermicompost, nutrient content was always higher in vermicompost than control organic waste. It was also seen that among the different sources, neem leaves and wheat straw gave rise to the most nutritious compost. The effect on plants was also seen to be much better with these vermicompost samples compared to control without added vermicompost. It was observed that the C/N ratio of the organic wastes significantly decreased during vermicompost, which indicates the increase in nitrogen concentration easily available to plants. Not only were we able to obtain better growth of plants, we were also able to transform some agricultural wastes into useful products, which otherwise would have been dumped into a landfill or burnt, both of which would have been a waste. [ABSTRACT FROM AUTHOR]

Soil compaction is generally viewed as one of the most serious soil degradation problems and a determining factor in crop productivity worldwide. It is imperative to understand the processes involved in soil compaction to meet the future global challenges of food security. In this work, we used co‐occurring keyword analysis to summarize 3491 papers on soil compaction over the past 40 years, elaborating on the main research focuses such as the causes, influencing factors, and effects of soil compaction on crops, and the mitigation and prevention of soil compaction. This review provides a comprehensive discussion of the effects of soil compaction, including altering soil structure, increasing bulk density (BD) and penetration resistance (PR), and reducing porosity and soil hydraulic properties. Notably, based on the 387 data points of 11 papers about BD, our results demonstrated soil compaction on average, increased BD by 7.6%, 6.9%, and 3.2% in the medium‐, coarse‐, and fine‐textured soils, respectively. Based on the 264 data points of 18 papers, in the 0–30 cm soil layer, compaction increased penetration resistance (by 91% in the coarse‐textured, 84.2% in the medium‐textured, and 8.8% in the fine‐textured soils). Compacted soil limits the access of crop roots to water and nutrients, leading to poor root development and reduced crop productivity. There was a difference in soil compaction sensitivity between the different crops, but crop growth and yield showed an overall worsening trend with increasing degrees of compaction. This review collected data points on 142 crop yields and found that wheat, barley, corn, and soybean yields decreased by an average of 4.1%, 15.1%, 37.7%, and 22.7%, respectively, in the BD range of 1.1–1.8 Mg/cm3 after compaction. Additionally, the effectiveness of different compaction mitigation measures, including natural, tillage, and biological, is systematically discussed. Compared with soil compaction mitigation measures, prevention should be the top priority although there is still a lack of practical prevention methods. Soil conditions and agricultural machinery type are the main factors affecting the risk of soil compaction in the process of soil compaction. Therefore, it is particularly important to optimize the soil working conditions in the field and the type of farm machinery used to reduce the risk of soil compaction. This initiative is pivotal for ensuring sustainable systems for food production and recovering crop productivity from compacted soil. [ABSTRACT FROM AUTHOR]

The advent of Internet of Things (IoT) in agriculture has revolutionized the way farmers monitor and manage their crops. IoT-enabled sensors can provide real-time data on various environmental parameters such as temperature, humidity, soil moisture, and crop growth, which can be used to make informed decisions and optimize crop yield. However, the vast amount of data generated by these sensors poses a significant challenge in terms of data processing and communication. To address this challenge, clustering is often used to group the sensors into clusters and elect a cluster head (CH) to communicate with the gateway node. The selection of an appropriate CH and the optimal path for data transmission are critical factors that affect the performance of the IoT system. In this paper, we propose a novel approach to optimize the CH selection and path selection using modified fuzzy logic, Whale optimization algorithm (WOA) and enhanced crow swarm optimization (ECSO). Fuzzy logic is used to evaluate the relevant parameters such as energy, distance, overhead, trust, and node degree to select the most suitable CH. ECSO is then employed to find the optimal path for data transmission based on the selected CH. We evaluate the proposed approach using simulation experiments in a smart agriculture scenario. The results show that the proposed approach outperforms existing approaches in terms of throughput, packet delivery ratio, delay, and energy efficiency. The proposed system demonstrates substantial advantages in terms of throughput, with a remarkable throughput value of 68 Mbps, outperforming the other methods, including EQSR (12.5 Mbps), E2S-DRL (60 Mbps), and OSEAP. The packet delivery ratio (PDR) is also significantly higher for the proposed system, reaching 90.9%. The proposed approach can significantly improve the performance of IoT-enabled smart agriculture systems, leading to better crop yield and higher profitability for farmers. The results of the simulation experiments demonstrate the superiority of the proposed approach over the existing one's throughput, packet delivery ratio (PDR), delay, and energy consumption efficiency is found in the result section. [ABSTRACT FROM AUTHOR]

Climate change can have significant impacts on crop growth, yield, water requirement and, consequently, crop water productivity. In this study, the effect of climate change under RCP2.6, RCP4.5, and RCP8.5 projection scenarios of the CanESM2 model on soybean yield and water requirement was investigated in Kermanshah, west of Iran. Crop growth was simulated using crop growth simulation models (DSSAT and AquaCrop) based on historical (1985-2015) and projected (2025-2064) weather data. Using the AquaCrop model in RCP2.6, RCP4.5, and RCP8.5 scenarios, the average increase in seasonal crop evapotranspiration (ETc) was estimated to be 9.4, 11, and 14.9%, respectively. The results of the DSSAT model showed 4.1, 8.5, and 12.1% increase in seasonal ETc under the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. Based on the AquaCrop and DSSAT models, soybean yield decreases by 5.3, 3.7, and 2% and by 5.7, 4.8, and 1.6% for the RCP8.5, RCP4.5, and RCP2.6 scenarios, respectively. The results also show a decrease in crop water productivity under climate change scenarios as a result of increased ETc and reduced grain yield. According to AquaCrop and DSSAT models, the maximum daily ETc that should be used for the design of irrigation systems will increase by 11.5 and 10.2%, respectively. [ABSTRACT FROM AUTHOR]

Lately, irrigated soybean production has increased; therefore, tools that can aid water resources management must be improved. Two experiments were carried out, the first one from May to August and the second one from September to December 2019. The experimental design included randomized blocks with five treatments and four replicates. In the control treatment (SE), irrigation was carried out to meet the crop's water demand during all growth stages. In the other treatments, irrigation was interrupted at specific crop growth stages (TI = VCV4, TII = V5-R1, TIII = R1-R5, and TIV = R5-R7), and then restored. After calibration, the model satisfactorily estimated the canopy cover, biomass, and soybean yield, with high values of determination coefficients (r² > 0.90), low RMSE and MBE values, and high values of EF. In experiment 1, the soil water content was overestimated in the SE, TI, and TIV treatments by 0.24%, 0.78%, and 0.23%, respectively, and underestimated by 3.3% and 5.5% in the TII and TIII treatments, respectively. In experiment 2, in the SE, TI, TII, TIII, and TIV treatments, the soil water content was underestimated by 6%, 3%, 4.6%, 5.9%, and 6.7%, respectively. Real evapotranspiration was overestimated in all treatments in both experiments, with low r² values in both experiments 1 (0.11-0.23) and 2 (0.04 - 0.21). [ABSTRACT FROM AUTHOR]

Remotely sensed images provide effective sources for monitoring crop growth and the early prediction of crop productivity. To monitor carrot crop growth and yield estimation, three 27 ha center-pivot irrigated fields were studied to develop yield prediction models using crop biophysical parameters and vegetation indices (VIs) extracted from Sentinel-2A (S2) multi-temporal satellite data. A machine learning (ML)-based image classification technique, the random forest (RF) algorithm, was used for carrot crop monitoring and yield analysis. The VIs (NDVI, RDVI, GNDVI, SIPI, and GLI), extracted from S2 satellite data for the crop ages of 30, 45, 60, 75, 90, 105, and 120 days after plantation (DAP), and the chlorophyll content, SPAD (Soil Plant Analysis Development) meter readings, were incorporated as predictors for the RF algorithm. The RMSE of the five RF scenarios studied ranged from 7.8 t ha−1 (R2 ≥ 0.82 with Scenario 5) to 26.2 t ha−1 (R2 ≤ 0.46 with Scenario 1). The optimal window for monitoring the carrot crop for yield prediction with the use of S2 images could be achieved between the 60 DAP and 75 DAP with an RMSE of 8.6 t ha−1 (i.e., 12.4%) and 11.4 t ha−1 (16.2%), respectively. The developed RF algorithm can be utilized in carrot crop yield monitoring and decision-making processes for the self-sustainability of carrot production. [ABSTRACT FROM AUTHOR]

Crop growth status detection is significant in agriculture and is vital in planting planning, crop yield, and reducing the consumption of fertilizers and workforce. However, little attention has been paid to detecting the growth status of each crop. Accuracy remains a challenging problem due to the small size of individual targets in the image. This paper proposes an object detection model, HR-YOLOv8, where HR means High-Resolution, based on a self-attention mechanism to alleviate the above problem. First, we add a new dual self-attention mechanism to the backbone network of YOLOv8 to improve the model's attention to small targets. Second, we use InnerShape(IS)-IoU as the bounding box regression loss, computed by focusing on the shape and size of the bounding box itself. Finally, we modify the feature fusion part by connecting the convolution streams from high resolution to low resolution in parallel instead of in series. As a result, our method can maintain a high resolution in the feature fusion part rather than recovering high resolution from low resolution, and the learned representation is more spatially accurate. Repeated multiresolution fusion improves the high-resolution representation with the help of the low-resolution representation. Our proposed HR-YOLOv8 model improves the detection performance on crop growth states. The experimental results show that on the oilpalmuav dataset and strawberry ripeness dataset, our model has fewer parameters compared to the baseline model, and the average detection accuracy is 5.2% and 0.6% higher than the baseline model, respectively. Our model's overall performance is much better than other mainstream models. The proposed method effectively improves the ability to detect small objects. [ABSTRACT FROM AUTHOR]

Background: As a newly class of endogenous phytohormones, strigolactones (SLs) regulate crop growth and yield formation by interacting with other hormones. However, the physiological mechanism of SLs affect the yield by regulating the balance of endogenous hormones of Tartary buckwheat is still unclear. Results: In this study, a 2-year field experiment was conducted on Tartary buckwheat (Jinqiao 2) to study the effects of different concentrations (0, 10, and 20 µmol/L) of artificial synthetic analogs of SLs (rac-GR24) and inhibitor of SL synthesis (Tis-108) on the growth, endogenous-hormone content, and yield of Tartary buckwheat. The main-stem branch number, grain number per plant, grain weight per plant, and yield of Tartary buckwheat continuously decreased with increased rac-GR24 concentration, whereas the main-stem diameter and plant height initially increased and then decreased. Rac-GR24 treatment significantly increased the content of SLs and abscisic acid (ABA) in grains, and it decreased the content of Zeatin (Z) + Zeatin nucleoside (ZR). Conversely, Tis-108 treatment decreased the content of SLs and ABA but increased the content of Z + ZR. Results of correlation analysis showed that the content of ABA and SLs, the ratio of SLs/(Z + ZR), SLs/ABA, and ABA/(Z + ZR) were significantly negatively correlated with the yield of Tartary buckwheat, and that Z + ZR content was significantly positively correlated with the yield. Regression analysis further showed that ABA/ (Z + ZR) can explain 58.4% of the variation in yield. Conclusions: In summary, by adjusting the level of endogenous SLs in Tartary buckwheat, the balance of endogenous hormones in grains can be changed, thereby exerting the effect on yield. The results can provide a new agronomic method for the high-yield cultivation of Tartary buckwheat. [ABSTRACT FROM AUTHOR]

Cold stress is a major meteorological threat to crop growth and yield. Abscisic acid (ABA) plays important roles in plant cold tolerance by activating the expression of cold‐responsive genes; however, the underlying transcriptional regulatory module remains unknown. Here, we demonstrated that the cold‐ and ABA‐responsive transcription factor ETHYLENE RESPONSE FACTOR 15 (ERF15) positively regulates ABA‐mediated cold tolerance in tomato. Exogenous ABA treatment significantly enhanced cold tolerance in wild‐type tomato plants but failed to rescue erf15 mutants from cold stress. Transcriptome analysis showed that ERF15 was associated with the expression of cold‐responsive transcription factors such as CBF1 and WRKY6. Further RT‐qPCR assays confirmed that the ABA‐induced increased in CBF1 and WRKY6 transcripts was suppressed in erf15 mutants when the plants were subjected to cold treatment. Moreover, yeast one‐hybrid assays, dual‐luciferase assays and electrophoretic mobility shift assays demonstrated that ERF15 activated the transcription of CBF1 and WRKY6 by binding their promoters. Silencing CBF1 or WRKY6 significantly decreased cold tolerance. Overall, our study identified the role of ERF15 in conferring ABA‐mediated cold tolerance in tomato plants by activating CBF1 and WRKY6 expression. This study not only broadens our knowledge of the mechanism of ABA‐mediated cold tolerance in plants but also highlights ERF15 as an ideal target gene for cold‐tolerant crop breeding. Summary statement: This study demonstrated that the cold‐ and abscisic acid (ABA)‐responsive transcription factor ETHYLENE RESPONSE FACTOR 15 positively regulates ABA‐mediated cold tolerance in tomato plants by activating CBF1 and WRKY6 expression. [ABSTRACT FROM AUTHOR]

Trichoderma has become one of the most studied filamentous fungi to be used as a greener and more sustainable solution for improving the production and growth of numerous crops, due to its capability to form symbiotic associations with plants. This study aimed to evaluate the effect of Trichoderma isolates obtained from the rhizosphere of organic rice fields in Sukabumi, Indonesia, in enhancing rice germination and seedling growth. A laboratory experiment used a completely randomized design consisting of seed treatments of 21 Trichoderma isolates (T1-T21) and a control treatment without Trichoderma (C). The inoculation was employed to elucidate any potential effects of Trichoderma isolates. Results showed that five isolates, i.e., T5, T7, T9, T10, and T14 stimulated the highest seedling vigor index, root and shoot length, and fresh weight and dry weight. These findings exhibited the potential of these five isolates as plant growth-promoting fungi to improve rice seedling growth and contribute to our understanding of the role of symbiotic fungi in sustainable rice crop production. [ABSTRACT FROM AUTHOR]

Digital Twin is an emerging agritech technology that involves creating virtual representations of physical systems, which can be used for various purposes, such as optimizing crop management, predicting yield, and managing resources efficiently. The research is focusing to build a accurate digital twin model for crop growth, considering factors like evaporation (ET), growing degrees days (GDD), crop type, soil data, and agricultural practices. The model handles data streams related with geolocation, IOT historical sensor data and weather forecasts streams to simulate the crop risk and yield. Frequent updates based on realtime data enhance accuracy. Aside essential water management crop flow, the model is processing historical data related with nutrients like nitrogen (N), phosphorus (P), and potassium (K) elements are vital for plant growth and health, and their optimal balance can significantly impact corn yield. The research is extended on five locations in both Romania and Luxembourg handling wheat, corn and rapeseed crop simulation. [ABSTRACT FROM AUTHOR]

Elevated surface ozone (O 3) concentrations can negatively impact growth and development of crop production by reducing photosynthesis and accelerating leaf senescence. Under unabated climate change, future global O 3 concentrations are expected to increase in many regions, adding additional challenges to global agricultural production. Presently, few global process-based crop models consider the effects of O 3 stress on crop growth. Here, we incorporated the effects of O 3 stress on photosynthesis and leaf senescence into the Decision Support System for Agrotechnology Transfer (DSSAT) crop models for maize, rice, soybean, and wheat. The advanced models reproduced the reported yield declines from observed O 3 -dose field experiments and O 3 exposure responses reported in the literature (O 3 relative yield loss RMSE <10 % across all calibrated models). Simulated crop yields decreased as daily O 3 concentrations increased above 25 ppb, with average yield losses of 0.16 % to 0.82 % (maize), 0.05 % to 0.63 % (rice), 0.36 % to 0.96 % (soybean), and 0.26 % to 1.23 % (wheat) per ppb O 3 increase, depending on the cultivar O 3 sensitivity. Increased water deficit stress and elevated CO 2 lessen the negative impact of elevated O 3 on crop yield, but potential yield gains from CO 2 concentration increases may be counteracted by higher O 3 concentrations in the future, a potentially important constraint to global change projections for the latest process-based crop models. The improved DSSAT models with O 3 representation simulate the effects of O 3 stress on crop growth and yield in interaction with other growth factors and can be run in the parallel DSSAT global gridded modeling framework for future studies on O 3 impacts under climate change and air pollution scenarios across agroecosystems globally. [ABSTRACT FROM AUTHOR]

Sweet potato is a crucial crop for food security and income generation. Sweet potato vine length, number of stems, average number of roots per plant, average root weight, marketable root yield, non-marketable root yield, and total sweet potato root yield were determined by the NPSB and nitrogen fertilizer application rates (p<0.01). Using the right fertilizer recommendations can improve crop growth and yield while minimizing resource use. Both NPSB and Nitrogen fertilizer rates had a highly significant impact on root number, root weight, marketable root yield, unmarketable root yield, and total root yield. The combination of 100 kg ha-1 NPSB fertilizer and 69 kg ha-1 of Nitrogen fertilizer gave the highest marketable root yield (553.09 qt ha-1). The treatment with 100 kg ha-1 NPSB fertilizer and 46 kg ha-1 Nitrogen fertilizer demonstrated the best result in terms of marginal rate of returns, with a marginal revenue of 17872%. To optimize sweet potato productivity in the Adola rede region, it is recommended to apply 100 kg ha-1 NPSB and 46 kg ha-1 nitrogen fertilizer. In general, cultivation in the Adola rede region can be optimized by applying a combination of 100 kg ha-1 of NPSB fertilizer and 46 kg ha-1 of nitrogen, resulting in improved plant growth and marketability, higher root yields and cost efficiency. [ABSTRACT FROM AUTHOR]

The present experiment was conducted from November 2020 to March 2021 at Sher-e-Bangla Agricultural University's Horticulture Farm in Dhaka, Bangladesh. The investigation included four levels of vermicompost (T0 = control, T1=3 t.ha-1, T2=6 t.ha-1 and T3=9 t.ha-1) and biofertilizer (F0=control, F1=3 kg.ha-1, F2=5 kg.ha-1 and F3=7 kg.ha-1) which was carried out by factorial randomized complete block design with three replications. The broccoli variety 'Green Carpet' was used as planting material. The application of the treatment T3F3 (vermicompost at 9 t.ha-1 and biofertilizer at 7 kg.ha-1) resulted in the highest plant height (67.85 cm), number of leaves per plant (22.76), leaf length (60.57 cm), leaf breadth (23.23 cm) and chlorophyll (SPAD index) (54.90). However, statistically similar results were also observed for T2F3 in most cases (vermicompost at 6 t.ha-1 and biofertilizer at 7 kg.ha-1). The maximum stem diameter (4.98 cm) was recorded in T2F3. Fewest days to achieve 100% curd initiation (54 days), maximum curd diameter (13.19 cm), yield (15.84 t.ha-1) and vitamin C (64.34 mg 100 g-1) content were recorded in T3F3. With the exception of the fewer days required to initiate curd formation, all other parameters were statistically similar to those observed in the T2F3 treatment combination. [ABSTRACT FROM AUTHOR]

The use of plastic mulch, water-soluble fertilizers, and drip irrigation has grown in popularity recently for banana (Musa acuminata L.) farming. A field experiment was carried out at Kharagpur, West Bengal, India, to examine the impact of different fertigation intervals and plastic mulch on the response of the Grand Naine cultivar of banana. A randomized complete block design with four fertigation intervals both with and without plastic mulch was used in the study. Biometric characteristics including plant height, pseudo stem girth, leaf area, number of suckers, and crop duration were measured. The outcomes demonstrated the superiority of two-day fertigation interval and black plastic mulchtreatment by displaying higher plants height, a greater stem girth, more leaf area, the greatest number of suckers, and a shorter crop duration. For both the main crop and the ratoon crop, the maximum banana production was achieved with a fertigation interval of two days alongwith black plastic mulch (T1), yielding 66.3 t/ha and 52.2 t/ha, respectively. The yield obtained under the T1 treatment was statistically similar to the fertigation intervals of bi-weekly and weekly treatments for both main and ratoon crops. Fertigation intervals of bi-weekly and weekly treatments showed statistically similar values for pulp: peel ratio, TSS, and reducing sugar of banana fruit when compared to the fruit quality parameters of the T1 treatment. Consequently, using fertilizer interval advised at weekly for the banana. The results highlight the significance of systematic fertigation scheduling and mulching procedures, providing insightful information for effective banana growing practices. [ABSTRACT FROM AUTHOR]

Plant growth regulators (PGRs) play an important role in increasing crop yield, and quality, and enhancing crop stress resistance in agricultural production, especially for important crops. PGRs can affect the transport and distribution of assimilates by changing the content and distribution of endogenous hormones in plants. Numerous empirical research results have proven that PGRs have an important impact on the growth, development, and yield composition of wheat. Taking wheat plants as an example, this study reviews the application of PGRs in wheat production and explores their impact on wheat growth and yield. Furthermore, residues and microbial degradation of PGRs are summarized in detail. Finally, future research directions on PGR application in wheat production are proposed. This summary is of great significance for understanding the role of PGRs in wheat production. [ABSTRACT FROM AUTHOR]

Numerous studies have attempted to pinpoint certain traits of rice varieties linked with great ratooning ability that may be used in cultural practice. However, both genetic and environmental variables affect rice's capacity for ratooning. We are able to measure the innovative ratooning ability that affects the decline in ratoon yield using the agronomic features of the main crop and ratoon rice in our global database for a meta‐analysis, drawn from 51 experiments in 14 countries. We discovered that changes in cultivar yield and maturity features, cropping location, and nitrogen fertilizer treatment may all affect a plant's capacity to tiller. On the other hand, the growth duration ratoon ability was less responsive to variations in cultivars and cropping location. We also found that ratooning changes the plant architecture for yield generation from bigger spikelets with fewer panicles to fewer spikelets (dropping 48%) with larger panicles (increasing 19%). We came to the conclusion based on our research that the decreased yield in ratoon crops may be caused by fast ear emergence and aggressive tillering, which negatively influence stem elongation, panicle differentiation, and a lack of nutrition, resulting in fewer spikelets (panicle−1). The present data are thoroughly summarized and analyzed in this research, which also clarifies the lack of knowledge around the characteristics that affect ratoon rice crop production. Core Ideas: A comprehensive global quantitative analysis was conducted to assess the ratoon rice's ratooning ability.The tillering–ratooning ability was found to be influenced by variations in genetic and environmental factors.Genetic and environmental variables may have little effect on ratoon crop growth duration.The plant architecture shifts from large spikelets in the main crop to large panicles in the ratoon crop.The accelerated ear emergence could have a detrimental impact on stem elongation during panicle differentiation. [ABSTRACT FROM AUTHOR]

Legumes being a major source of protein have a wide range of economic importance. But the major constraints in growing legumes are poor germination, seedling emergence, non uniform stand establishment and crop mortality leading to lower pulse productivity. Thus, pre-sowing seed treatments are critical parameters which attribute to efficient plant growth and high yield. Uniform seed germination, seedling growth and uniform establishment are the critical stages during the growth of crops. Seed priming is a very promising presowing treatment employed to improve seed germination, better crop establishment, enhance the seed quality and induces tolerance against biotic and abiotic stresses in plants thereby providing a balanced healthy diet to the citizens. Priming is a cost effective and feasible strategy involving controlled hydration of seeds followed by drying to stimulate the pre-germinative metabolic activities to occur promoting rapid germination of seedlings, break dormancy and enhance crop yield. Enzymatic, metabolic and biochemical processes of the primed seeds attributes to rapid and uniform seedling emergence. Seed priming methods comprises of conventional methods including hydro priming, osmopriming, biopriming, chemical priming and the advanced methods including nano priming and priming with physical agents. In this review paper, the underlying physiological, biochemical and molecular aspects of priming in pulses were discussed. [ABSTRACT FROM AUTHOR]

Soil salinization and alkalization are important abiotic stresses that affect crop growth and yield. Development of salt and alkali tolerant varieties is still dominated by the following conventional breeding method: The salt and alkali tolerant traits from screened germplasm are introduced into elite varieties by means of hybridization and backcrossing. In recent years, the breeding of salt and alkali tolerant rice has also made great progress. For example, the yield of Chao‐You 1000, a two‐line rice hybrid, has reached 12.04 t/ha growing in fields with salinity between 0.2% and 0.6%. This review is an update on the progress of salt and alkali tolerant rice germplasm screening and new salt and alkali tolerant varieties in development. By reviewing the performance of current rice hybrids in China's National Regional Variety Trials of Saline‐Alkali Tolerant Rice, we proposed the technical approach of developing saline–alkali tolerant rice hybrids using the third‐generation hybrid rice technology and furthermore the trend of developing salt and alkali tolerant rice hybrids. [ABSTRACT FROM AUTHOR]

This paper examines the optimal design for agri‐photovoltaic (agri‐PV) systems. Agri‐PV systems should be evaluated on the total crop yield and power generation, and the balance is essential. Specifically, the amount of solar irradiance reaching the farmland and power generation by PV systems varies by panel separation and tilt angle, affecting crop yield. Quantitative analysis is essential for balancing. This study investigated the balance between the output of Agri‐PV installed on farmland and photosynthetic photon flux density (PPFD), a crucial indicator for crop growth, and discussed the optimal solutions for Agri‐PV systems installed in various regions. Simulations were conducted for Miyazaki (semi‐tropical) and Nagano (inland climate) to understand the changes in different climate regions. Miyazaki has higher PPFD and PV output than Nagano because Miyazaki has more solar irradiance and longer sunshine duration than Nagano. When the normalized panel pitch is small, PPFD changes significantly by the tilt angle. When the normalized panel pitch is large, the profit may be maximized by setting the panel tilt angle to maximize the PV output. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Sustainable intensification of agriculture requires understanding of the effect of soil characteristics and nutrient supply on crop growth. As farms are increasing in size by acquiring small fields from various farmers, the soil characteristics and nutrient supply might be very different from field to field, while at the same time specific soil properties might limit the nutrient uptake. As a result, there might be a large number of heterogeneous reasons why crop growth varies significantly. New data analysis techniques can help to explain variability in crop growth among fields. This paper introduces Exceptional Growth Mining (EGM) as a first contribution. EGM instantiates the data mining framework Exceptional Model Mining (EMM) such that subgroups of fields can be found that grow exceptionally in terms of three growth parameters (high/low maximum growth, steep/flat linear growth and early/late midpoint of maximum growth). As second contribution, we apply EGM to a case study by analyzing the dataset of a potato farm in the south of the Netherlands. EGM consists of (i) estimating growth curves by applying nonlinear mixed models, (ii) investigating the correlation between the estimated growth parameters, and (iii) applying EMM on these growth curve parameters using a growth curve-specific quality measure. By applying EGM on the data of the potato farm, we obtain the following results: 1) the estimated growth curves represent the variability in potato tuber growth very well (R2 of 0.92), 2) the steepness of the growth curve has a strong correlation with the maximum growth and the midpoint of maximum growth, and the correlation between the midpoint of maximum growth and maximum growth is weak, 3) the subgroup analyses indicate that: high values of K correspond to high maxima; low values of K correspond to low maxima, steep growth curves', and a late midpoint of halfway growth; Mg influences the midpoint of the growth curve; values of B are higher on dry soils with high tuber growth, while low values of B are found on wet soils with high tuber growth; high values of Zn, Mn, and Fe are found in subgroups with low tuber weight, probably related to the soil's low pH. In summary, this paper introduces EGM to obtain understanding in crop response to soil properties and nutrient supply. In addition, EGM provides a way to analyze only small parts of a large dataset, such that the impact of soil factors on growth can be analyzed on a more detailed level than existing methods. [ABSTRACT FROM AUTHOR]

Summary: Drought and the availability of nitrate, the predominant source of nitrogen (N) in agriculture, are major factors limiting plant growth and crop productivity. The dissection of the transcriptional networks' components integrating droght stress and nitrate responses provides valuable insights into how plants effectively balance stress response with growth programs. Recent evidence in Arabidopsis thaliana indicates that transcription factors (TFs) involved in abscisic acid (ABA) signaling affect N metabolism and nitrate responses, and reciprocally, components of nitrate signaling might affect ABA and drought gene responses. Advances in understanding regulatory circuits of nitrate and drought crosstalk in plant tissues empower targeted genetic modifications to enhance plant development and stress resistance, critical traits for optimizing crop yield and promoting sustainable agriculture. [ABSTRACT FROM AUTHOR]

Crop mapping is vital in ensuring food production security and informing governmental decision-making. The satellite-normalized difference vegetation index (NDVI) obtained during periods of vigorous crop growth is important for crop species identification. Sentinel-2 images with spatial resolutions of 10, 20, and 60 m are widely used in crop mapping. However, the images obtained during periods of vigorous crop growth are often covered by clouds. In contrast, time-series moderate-resolution imaging spectrometer (MODIS) images can usually capture crop phenology but with coarse resolution. Therefore, a time-series-based spatiotemporal fusion network (TSSTFN) was designed to generate TSSTFN-NDVI during critical phenological periods for finer-scale crop mapping. This network leverages multi-temporal MODIS-Sentinel-2 NDVI pairs from previous years as a reference to enhance the precision of crop mapping. The long short-term memory module was used to acquire data about the time-series change pattern to achieve this. The UNet structure was employed to manage the spatial mapping relationship between MODIS and Sentinel-2 images. The time distribution of the image sequences in different years was inconsistent, and time alignment strategies were used to process the reference data. The results demonstrate that incorporating the predicted critical phenological period NDVI consistently yields better crop classification performance. Moreover, the predicted NDVI trained with time-consistent data achieved a higher classification accuracy than the predicted NDVI trained with the original NDVI. [ABSTRACT FROM AUTHOR]

Boro rice (irrigated rice) cultivation in the saline area of the coastal region of Bangladesh is limited because of increased soil and water salinity, lack of freshwater for irrigation and proper agronomic practices. An on-farm field trial was conducted in the farmer's field at Dacope upazila in Khulna district of Bangladesh during the dry season (Boro) in 2022-23 to evaluate the growth and yield of Boro rice with different establishment methods and soil salinity dynamics with each type of establishment. The tested establishment methods were: (i) conventional tillage wet direct seeding (CTWDS), (ii) no-tillage wet direct seeding (NTWDS), (iii) conventional tillage transplanting rice (CTTP) and (iv) conventional tillage dry direct seeding (CTDDS). Grain yield was significantly higher (13-63%) in CTTP treatment than the other treatments. The direct seeding methods saved irrigation water but had a lower panicle-bearing tiller and grain per panicle which was related to lower yield. The direct seeding methods had also higher soil salinity. In conclusion, Boro rice cultivation with conventional transplanting (CTTP) method in the saline area maintained a higher yield and lower soil salinity than the direct seeding method. [ABSTRACT FROM AUTHOR]

This article, published in the journal Environment & Ecology, discusses the impact of organic manure and bio-fertilizers on the growth and yield of summer squash. The researchers conducted an experiment with twelve different treatments and observed various growth and yield parameters. The results showed that the treatment with Azotobacter and vermicompost resulted in better growth, yield, and quality. The study suggests that the use of organic and bio-fertilizers can promote sustainable production of summer squash. Additionally, the document provides a list of references for further research on the effect of integrated nutrient management and fertilizers on various crops. [Extracted from the article]

The article presents a study conducted in Uttar Pradesh, India, which aimed to determine the optimal transplanting date and bed conditions for year-round production of Agrifound Dark Red onions. The results showed that transplanting on October 1st resulted in the highest vegetative growth, while transplanting on November 1st produced the maximum bulb yield. Raised bed conditions showed better performance in terms of growth and yield. The study concludes that transplanting on October 1st is recommended for maximum onion production in central Uttar Pradesh. The document provides data on the effects of different planting dates and bed types on various parameters of onion cultivation, such as leaf length, neck thickness, number of leaves, and bulb yield. The findings suggest that specific combinations of planting dates and bed types can influence the growth and yield of onion crops. The study also highlights the impact of weather conditions, particularly heavy rainfall during the monsoon season, on the crop. Overall, the study recommends transplanting in early October on raised beds as the most favorable method for onion production in central Uttar Pradesh. [Extracted from the article]

This article presents the findings of a field experiment conducted in West Bengal to study the growth, yield, and water use efficiency of grass pea under different nutrient management practices. The results showed that fertilizing the grass pea plot with the recommended dose of fertilizer along with foliar application of Borax resulted in the highest plant height, number of branches, dry matter accumulation, number of pods per plant, pod length, number of seeds per pod, and 100-seed weight. The plot treated with RDF+ Borax also recorded the highest seed yield, stover yield, and water use efficiency. The study concludes that the combined use of RDF with Borax is the best option for better production of grass pea in terms of quality and quantity in the New Alluvial Zone of West Bengal. [Extracted from the article]

This article discusses a field experiment that studied the impact of pre and post emergence herbicides on the growth and yield of chickpea. The results showed that the sequential application of Pendimethalin and Propaquizafop herbicides resulted in lower weed population, higher weed control efficiency, and higher grain yield compared to other treatments. The article also provides information on the importance of weed control in chickpea cultivation and the significance of chickpea production in India. The study concluded that the recommended herbicide treatment was the most effective for weed management in chickpea cultivation. [Extracted from the article]