Crop Journal 

About: Crop Journal is an academic journal published by KeAi. The journal publishes majorly in the area(s): Biology & Gene. It has an ISSN identifier of 2214-5141. It is also open access. Over the lifetime, 935 publications have been published receiving 18787 citations. The journal is also known as: Zuowu xuebao.

QTL IciMapping: Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations

Abstract: QTL IciMapping is freely available public software capable of building high-density linkage maps and mapping quantitative trait loci (QTL) in biparental populations. Eight functionalities are integrated in this software package: (1) BIN: binning of redundant markers; (2) MAP: construction of linkage maps in biparental populations; (3) CMP: consensus map construction from multiple linkage maps sharing common markers; (4) SDL: mapping of segregation distortion loci; (5) BIP: mapping of additive, dominant, and digenic epistasis genes; (6) MET: QTL-by-environment interaction analysis; (7) CSL: mapping of additive and digenic epistasis genes with chromosome segment substitution lines; and (8) NAM: QTL mapping in NAM populations. Input files can be arranged in plain text, MS Excel 2003, or MS Excel 2007 formats. Output files have the same prefix name as the input but with different extensions. As examples, there are two output files in BIN, one for summarizing the identified bin groups and deleted markers in each bin, and the other for using the MAP functionality. Eight output files are generated by MAP, including summary of the completed linkage maps, Mendelian ratio test of individual markers, estimates of recombination frequencies, LOD scores, and genetic distances, and the input files for using the BIP, SDL, and MET functionalities. More than 30 output files are generated by BIP, including results at all scanning positions, identified QTL, permutation tests, and detection powers for up to six mapping methods. Three supplementary tools have also been developed to display completed genetic linkage maps, to estimate recombination frequency between two loci, and to perform analysis of variance for multi-environmental trials.

Phytohormones and their metabolic engineering for abiotic stress tolerance in crop plants

Abstract: Abiotic stresses including drought, salinity, heat, cold, flooding, and ultraviolet radiation causes crop losses worldwide. In recent times, preventing these crop losses and producing more food and feed to meet the demands of ever-increasing human populations have gained unprecedented importance. However, the proportion of agricultural lands facing multiple abiotic stresses is expected only to rise under a changing global climate fueled by anthropogenic activities. Identifying the mechanisms developed and deployed by plants to counteract abiotic stresses and maintain their growth and survival under harsh conditions thus holds great significance. Recent investigations have shown that phytohormones, including the classical auxins, cytokinins, ethylene, and gibberellins, and newer members including brassinosteroids, jasmonates, and strigolactones may prove to be important metabolic engineering targets for producing abiotic stress-tolerant crop plants. In this review, we summarize and critically assess the roles that phytohormones play in plant growth and development and abiotic stress tolerance, besides their engineering for conferring abiotic stress tolerance in transgenic crops. We also describe recent successes in identifying the roles of phytohormones under stressful conditions. We conclude by describing the recent progress and future prospects including limitations and challenges of phytohormone engineering for inducing abiotic stress tolerance in crop plants.

Magnesium deficiency in plants: An urgent problem

Abstract: Although magnesium (Mg) is one of the most important nutrients, involved in many enzyme activities and the structural stabilization of tissues, its importance as a macronutrient ion has been overlooked in recent decades by botanists and agriculturists, who did not regard Mg deficiency (MGD) in plants as a severe health problem. However, recent studies have shown, surprisingly, that Mg contents in historical cereal seeds have markedly declined over time, and two thirds of people surveyed in developed countries received less than their minimum daily Mg requirement. Thus, the mechanisms of response to MGD and ways to increase Mg contents in plants are two urgent practical problems. In this review, we discuss several aspects of MGD in plants, including phenotypic and physiological changes, cell Mg2 + homeostasis control by Mg2 + transporters, MGD signaling, interactions between Mg2 + and other ions, and roles of Mg2 + in plant secondary metabolism. Our aim is to improve understanding of the influence of MGD on plant growth and development and to advance crop breeding for Mg enrichment.

From leaf to whole-plant water use efficiency (WUE) in complex canopies: Limitations of leaf WUE as a selection target

Abstract: Plant water use efficiency (WUE) is becoming a key issue in semiarid areas, where crop production relies on the use of large volumes of water. Improving WUE is necessary for securing environmental sustainability of food production in these areas. Given that climate change predictions include increases in temperature and drought in semiarid regions, improving crop WUE is mandatory for global food production. WUE is commonly measured at the leaf level, because portable equipment for measuring leaf gas exchange rates facilitates the simultaneous measurement of photosynthesis and transpiration. However, when those measurements are compared with daily integrals or whole-plant estimates of WUE, the two sometimes do not agree. Scaling up from single-leaf to whole-plant WUE was tested in grapevines in different experiments by comparison of daily integrals of instantaneous water use efficiency [ratio between CO2 assimilation (AN) and transpiration (E); AN/E] with midday AN/E measurements, showing a low correlation, being worse with increasing water stress. We sought to evaluate the importance of spatial and temporal variation in carbon and water balances at the leaf and plant levels. The leaf position (governing average light interception) in the canopy showed a marked effect on instantaneous and daily integrals of leaf WUE. Night transpiration and respiration rates were also evaluated, as well as respiration contributions to total carbon balance. Two main components were identified as filling the gap between leaf and whole plant WUE: the large effect of leaf position on daily carbon gain and water loss and the large flux of carbon losses by dark respiration. These results show that WUE evaluation among genotypes or treatments needs to be revised.

Estimation of biomass in wheat using random forest regression algorithm and remote sensing data

Abstract: Wheat biomass can be estimated using appropriate spectral vegetation indices. However, the accuracy of estimation should be further improved for on-farm crop management. Previous studies focused on developing vegetation indices, however limited research exists on modeling algorithms. The emerging Random Forest (RF) machine-learning algorithm is regarded as one of the most precise prediction methods for regression modeling. The objectives of this study were to (1) investigate the applicability of the RF regression algorithm for remotely estimating wheat biomass, (2) test the performance of the RF regression model, and (3) compare the performance of the RF algorithm with support vector regression (SVR) and artificial neural network (ANN) machine-learning algorithms for wheat biomass estimation. Single HJ-CCD images of wheat from test sites in Jiangsu province were obtained during the jointing, booting, and anthesis stages of growth. Fifteen vegetation indices were calculated based on these images. In-situ wheat above-ground dry biomass was measured during the HJ-CCD data acquisition. The results showed that the RF model produced more accurate estimates of wheat biomass than the SVR and ANN models at each stage, and its robustness is as good as SVR but better than ANN. The RF algorithm provides a useful exploratory and predictive tool for estimating wheat biomass on a large scale in Southern China.