Machine learning ensembles, neural network, hybrid and sparse regression approaches for weather based rainfed cotton yield forecast.

Cotton is a major economic crop predominantly cultivated under rainfed situations. The accurate prediction of cotton yield invariably helps farmers, industries, and policy makers. The final cotton yield is mostly determined by the weather patterns that prevail during the crop growing phase. Crop yield prediction with greater accuracy is possible due to the development of innovative technologies which analyses the bigdata with its high-performance computing abilities. Machine learning technologies can make yield prediction reasonable and faster and with greater flexibility than process based complex crop simulation models. The present study demonstrates the usability of ML algorithms for yield forecasting and facilitates the comparison of different models. The cotton yield was simulated by employing the weekly weather indices as inputs and the model performance was assessed by nRMSE, MAPE and EF values. Results show that stacked generalised ensemble model and artificial neural networks predicted the cotton yield with lower nRMSE, MAPE and higher efficiency compared to other models. Variable importance studies in LASSO and ENET model found minimum temperature and relative humidity as the main determinates of cotton yield in all districts. The models were ranked based these performance metrics in the order of Stacked generalised ensemble > ANN > PCA ANN > SMLR ANN > LASSO> ENET > SVM > PCA SMLR > SMLR SVM > SMLR. This study shows that stacked generalised ensembling and ANN method can be used for reliable yield forecasting at district or county level and helps stakeholders in timely decision-making.

Drought and salinity stresses induced physio-biochemical changes in sugarcane: an overview of tolerance mechanism and mitigating approaches.

Sugarcane productivity is being hampered globally under changing environmental scenarios like drought and salinity. The highly complex nature of the plant responses against these stresses is determined by a variety of factors such as genotype, developmental phase of the plant, progression rate and stress, intensity, and duration. These factors influence plant responses and can determine whether mitigation approaches associated with acclimation are implemented. In this review, we attempt to summarize the effects of drought and salinity on sugarcane growth, specifically on the plant's responses at various levels, viz., physiological, biochemical, and metabolic responses, to these stresses. Furthermore, mitigation strategies for dealing with these stresses have been discussed. Despite sugarcane's complex genomes, conventional breeding approaches can be utilized in conjunction with molecular breeding and omics technologies to develop drought- and salinity-tolerant cultivars. The significant role of plant growth-promoting bacteria in sustaining sugarcane productivity under drought and salinity cannot be overlooked.

Balancing water and radiation productivity suggests a clue for improving yields in wheat under combined water deficit and terminal heat stress.

Sustaining crop yield under abiotic stresses with optimized resource use is a prerequisite for sustainable agriculture, especially in arid and semi-arid areas. Water and heat stress are major abiotic stresses impacting crop growth and yield by influencing complex physiological and biochemical processes during the life cycle of crops. In a 2-year (2015-2017) research, spring wheat cv. HD-2967 was grown under deficit irrigation and delayed sowing conditions to impose water and terminal heat stresses, respectively. The data were analyzed for seasonal crop water use, radiation interception, water productivity (WP), and radiation productivity (RP) under combined water deficit and terminal heat stresses. Seasonal crop water use was significantly affected by stresses in the order of water + terminal heat > water > terminal heat. Water stress showed minimal effect on the light extinction coefficient and consequently on seasonal intercepted photosynthetically active radiation (IPAR). However, seasonal IPAR was primarily affected by combined water + terminal heat and terminal heat stress alone. The slope of crop water use and IPAR, i.e., canopy conductance, an indicator of canopy stomatal conductance, was more influenced by water stress than by terminal heat stress. Results showed that linear proportionality between WP and RP is no longer valid under stress conditions, as it follows a curvilinear relation. This is further supported by the fact that independent productivity (either water or radiation) lacked the ability to explain variability in the final economic yield or biomass of wheat. However, the ratio of RP to WP explained the variability in wheat yield/biomass under individual or combined stresses. This suggests a clue for improving higher wheat yield under stress by managing WP and RP. The highest biomass or yield is realized when the ratio of RP to WP approaches unity. Screening of genotypes for traits leading to a higher ratio of RP to WP provides an opportunity for improving wheat productivity under stressed environments.

Hydrogen Peroxide and GA3 Levels Regulate the High Night Temperature Response in Pistils of Wheat (Triticum aestivum L.).

High night temperature (HNT) impairs crop productivity through the reproductive failure of gametes (pollen and pistil). Though female gametophyte (pistil) is an equal partner in the seed-set, the knowledge of the antioxidant system(s) and hormonal control of HNT tolerance or susceptibility of pistils is limited and lacking. The objectives of this study were to determine the antioxidant mechanism for homeostatic control of free radicals, and the involvement of abscisic acid (ABA) and gibberellic acid (GA3) in HNT stress protection in the wheat pistils of contrasting wheat genotypes. We hypothesized that HNT tolerance is attributed to the homeostatic control of reactive oxygen species (ROS) and hormonal readjustment in pistils of the tolerant genotype. The ears of two contrasting wheat genotypes-HD 2329 (susceptible) and Raj 3765 (tolerant) were subjected to two HNTs (+5 °C and +8 °C) over ambient, in the absence and presence of dimethylthiourea (DMTU), a chemical trap of hydrogen peroxide (H2O2). Results showed that HNTs significantly increased ROS in pistils of susceptible genotype HD 2329 to a relatively greater extent compared to tolerant genotype Raj 3765. The response was similar in the presence or absence of DMTU, but the H2O2 values were lower in the presence of DMTU. The ROS levels were balanced by increased activity of peroxidase under HNT to a greater extent in the tolerant genotype. Cytosolic glyceraldehyde-3-phosphate dehydrogenase (GAPC) activity was inversely related to H2O2 production within a critical range in Raj 3765, indicating its modulation by H2O2 levels as no change was observed at the transcriptional level. The hormonal status showed increased ABA and decreased GA3 contents with increasing temperature. Our study elucidates the role of H2O2 and GA3 in stress tolerance of pistils of tolerant genotype where GAPC acts as a ROS sensor due to H2O2-mediated decrease in its activity.

Targeting Apoptotic Pathway of Cancer Cells with Phytochemicals and Plant-Based Nanomaterials.

Apoptosis is the elimination of functionally non-essential, neoplastic, and infected cells via the mitochondrial pathway or death receptor pathway. The process of apoptosis is highly regulated through membrane channels and apoptogenic proteins. Apoptosis maintains cellular balance within the human body through cell cycle progression. Loss of apoptosis control prolongs cancer cell survival and allows the accumulation of mutations that can promote angiogenesis, promote cell proliferation, disrupt differentiation, and increase invasiveness during tumor progression. The apoptotic pathway has been extensively studied as a potential drug target in cancer treatment. However, the off-target activities of drugs and negative implications have been a matter of concern over the years. Phytochemicals (PCs) have been studied for their efficacy in various cancer cell lines individually and synergistically. The development of nanoparticles (NPs) through green synthesis has added a new dimension to the advancement of plant-based nanomaterials for effective cancer treatment. This review provides a detailed insight into the fundamental molecular pathways of programmed cell death and highlights the role of PCs along with the existing drugs and plant-based NPs in treating cancer by targeting its programmed cell death (PCD) network.

Systems biology of chromium-plant interaction: insights from omics approaches.

Plants are frequently subjected to heavy metal (HM) stress that impedes their growth and productivity. One of the most common harmful trace metals and HM discovered is chromium (Cr). Its contamination continues to increase in the environment due to industrial or anthropogenic activities. Chromium is severely toxic to plant growth and development and acts as a human carcinogen that enters the body by inhaling or taking Cr-contaminated food items. Plants uptake Cr via various transporters, such as sulfate and phosphate transporters. In nature, Cr is found in various valence states, commonly Cr (III) and Cr (VI). Cr (VI) is soil's most hazardous and pervasive form. Cr elevates reactive oxygen species (ROS) activity, impeding various physiological and metabolic pathways. Plants have evolved various complex defense mechanisms to prevent or tolerate the toxic effects of Cr. These defense mechanisms include absorbing and accumulating Cr in cell organelles such as vacuoles, immobilizing them by forming complexes with organic chelates, and extracting them by using a variety of transporters and ion channels regulated by various signaling cascades and transcription factors. Several defense-related proteins including, metallothioneins, phytochelatins, and glutathione-S-transferases aid in the sequestration of Cr. Moreover, several genes and transcriptional factors, such as WRKY and AP2/ERF TF genes, play a crucial role in defense against Cr stress. To counter HM-mediated stress stimuli, OMICS approaches, including genomics, proteomics, transcriptomics, and metallomics, have facilitated our understanding to improve Cr stress tolerance in plants. This review discusses the Cr uptake, translocation, and accumulation in plants. Furthermore, it provides a model to unravel the complexities of the Cr-plant interaction utilizing system biology and integrated OMICS approach.

Multigene phylogeny and haplotype analysis reveals predominance of oomycetous fungus, Phytophthora meadii (McRae) associated with fruit rot disease of arecanut in India.

An oomycetous fungus Phytophthora causing fruit rot is the most devastating disease of arecanut in different agro-climatic zones of Karnataka with varied climatic profiles. The main aim of this investigation was to characterize the geo-distant Phytophthora populations infecting arecanut using robust morphological, multi-gene phylogeny and haplotype analysis. A total of 48 geo-distant fruit rot infected samples were collected during the South-West monsoon of 2017-19. Pure culture of the suspected pathogen was isolated from the infected nuts and pathogenic ability was confirmed and characterized. Colony morphology revealed typical whitish mycelium with stellate or petalloid pattern and appearance with torulose hyphae. Sporangia were caducous, semipapillate or papillate, globose, ellipsoid or ovoid-obpyriform in shape and sporangiophores were irregularly branched or simple sympodial in nature. Subsequent multi-gene phylogeny (ITS, ß-tub, TEF-1α and Cox-II) and sequence analysis confirmed the identity of oomycete as Phytophthora meadii which is predominant across the regions studied. We identified 49 haplotypes representing the higher haplotype diversity with varying relative haplotype frequency. Comprehensive study confirmed the existence of substantial variability among geo-distant populations (n = 48) of P. meadii. The knowledge on population dynamics of the pathogen causing fruit rot of arecanut generated from this investigation would aid in developing appropriate disease management strategies to curtail its further occurrence and spread in arecanut ecosystem.

Impacts, Tolerance, Adaptation, and Mitigation of Heat Stress on Wheat under Changing Climates.

Heat stress (HS) is one of the major abiotic stresses affecting the production and quality of wheat. Rising temperatures are particularly threatening to wheat production. A detailed overview of morpho-physio-biochemical responses of wheat to HS is critical to identify various tolerance mechanisms and their use in identifying strategies to safeguard wheat production under changing climates. The development of thermotolerant wheat cultivars using conventional or molecular breeding and transgenic approaches is promising. Over the last decade, different omics approaches have revolutionized the way plant breeders and biotechnologists investigate underlying stress tolerance mechanisms and cellular homeostasis. Therefore, developing genomics, transcriptomics, proteomics, and metabolomics data sets and a deeper understanding of HS tolerance mechanisms of different wheat cultivars are needed. The most reliable method to improve plant resilience to HS must include agronomic management strategies, such as the adoption of climate-smart cultivation practices and use of osmoprotectants and cultured soil microbes. However, looking at the complex nature of HS, the adoption of a holistic approach integrating outcomes of breeding, physiological, agronomical, and biotechnological options is required. Our review aims to provide insights concerning morpho-physiological and molecular impacts, tolerance mechanisms, and adaptation strategies of HS in wheat. This review will help scientific communities in the identification, development, and promotion of thermotolerant wheat cultivars and management strategies to minimize negative impacts of HS.

Heat stress tolerance in peas (Pisum sativum L.): Current status and way forward.

In the era of climate change, the overall productivity of pea (Pisum sativum L.) is being threatened by several abiotic stresses including heat stress (HS). HS causes severe yield losses by adversely affecting several traits in peas. A reduction in pod yield has been reported from 11.1% to 17.5% when mean daily temperature increase from 1.4 to 2.2°C. High-temperature stress (30.5-33°C) especially during reproductive phase is known to drastically reduce both seed yield and germination. HS during germination and early vegetative stage resulted in poor emergence and stunted plant growth along with detrimental effects on physiological functions of the pea plant. To combat HS and continue its life cycle, plants use various defense strategies including heat escape, avoidance or tolerance mechanisms. Ironically, the threshold temperatures for pea plant and its responses are inconsistent and not yet clearly identified. Trait discovery through traditional breeding such as semi leaflessness (afila), upright growing habit, lodging tolerance, lower canopy temperature and small seeded nature has highlighted their utility for greater adaptation under HS in pea. Screening of crop gene pool and landraces for HS tolerance in a targeted environment is a simple approach to identify HS tolerant genotypes. Thus, precise phenotyping using modern phenomics tools could lead to increased breeding efficiency. The NGS (next generation sequencing) data can be associated to find the candidate genes responsible for the HS tolerance in pea. In addition, genomic selection, genome wide association studies (GWAS) and marker assisted selection (MAS) can be used for the development of HS tolerant pea genotypes. Additionally, development of transgenics could be an alternative strategy for the development of HS tolerant pea genotypes. This review comprehensively covers the various aspects of HS tolerance mechanisms in the pea plant, screening protocols, omic advances, and future challenges for the development of HS tolerant genotypes.

Effect of Foliar Micronutrients (B, Mn, Fe, Zn) on Maize Grain Yield, Micronutrient Recovery, Uptake, and Partitioning.

Timing of micronutrient demand and acquisition by maize (Zea mays L.) is nutrient specific and associated with key vegetative and reproductive growth stages. The objective of this study was to determine the fate of foliar-applied B, Fe, Mn, Zn, and Fe/Zn together, evaluate the effect of foliar micronutrients applied at multiple rates and growth stages on maize grain yield, and determine their apparent nutrient recovery efficiency (ANR). Five Randomized Complete Block Design (RCBD) experiments were conducted in 2014 and 2015 at five locations across Nebraska. Total dry matter was collected at 5-6 stages, and separated into leaves, stalk, and reproductive tissue as appropriate to determine micronutrient uptake, partitioning, and translocation. Foliar B, Mn, Zn, and Fe/Zn had no effect on grain yield for most application time by rate levels, though, at the foliar Mn site, there was a 19% yield increase due to a V18 application of 0.73 kg Mn ha-1 which corresponded with reduced Mn uptake in maize grown in control plots. At the foliar Zn site, there was 4.5% decrease in yield due to a split foliar application of 0.84 kg Zn ha-1 total, applied at V11 and V15 stage, which increased leaf Zn concentrations greater than the established toxic level. Only the Fe site had consistent grain yield response and was the only experiment that had visual signs of micronutrient deficiency. Regardless of application time from V6 to R2, there was a 13.5-14.6% increase in grain yield due to 0.22 kg Fe ha-1 foliar application. Most micronutrients had limited or no translocation, however, early season applications of B, prior to V10, had significant mobilization to reproductive tissues at or after VT. Foliar Mn, Zn, and B application had ANR LSmeans of 9.5, 16.9, and 2.5%, respectively, whereas the Fe/Zn mix had negative ANR LSmeans of -9.1% Fe and -1.3% Zn which indicate suppression. These data highlight the importance of confirming a micronutrient deficiency prior to foliar application, guide specific growth stages to target with specific micronutrients, track the fate of foliar-applied micronutrients, and describe the variable effect of foliar-applied micronutrients on grain yield.

Differential white blood cell count in the COVID-19: A cross-sectional study of 148 patients.

BACKGROUND: SARS-CoV-2 infection alters various blood parameters, which may indicate disease severity and thus help in better clinical management. AIM: To study the association between various hematological parameters and disease severity of COVID-19. To analyze the effects of hypertension and diabetes on neutrophil-lymphocyte ratio and neutrophil-monocyte ratio in patients suffering from COVID-19. MATERIALS AND METHODS: The study was a cross-sectional study involving 148 laboratory-confirmed cases of SARS-CoV-2 infection. The patients were divided into three groups on the basis of disease severity. Various hematological parameters were analyzed. The effects of hypertension and diabetes on NLR and NMR in COVID-19 patients were evaluated. RESULTS: Of the 148 patients, 78.4%, 8.1% and 13.5% cases were in the mild, moderate and severe groups, respectively. Mean age was 42.63 ± 16.04 years (IQR: 29, 54.75; Range: 7-74). 58.8% patients were male while the rest (42.2%) were female. Mean TLC (cells/mm3), neutrophil (%), lymphocyte (%), monocyte (%), eosinophil (%), neutrophil-lymphocyte ratio (NLR) and neutrophil-monocyte ratio (NMR) among mild, moderate and severe COVID-19 was statistically significant (p < 0.05). Basophil (%) and lymphocyte-monocyte ratio (LMR) was statistically insignificant among the three groups. Lymphocyte (%), monocyte (%) and eosinophil (%) were negatively correlated to disease severity. Among diabetics, both NLR and NMR were statistically significant (p < 0.05). However, among hypertensive cases, only the NLR was statistically significant. CONCLUSION: Older age, higher TLC, neutrophilia, lymphopenia, eosinopenia, high NLR and high NMR are associated with severe COVID-19. High NLR and high NMR are indicative of severe disease among diabetic patients. High NLR also indicates severe disease among hypertensive patients.